Article

# Kinematic Parameters to Evaluate Functional Performance of Sit-to-Stand and Stand-to-Sit Transitions Using Motion Sensor Devices: A Systematic Review

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## Abstract

Clinicians commonly use questionnaires and tests based on daily life activities to evaluate physical function. However, the outcomes are usually more qualitative than quantitative and subtle differences are not detectable. In this review, we aim to assess the role of body motion sensors in physical performance evaluation, especially for the sit-to-stand and stand-to-sit transitions. In total, 53 full papers and conference abstracts on related topics were included and different parameters related to transition performance were identified as potentially meaningful to explain certain disabilities and impairments. Transition duration is the most used to evaluate chair-related tests in real clinical settings. High-fall-risk fallers and frail subjects presented longer and more variable 15 transition duration. Other kinematic parameters have also been 16 highlighted in the literature as potential means to detect age related impairments. In particular, vertical linear velocity and trunk tilt range were able to differentiate between different frailty levels. Frequency domain measures such as spectral edge frequency were also higher for elderly fallers. Lastly, approximate entropy values were larger for subjects with Parkinson's disease and were significantly reduced after treatment. This information could help clinicians in their evaluations as well as in prescribing a physical fitness program to correct a specific deficit.

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... More specifically, more falls occur during STS (including stand-to-sit) compared to walking, especially in residents with higher fall frequency (Rapp et al., 2012;Pozaic et al., 2016;van Schooten et al., 2017). As falls are the number one cause of injuries in older adults over the age of 65, it is imperative to understand and improve their STS performance (Janssen et al., 2002;Millor et al., 2014). ...
... STS is considered the most mechanically demanding task of common daily activities, requiring leg muscle strength, coordination, and balance control (Riley et al., 1997;Millor et al., 2014). Limitations in any one of these factors is suggested to cause poor STS ability, resulting in STS attempts that fail, leaving older adults to sit back down or take a step if possible, potentially creating an even more unstable situation. ...
... Clinical tests commonly measure the duration of, or ability to perform, a number of STS movements, which yields little information regarding any underlying problems (Bohannon, 2012;Silva et al., 2014). Biomechanical studies have described the STS motion, different STS compensatory strategies, and evaluated the effect of factors, such as chair height and foot placement on STS difficulty (Aissaoui and Dansereau, 1999;Janssen et al., 2002;Millor et al., 2014;Boukadida et al., 2015). Only a few studies have aimed to evaluate balance during STS using metrics such as transfer duration, body or trunk dynamics around seat-off, or the location of the body's center of mass or pressure relative to the ankle at seat-off (Moxley Scarborough et al., 1999;Åberg et al., 2010;Akram and McIlroy, 2011;Fujimoto and Chou, 2014). ...
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Many older adults suffer injuries due to falls as the ability to safely move between sitting and standing degrades. Unfortunately, while existing measures describe sit-to-stand (STS) performance, they do not directly measure the conditions for balance. To gain insight into the effect of age on STS balance, we analyzed how far 8 older and 10 young adults strayed from a state of static balance and how well each group maintained dynamic balance. Static balance was evaluated using the position of the center-of-mass (COM) and center-of-pressure (COP), relative to the functional base-of-support (BOS). As the name suggests, static balance applies when the linear and angular velocity of the body is small in magnitude, in the range of that observed during still standing. Dynamic balance control was evaluated using a model-based balance metric, the foot-placement-estimator (FPE), relative to the COP and BOS. We found that the older adults stay closer to being statically balanced than the younger participants. The dynamic balance metrics show that both groups keep the FPE safely within the BOS, though the older adults maintain a larger dynamic balance margin. Both groups exhibit similar levels of variability in these metrics. Thus, the conservative STS performance in older adults is likely to compensate for reduced physical ability or reduced confidence, as their dynamic balance control does not seem affected. The presented analysis of both static and dynamic balance allows us to distinguish between STS performance and balance, and as such can contribute to the identification of those older adults prone to falling, thus ultimately reducing the number of falls during STS transfers.
... The sit-to-stand (STS) movement is one of the most commonly performed daily tasks (Nuzik et al., 1986). This postural transition requires coordination, balance, strength and muscle power (Millor et al., 2014) which become difficult with age (Alexander et al., 1991). Mobility is reduced with age due to illness, trauma, or progressive deconditioning i.e. sarcopenia, osteoporosis (Millor et al., 2014). ...
... This postural transition requires coordination, balance, strength and muscle power (Millor et al., 2014) which become difficult with age (Alexander et al., 1991). Mobility is reduced with age due to illness, trauma, or progressive deconditioning i.e. sarcopenia, osteoporosis (Millor et al., 2014). The STS transition is often used to monitor the seniors and evaluate physical performance (Mijnarends et al., 2013). ...
... In practice, the clinical evaluation of the STS is based on motion description to investigate motor strategy modification (Millington et al., 1992). As quantification, the task duration is classically used as a descriptor of the STS transition performance (Beauchet et al., 2011;Millor et al., 2014). However this parameter is global, and not specific enough to quantify deficit in seniors (Lepetit et al., 2018). ...
Article
Background: Sit-to-stand is used as a qualitative test to evaluate functional performance, especially to detect fall risks and frail individuals. The use of various quantitative criteria would enable a better understanding of musculoskeletal deficits and movement strategy modifications. This quantification was proven possible with a magneto-inertial unit which provides a compatible wearable device for clinical routine motion analysis. Methods: Sit-to-stand movements were recorded using a single magneto-inertial measurement unit fixed on the chest for 74 subjects in three groups healthy young, healthy senior and frail. MIMU data was used to compute 15 spatiotemporal, kinematic and energetic parameters. Nonparametric statistical test showed a significant influence of age and frailness. After reducing the number of parameters by a principal component analysis, an AgingScore and a FrailtyScore were computed. Findings: The fraction of variance explained by the first principal component was 77.48 ± 2.80% for principal component analysis with healthy young and healthy senior groups, and 74.94 ± 2.24% with healthy and frail senior groups. By receiver operating characteristic curve analysis of this score, we were able to refine the analysis to differentiate between healthy young and healthy senior subjects as well as healthy senior and frail subjects. By radar plot of the most discriminate parameters, the motion's strategy could be characterized and be used to detect premature functional deficit or frail subjects. Interpretation: Sit-to-stand measured by a single magneto-inertial unit and dedicated post processing is able to quantify subject's musculoskeletal performance and will allow longitudinal investigation of aging population.
... One of the determinant factors of such a system is the specifics of the sensing device. According to Millor et al., the study of SiSt and stand-to-sit (StSi) transitions with inertial sensors can be traced back to the mid-1990s [21]; in particular to Kerr et al., in 1994 [22]. Over half of the works that Millor et al. reviewed were based on the assessment of daily life activities [21]. ...
... According to Millor et al., the study of SiSt and stand-to-sit (StSi) transitions with inertial sensors can be traced back to the mid-1990s [21]; in particular to Kerr et al., in 1994 [22]. Over half of the works that Millor et al. reviewed were based on the assessment of daily life activities [21]. Only a few of them involved the assessment of repeated SiSt/StSi cycles in traditional tests for frailty assessment [21]. ...
... Over half of the works that Millor et al. reviewed were based on the assessment of daily life activities [21]. Only a few of them involved the assessment of repeated SiSt/StSi cycles in traditional tests for frailty assessment [21]. While some works relied on the use of multiple devices on different parts of the body, a low number of devices is recommendable to simplify the setup, lower the cost, and eventually improve acceptance and adoption. ...
Article
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The present paper describes a system for older people to self-administer the 30-s chair stand test (CST) at home without supervision. The system comprises a low-cost sensor to count sit-to-stand (SiSt) transitions, and an Android application to guide older people through the procedure. Two observational studies were conducted to test (i) the sensor in a supervised environment (n = 7; m = 83.29 years old, sd = 4.19; 5 female), and (ii) the complete system in an unsupervised one (n = 7; age 64-74 years old; 3 female). The participants in the supervised test were asked to perform a 30-s CST with the sensor, while a member of the research team manually counted valid transitions. Automatic and manual counts were perfectly correlated (Pearson's r = 1, p = 0.00). Even though the sample was small, none of the signals around the critical score were affected by harmful noise; p (harmless noise) = 1, 95% CI = (0.98, 1). The participants in the unsupervised test used the system in their homes for a month. None of them dropped out, and they reported it to be easy to use, comfortable, and easy to understand. Thus, the system is suitable to be used by older adults in their homes without professional supervision.
... In physiotherapy and epidemiology, relationships between the IADL scales and some daily motion parameters are known, which allows us to investigate a sensing-based approach for IADL evaluation. For example, sit-to-stand-to-sit (STSTS) movement is considered to be an easily measurable motion in daily life, and correlations for STSTS movements with IADL scales have been reported [17]- [23]. For example, significant relationships have been reported between IADL (or more fundamental activities of daily living) dependence and strength in knee extension [17] and muscle mass [18], [19] related to STSTS movement. ...
... This test requires five quick repetitions of the STSTS movements, and the movements must be measured by a professional such as a physiotherapist. Sensing-based techniques to assess STSTS movements, such as techniques involving the use of force plates [22] or accelerometers [23], [24], have been studied, but these techniques are unsuitable for daily use because of their limited measurement and installation capabilities. ...
... Muscle mass is closely related to muscle strength and the ability to perform STSTS movements [18], [19]. With respect to acceleration, a few studies reported that accelerations in sit-to-stand motion are associated with the difficulty the elderly have in performing STSTS [23], [52] which could explain the relationship between STSTS acceleration and HL-IADL. Moreover, the minimum jerk has been reported to be an important factor for natural and smooth sit-to-stand motion [23], [53]. ...
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This paper presents an evaluation technique for higher-level instrumental activities of daily living (HL-IADLs), which are defined as relatively complicated modern daily activities to perform independently, using micro-Doppler radar (MDR) signatures of sit-to-stand-to-sit (STSTS) movements. Because HL-IADLs are useful for evaluating the degree of disability and cognitive decline in daily life, this study aims to develop a system that enables the identification of individuals with HL-IADL impairments in an unconstrained manner. The study participants were elderly adults of age 65–74 years of rural communities in Japan, and their motion parameters in natural STSTS were extracted via a single 24-GHz MDR installed on the ceiling. Their HLIADLs were evaluated using a questionnaire-based scale called the Japan Science and Technology Agency Index of Competence (JST-IC). The relationship between the HL-IADLs scaled with the JST-IC and the extracted STSTS parameters were statistically analyzed, and the results revealed that the extracted parameters were associated with the JST-IC score. Furthermore, an appropriately accurate screening method was verified for elderly adults with HL-IADL impairment using the extracted parameters.
... STS variants based on number of repetitions have shown muscular activity differences [12]. Among them, the most studied and used is 5 repetitions STS (5-STS), which has shown to be a reliable for measuring func- 50 tional strength in adult population [13] and a feasible tool for individuals with neurological disorders [14].Besides quantify motion through number of repetitions, lately, several studies have shown that it is important to provide information about the quality of, and, in this field, kinematic parameters play a main 55 role [15]. Inertial units and accelerometers have been validated in STS variants in order to measure movement duration [16,17]. ...
... Accelerometry has been validated to assess the duration of STS in the sternum and thighs [17]. Nowadays, 280 the great amount of possible placements makes the best device placement uncertain [15]. ...
... One of the limitations of the present study is that it did not include other kinematic variables such acceleration, which is extended in the research field of this test [15]. It also did not 285 analyze other motions like rotations or inclinations. ...
Article
Objective: The objective of the present study was to measure trunk flexo-extension during different Sit-To-Stand (STS) tasks and to analyse differences in those variables when STS repetitions are increased, by using an inertial sensor. Methods: In this cross-sectional study trunk flexo-extension was obtained through inertial measurements using an inertial sensor placed on the flat part of the sternum with the Y transversally oriented and attached using double-sided adhesive tape. Trunk flexo-extension was expressed along the Y axis (pitch angle) in a sagittal plane, representing antero-posterior motion (degrees, °). Descriptive anthropometric independent variables were also recorded. Subject had to sit and rise from a 43 cm high chair at a speed of 40 beats per minute in 5, 10 and 15 repetitions of STS variants. Results: Men showed higher mean mobility (between 41.51° and 43.23°) than women (between 32.16° and 33.31°) in all STS test, although significant was only found for 10-STS and 15-STS (<0.05). Male gender showed stronger Pearson correlation between each test than female gender. In men, correlations were highly significant in all tests (r between 0.891 and 0.939). However, in the case of women, significance varied between each test comparison (r between 0.474 and 0.745). There were no significant differences observed between trunk flexo-extension and STS variants (p=0.908; F=0.097). Conclusion: Men showed a wider range of trunk motion and a more consistent pattern than women through STS variants. However, no significant differences were found in mobility between each test. The results provided in this study should be taken into account when performing STS in this population and should be applied only to a healthy population.
... STS can be examined in terms of the trajectory of the CoM of the body, the involved joints (hip, knee, and ankle), body segments (head-arms-trunk, thigh, and shank), and several major lower limb muscles (Roebroeck et al., 1994). Modern inertial sensing technology has made it possible to extract an extensive amount of STS kinematic and kinetic data, making such sensors useful tools for STS performance assessment (Millor et al., 2014). ...
... Raw inertial readings require extra signal analysis to derive meaningful, clinically relevant features (see Millor et al., 2014 for a detailed review). Several such features have been defined and captured using various configurations of accelerometers, gyroscopes, and magnetometers mounted at different body locations. ...
... Several such features have been defined and captured using various configurations of accelerometers, gyroscopes, and magnetometers mounted at different body locations. An important one is the transition duration (time expended in performing STS), which can differentiate frail and healthy subjects (Millor et al., 2014). Several linear kinematic parameters have been found to differentiate pathological and non-pathological STS, such as vertical, mediolaterial and anteroposterior acceleration, anteroposterior jerk, and vertical linear velocity (Millor et al., 2014). ...
Article
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Interactive sonification of biomechanical quantities is gaining relevance as a motor learning aid in movement rehabilitation, as well as a monitoring tool. However, existing gaps in sonification research (issues related to meaning, aesthetics, and clinical effects) have prevented its widespread recognition and adoption in such applications. The incorporation of embodied principles and musical structures in sonification design has gradually become popular, particularly in applications related to human movement. In this study, we propose a general sonification model for the sit-to-stand (STS) transfer, an important activity of daily living. The model contains a fixed component independent of the use-case, which represents the rising motion of the body as an ascending melody using the physical model of a flute. In addition, a flexible component concurrently sonifies STS features of clinical interest in a particular rehabilitative/monitoring situation. Here, we chose to represent shank angular jerk and movement stoppages (freezes), through perceptually salient pitch modulations and bell sounds. We outline the details of our technical implementation of the model. We evaluated the model by means of a listening test experiment with 25 healthy participants, who were asked to identify six normal and simulated impaired STS patterns from sonified versions containing various combinations of the constituent mappings of the model. Overall, we found that the participants were able to classify the patterns accurately (86.67 ± 14.69% correct responses with the full model, 71.56% overall), confidently (64.95 ± 16.52% self-reported rating), and in a timely manner (response time: 4.28 ± 1.52 s). The amount of sonified kinematic information significantly impacted classification accuracy. The six STS patterns were also classified with significantly different accuracy depending on their kinematic characteristics. Learning effects were seen in the form of increased accuracy and confidence with repeated exposure to the sound sequences. We found no significant accuracy differences based on the participants' level of music training. Overall, we see our model as a concrete conceptual and technical starting point for STS sonification design catering to rehabilitative and clinical monitoring applications.
... Elle nécessite un déplacement globalement vertical du centre de gravité qui passe par une position instable [25]. Le lever de chaise requière donc un bonéquilibre et suffisamment de 13 Chapitre 1. Cadre générale de la thèse force et puissance musculaire [26]. Ces paramètres traduisent la capacité motrice des membres inférieurs. ...
... Actuellement, lesétudes montrent la nécessité de standardiser le test de lever de chaise non répétitif [29]. D'autre part, la quantification de la mesure via des paramètres pertinents pourrait permettre de différencier des populations [26]. ...
... Pour le test du lever de chaise, de nombreux paramètres issus de centrales inertielles semblentêtre significatifs pourévaluer les performances fonctionnelles [26]. Ces paramètres peuventêtre de différentes natures : temporel, accélération linéaire, vitesse angulaire, fréquentiel, etc. Ils sont souvent directement issus du capteur utilisé et ne décrivent donc que partiellement la cinématique du mouvement du patient. ...
Thesis
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Les capacités physiques sont directement liées au vieillissement en bonne santé. Ainsi, il est indispensable d'être capable de les estimer rapidement et simplement dans le cadre d'une routine clinique. Dans cette thèse, nous nous sommes concentrés sur la transition assis / debout qui est déjà utilisée en gériatrie et qui constitue un mouvement de la vie courante qui se complexifie pour les personnes dont les capacités physiques diminuent. La quantification de ce mouvement a été proposée à l'aide d'une centrale inertielle fixée sur le buste. Ce type de boitier est petit et bon marché, ce qui en fait un excellent candidat pour les mesures ambulatoires.Dans un premier temps, il a été nécessaire de valider les mesures de la cinématique et de l'énergétique du mouvement à l'aide de la centrale lors du lever de chaise. Cette validation s'est faite sur un panel de sujets jeunes et sains en comparaison avec un système de capture du mouvement par caméras de référence Vicon.Le second objectif était de comparer différentes populations à travers la quantification du lever de chaise. Outre un groupe de sujets jeunes sains, un groupe de sujets âgés sains a été intégré à l'étude pour étudier l'effet de l'âge. Un groupe de sujets âgés fragiles a également pris part à l'étude pour investiguer l'effet de la fragilité. Nous avons proposé la mise en place de deux scores composites basés sur les paramètres mesurés. Le premier est un score de vieillissement et le second, un score de fragilité. Chaque score a été construit à l'aide d'une analyse en composantes principales. La performance de chaque score est meilleure que celle de n'importe quel paramètre considéré indépendamment.
... This test is based on measuring how long it takes a subject to execute five SiSt transitions [21]. There already are instrumented versions of these tests using sensors to quantify their standard outcomes and even more advanced parameters [31]. However, even though walking and standing up from a chair are usual activities of daily living, the constraints imposed by these kinds of tests require the subjects to interrupt their daily activities to take a measurement. ...
... Additionally, the interventions were aimed at the older general population without a focus on the frailty domain. The most recent papers included in other systematic reviews focusing on gait speed [42], kinematic parameters of sit-to-stand and stand-to-sit movements [31], and physical activity [43] were published over seven years ago. ...
... A second version of the search strategy was drafted by the first author by including the identified keywords and index terms and further refined through team discussion. The final search strategies can be found in Appendix B. In the second step, MEDLINE (PubMed), SCOPUS, and Web of Science, as in [31], were searched for English-language documents published between 2010 and December 2020. The search results were exported into Zotero, and duplicates were removed by the first author. ...
Article
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Ubiquity (devices becoming part of the context) and transparency (devices not interfering with daily activities) are very significant in healthcare monitoring applications for elders. The present study undertakes a scoping review to map the literature on sensor-based unobtrusive monitoring of older adults' frailty. We aim to determine what types of devices comply with unobtrusiveness requirements, which frailty markers have been unobtrusively assessed, which unsupervised devices have been tested, the relationships between sensor outcomes and frailty markers, and which devices can assess multiple markers. SCOPUS, PUBMED, and Web of Science were used to identify papers published 2010-2020. We selected 67 documents involving non-hospitalized older adults (65+ y.o.) and assessing frailty level or some specific frailty-marker with some sensor. Among the nine types of body worn sensors, only inertial measurement units (IMUs) on the waist and wrist-worn sensors comply with ubiquity. The former can transparently assess all variables but weight loss. Wrist-worn devices have not been tested in unsupervised conditions. Unsupervised presence detectors can predict frailty, slowness, performance, and physical activity. Waist IMUs and presence detectors are the most promising candidates for unobtrusive and unsupervised monitoring of frailty. Further research is necessary to give specific predictions of frailty level with unsupervised waist IMUs.
... The studies have used inertial sensors to automatically detect [75], [106]- [112] and quantify S2ST movements [82], [113]. Several detection algorithms have been proposed in the literature. ...
... Therefore, stride variability can serve as a marker of stability during walking. Several projects used inertial sensors to automatically detect [75], [106]- [112] and quantify mobility and fall risk [82], [113]. They used one or more body fixed sensors (i.e. ...
Thesis
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Assessment of mobility in older adults is important for early detection and prevention of falls. The Timed Up and Go (TUG) and the 30 Second Chair Stand (30SCS) tests are recommended and routinely used for assessing overall mobility, but they provide a single parameter to quantify mobility. These tests are still subjective and prone to errors. Therefore, we need cost effective new diagnostic procedures that provide more detailed assessment parameters related to fall risks. Modern smartphones enable the development of new mobile health (mHealth) applications by integrating inertial and environmental sensors along with the increasing data processing and communication capabilities. We developed a suite of smartphone applications for assessing mobility to automate and quantify the TUG test, the 30SCS test and the 4-Stage-Balance test (4SBT). We developed a personalized three-segment control model that quantifies torques/forces during sit-to-stand (S2ST) posture transitions, and assesses optimality of each S2ST transition using inputs from smartphone’s inertial sensors. The model assesses energy expenditure using action, defined as an integral of mechanical energy over time during the transition. We demonstrated that the theoretical optimal transition time can be determined for each person by finding the minimum action using a personalized dynamic model. We proposed additional methods of assessment of stability using spectral and harmonic analysis of signals during walking in the TUG test. We tested the model by evaluating optimum action and optimum S2ST transition time for a group geriatric patients undergoing a mobility improvement program by comparing their performance with the optimum performance generated by the model.
... Features were selected for the walking if: [feature was reported significantly in at least two studies (p < 0.05)] AND [feature was computed for walking task] AND [accelerometer was used, and it was worn on the lower back/trunk] OR feature was independent of sensor placement and type (e.g., number of steps). Our selection of features was mainly based on the papers [19,28,[32][33][34][35][36]. These features were further categorized similarly to [19]: linear acceleration, spatial, temporal, frequency and other. ...
... For the SiSt and StSi transitions, these linear acceleration features are directly related to the forces needed to perform the postural transitions thus explain certain impairments. This finding is consistent with previous literatures [34,52,53] on the study of postural transition. Table 4 shows the performance of the classifications in a combination of SFBBS subtask numbers and evaluation metrics. ...
Article
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Background Poor balance has been cited as one of the key causal factors of falls. Timely detection of balance impairment can help identify the elderly prone to falls and also trigger early interventions to prevent them. The goal of this study was to develop a surrogate approach for assessing elderly’s functional balance based on Short Form Berg Balance Scale (SFBBS) score. Methods Data were collected from a waist-mounted tri-axial accelerometer while participants performed a timed up and go test. Clinically relevant variables were extracted from the segmented accelerometer signals for fitting SFBBS predictive models. Regularized regression together with random-shuffle-split cross-validation was used to facilitate the development of the predictive models for automatic balance estimation. Results Eighty-five community-dwelling older adults (72.12 ± 6.99 year) participated in our study. Our results demonstrated that combined clinical and sensor-based variables, together with regularized regression and cross-validation, achieved moderate-high predictive accuracy of SFBBS scores (mean MAE = 2.01 and mean RMSE = 2.55). Step length, gender, gait speed and linear acceleration variables describe the motor coordination were identified as significantly contributed variables of balance estimation. The predictive model also showed moderate-high discriminations in classifying the risk levels in the performance of three balance assessment motions in terms of AUC values of 0.72, 0.79 and 0.76 respectively. Conclusions The study presented a feasible option for quantitatively accurate, objectively measured, and unobtrusively collected functional balance assessment at the point-of-care or home environment. It also provided clinicians and elderly with stable and sensitive biomarkers for long-term monitoring of functional balance.
... The five-time sit-to-stand (5xSTS) test which measures the time to perform five sit-to-stand transitions [13,14] and thirty-second chair-rise (30SCT) test which includes the numbers of sit-to-stands that can be performed within thirty seconds [8,15] are standardized functional tests used in clinical routine to assess the ability to perform, and the quality of transitions. Although these methods have been proven to display discriminative properties for balance disorders [16], subtle differences that may provide further relevant information about the movement are not detectable with these tests [17]. ...
... Sit-to-stand transitions have been studied with optical motion trackers [24] and force plates [25]. Although these methods provide very detailed and granular information about the movements, they are limited to the laboratory environment [7,17]. ...
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Background: Sit-to-stand and stand-to-sit transitions are frequent daily functional tasks indicative of muscle power and balance performance. Monitoring these postural transitions with inertial sensors provides an objective tool to assess mobility in both the laboratory and home environment. While the measurement depends on the sensor location, the clinical and everyday use requires high compliance and subject adherence. The objective of this study was to propose a sit-to-stand and stand-to-sit transition detection algorithm that works independently of the sensor location. Methods: For a location-independent algorithm, the vertical acceleration of the lower back in the global frame was used to detect the postural transitions in daily activities. The detection performance of the algorithm was validated against video observations. To investigate the effect of the location on the kinematic parameters, these parameters were extracted during a five-time sit-to-stand test and were compared for different locations of the sensor on the trunk and lower back. Results: The proposed detection method demonstrates high accuracy in different populations with a mean positive predictive value (and mean sensitivity) of 98% (95%) for healthy individuals and 89% (89%) for participants with diseases. Conclusions: The sensor location around the waist did not affect the performance of the algorithm in detecting the sit-to-stand and stand-to-sit transitions. However, regarding the accuracy of the kinematic parameters, the sensors located on the sternum and L5 vertebrae demonstrated the highest reliability.
... It requires the automatic identification and delimitation of sit-stand-sit (STS) cycles and the ability to automatically spot and dismiss failed attempts (i.e., when the subject does not reach an upright posture). Inertial sensors and inertial measurement units (IMUs) were extensively used to study sit-to-stand and stand-to-sit transitions, as well as STS cycles, over the past three decades [17]. Some of these studies looked for relationships between different kinematic parameters and the functional status (robust, pre-frail, frail) of the experimental subjects [18][19][20]. ...
... The wearable devices described above require the IMUs to be placed on the L3 region of the subject's lumbar spine [17,22]. Older people might experience some difficulties in placing them on the correct spot, especially if they do not have any help to put them on. ...
Article
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Lower-limb strength is a marker of functional decline in elders. This work studies the feasibility of using the quasi-periodic nature of the distance between a subjects' back and the chair backrest during a 30-s chair-stand test (CST) to carry out unsupervised measurements based on readings from a low-cost ultrasound sensor. The device comprises an ultrasound sensor, an Arduino UNO board, and a Bluetooth module. Sit-to-stand transitions are identified by filtering the signal with a moving minimum filter and comparing the output to an adaptive threshold. An inter-rater reliability (IRR) study was carried out to validate the device ability to count the same number of valid transitions as the gold-standard manual count. A group of elders (age: mean (m) = 80.79 years old, SD = 5.38; gender: 21 female and seven male) were asked to perform a 30-s CST using the device while a trained nurse manually counted valid transitions. Ultimately, a moving minimum filter was necessary to cancel the effect of outliers, likely produced because older people tend to produce more motion artefacts and, thus, noisier signals. While the intra-class correlation coefficient (ICC) for this study was good (ICC = 0.86, 95% confidence interval (CI) = 0.73, 0.93), it is not yet clear whether the results are sufficient to support clinical decision-making.
... In literature, AHRS are also sometimes referred to as magnetic and inertial measurement unit (MIMU), magnetic angular rate and gravity sensor (MARG) or inertial and magnetic measurement unit (IMMU). Over the past decade, researchers and clinicians have used AHRS to measure segments and joints kinematics in a wide variety of contexts including assessment of age-related kinematic changes, identification of neurodegenerative disease impairments and progression, assessment of rehabilitation evolution, ergonomics evaluations and assessment of sports biomechanics [1][2][3][4][5][6][7][8][9]. The accuracy of orientation data provided by AHRS has been studied in controlled conditions. ...
... However, the extent of these effects on human motion remains unclear. To this day, most validation studies concentrate on a single task (mainly levelled gait assessment or handling tasks) performed by a limited number of participants [1][2][3][4][5][6][7][8][9][10][11][12][13][14] and measured on a limited number of segments [13,[17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34]. The methodology used in those studies also varies (difference in systems used, anatomical calibration and refer-encing…), making it difficult to understand the global scope of AHRS accuracy results in the current literature. ...
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Background Joints kinematics assessment based on inertial measurement systems, which include attitude and heading reference system (AHRS), are quickly gaining in popularity for research and clinical applications. The variety of the tasks and contexts they are used in require a deep understanding of the AHRS accuracy for optimal data interpretation. However, published accuracy studies on AHRS are mostly limited to a single task measured on a limited number of segments and participants. This study assessed AHRS sensors kinematics accuracy at multiple segments and joints through a variety of tasks not only to characterize the system’s accuracy in these specific conditions, but also to extrapolate the accuracy results to a broader range of conditions using the characteristics of the movements (i.e. velocity and type of motion). Twenty asymptomatic adults (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\overline{age}$$\end{document}age¯ = 49.9) performed multiple 5 m timed up and go. Participants’ head, upper trunk, pelvis, thigh, shank and foot were simultaneously tracked using AHRS and an optical motion capture system (gold standard). Each trial was segmented into basic tasks (sit-to-stand, walk, turn). Results At segment level, results revealed a mean root-mean-squared-difference \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\overline{(RMSD)}$$\end{document}(RMSD)¯ varying between 1.1° and 5.5° according to the segment tracked and the task performed, with a good to excellent agreement between the systems. Relative sensor kinematics accuracy (i.e. joint) varied between 1.6° and 13.6° over the same tasks. On a global scheme, analysis of the effect of velocity on sensor kinematics accuracy showed that AHRS are better adapted to motions performed between 50°/s and 75°/s (roughly thigh and shank while walking). Conclusion Results confirmed that pairing of modules to obtain joint kinematics affects the accuracy compared to segment kinematics. Overall, AHRS are a suitable solution for clinical evaluation of biomechanics under the multi-segment tasks performed although the variation in accuracy should be taken into consideration when judging the clinical meaningfulness of the observed changes.
... Extensive sensor-based research on TUG has been performed in a range of clinical conditions (31,32). A brief survey of this literature reveals at least 90 sensor metrics for TUG have been derived to recognize falling risk. ...
... A brief survey of this literature reveals at least 90 sensor metrics for TUG have been derived to recognize falling risk. In a 2014 systematic review of 53 sensor-based studies on the sit-to-stand transition (32), 84% of the studies used a sensor on the torso, at either the spine [e.g., L3 (33,34)] or the sternum [e.g., (18)]. Other studies have placed sensors on the shanks (16,27,35); only in a few cases placement was on the thigh segment (20,36,37), despite the fact that the thigh would be the most directly involved body segment during the SI-ST or ST-SI transition. ...
Article
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Introduction: Inertial sensors generate objective and sensitive metrics of movement disability that may indicate fall risk in many clinical conditions including multiple sclerosis (MS). The Timed-Up-And-Go (TUG) task is used to assess patient mobility because it incorporates clinically-relevant submovements during standing. Most sensor-based TUG research has focused on the placement of sensors at the spine, hip or ankles; an examination of thigh activity in TUG in multiple sclerosis is wanting. Methods: We used validated sensors (x-IMU by x-io) to derive transparent metrics for the sit-to-stand (SI-ST) transition and the stand-to-sit (ST-SI) transition of TUG, and compared effect sizes for metrics from inertial sensors on the thighs to effect sizes for metrics from a sensor placed at the L3 level of the lumbar spine. Twenty-three healthy volunteers were compared to 17 ambulatory persons with MS (PwMS, HAI ≤ 2). Results: During the SI-ST transition, the metric with the largest effect size comparing healthy volunteers to PwMS was the Area Under the Curve of the thigh angular velocity in the pitch direction–representing both thigh and knee extension; the peak of the spine pitch angular velocity during SI-ST also had a large effect size, as did some temporal measures of duration of SI-ST, although less so. During the ST-SI transition the metric with the largest effect size in PwMS was the peak of the spine angular velocity curve in the roll direction. A regression was performed. Discussion: We propose for PwMS that the diminished peak angular velocity during SI-ST directly represents extensor weakness, while the increased roll during ST-SI represents diminished postural control. Conclusions: During the SI-ST transition of TUG, angular velocities can discriminate between healthy volunteers and ambulatory PwMS better than temporal features. Sensor placement on the thighs provides additional discrimination compared to sensor placement at the lumbar spine.
... Recently, wearable sensors have been widely used not only to detect, but also to objectively quantify motor signs in PD patients [16,17]. Most common approaches rely on inertial sensors (accelerometers and gyroscopes) [18][19][20][21][22][23][24][25][26], digitography [27,28], surface electromyographic [29], force detection surfaces [28], and more sophisticated, complex and costly setups such as video motion analysis systems [30]. ...
Article
Background Currently the most consistent, widely accepted and detailed instrument to rate Parkinson’s disease (PD) is the Movement Disorder Society sponsored Unified Parkinson Disease Rating Scale (MDS-UPDRS). However, the motor examination is based upon subjective human interpretation trying to capture a snapshot of PD status. Wearable sensors and machine learning have been broadly used to analyze PD motor disorder, but still most ratings and examinations lay outside MDS-UPDRS standards. Moreover, logical connections between features and output ratings are not clear and complex to derive from the model, thus limiting the understanding of the structure in the data. Methods Fifty-seven PD patients underwent a full motor examination in accordance to the MDS-UPDRS on twelve different sessions, gathering 123 measurements. Overall, 446 different combinations of limb features correlated to rest tremors amplitude are extracted from gyroscopes, accelerometers, and magnetometers and feed into a fuzzy inference system to yield severity estimations. Results A method to perform rest tremor quantification fully adhered to the MDS-UPDRS based on wearable sensors and fuzzy inference system is proposed, which enables a reliable and repeatable assessment while still computing features suggested by clinicians in the scale. This quantification is straightforward and scalable allowing clinicians to improve inference by means of new linguistic statements. In addition, the method is immediately accessible to clinical environments and provides rest tremor amplitude data with respect to the timeline. A better resolution is also achieved in tremors rating by adding a continuous range.
... In addition, data from two or more sensors can be integrated to form more composite patterns to distinguish frailty levels. The Si-St and St-Si are frequently used in clinical tests to assess the functionality of lower extremities for risk of fall assessment [73,74]. The variations of these tests such as 30 s, Si-St and five times Si-St tests are also commonly deployed at clinics by geriatricians. ...
Article
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Background: Frailty assessment is a critical approach in assessing the health status of older people. The clinical tools deployed by geriatricians to assess frailty can be grouped into two categories; using a questionnaire-based method or analyzing the physical performance of the subject. In performance analysis, the time taken by a subject to complete a physical task such as walking over a specific distance, typically three meters, is measured. The questionnaire-based method is subjective, and the time-based performance analysis does not necessarily identify the kinematic characteristics of motion and their root causes. However, kinematic characteristics are crucial in measuring the degree of frailty. Results: The studies reviewed in this paper indicate that the quantitative analysis of activity of daily living, balance and gait are significant methods for assessing frailty in older people. Kinematic parameters (such as gait speed) and sensor-derived parameters are also strong markers of frailty. Seventeen gait parameters are found to be sensitive for discriminating various frailty levels. Gait velocity is the most significant parameter. Short term monitoring of daily activities is a more significant method for frailty assessment than is long term monitoring and can be implemented easily using clinical tests such as sit to stand or stand to sit. The risk of fall can be considered an outcome of frailty. Conclusion: Frailty is a multi-dimensional phenomenon that is defined by various domains; physical, social, psychological and environmental. The physical domain has proven to be essential in the objective determination of the degree of frailty in older people. The deployment of inertial sensor in clinical tests is an effective method for the objective assessment of frailty.
... 21 The Timed Up and Go (TUG), one of the most common tests to evaluate dynamic balance, has been integrated with motion sensors in a range of clinical conditions. 22 A recent validation of a model of instrumented TUG in pwMS revealed that the movement of the thigh during the sit-to-stand transition was the most informative of all the measured body segments. 23 This evidence opens interesting views on the possible implementation of a reliable, accurate, and user-friendly TUG based on a smartphone simply positioned in the patient's pocket. ...
Article
Wearable sensors are designed to be worn on the body or embedded into portable devices (e.g. smartphones and smartwatches), allowing continuous patient-based monitoring, objective outcomes measuring, and feedback delivering on daily-life activities. Within the medicine domain, there has been a rapid increase in the development, testing, and use of wearable technologies especially in the context of neurological diseases. Although wearables represent promising tools also in multiple sclerosis (MS), the research on their application in MS is still ongoing, and further studies are required to assess their reliability and accuracy to monitor body functions and disability in people with MS (pwMS). Here, we provided a comprehensive overview of the opportunities, potential challenges, and limitations of the wearable technology use in MS. In particular, we classified previous findings within this field into macro-categories, considered crucial for disease management: assessment, monitoring, intervention, advice, and education. Given the increasing pivotal role played by wearables, current literature suggests that for pwMS, the time is right to shift from a center-based traditional therapeutic paradigm toward a personalized patient-based disease self-management. On this way, we present two ongoing initiatives aimed at implementing a continuous monitoring of pwMS and, consequently, providing timely and appropriate care interventions.
... The number of repetitions completed provides quantitative information with which to evaluate functional fitness levels [8], and has been used in the rehabilitation field [9]. Recently, several studies have highlighted the importance of kinematic parameters to provide qualitative information about how the motion is carried out [10]. In the sensors embedded in a smartphone, as well as surface electromyography, in a subject undertaking the 30-STS test. ...
Article
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The latest studies of the 30-second sit-to-stand (30-STS) test aim to describe it by employing kinematic variables, muscular activity, or fatigue through electromyography (EMG) instead of a number of repetitions. The aim of the present study was to develop a detection system based on acceleration measured using a smartphone to analyze fatigue during the 30-STS test with surface electromyography as the criterion. This case study was carried out on one woman, who performed eight trials. EMG data from the lower limbs and trunk muscles, as well as trunk acceleration were recorded. Both signals from eight trials were preprocessed, being averaged and temporarily aligned. The EMG signal was processed, calculating the spectral centroid (SC) by Discrete Fourier Transform, while the acceleration signal was processed by Discrete Wavelet Transform to calculate its energy percentage. Regarding EMG, fatigue in the vastus medialis of the quadriceps appeared as a decrease in SC, with a descending slope of 12% at second 12, indicating fatigue. However, acceleration analysis showed an increase in the percentage of relative energy, acting like fatigue firing at second 19. This assessed fatigue according to two variables of a different nature. The results will help clinicians to obtain information about fatigue using an accessible and inexpensive device, i.e., as a smartphone.
... The number of repetitions completed provides quantitative information with which to evaluate functional fitness levels [8], and has been used in the rehabilitation field [9]. Recently, several studies have highlighted the importance of kinematic parameters to provide qualitative information about how the motion is carried out [10]. In the sensors embedded in a smartphone, as well as surface electromyography, in a subject undertaking the 30-STS test. ...
... However, the evaluation is a subjective manner and depends a lot on the visual observations. The evaluations are more qualitative than quantitative and the subtle differences are not detected [7]. The attending physician observes and explores the patient and then issues a diagnosis, based on his own perception, which can even vary with the opinion of another physician. ...
Conference Paper
The biomechanical signals acquisition through wireless sensor networks and the information processing for healthcare in patients with Parkinson's disease (PD) have an important challenge. As well as other biomechanical signs, patients with PD usually present slow movements, difficult to initiate, vary or interrupt which reflect in gait alterations. The patient should walk at least 10 meters, then turn around and return to the starting point. These movement requirements can affect the wireless communication quality. Currently there are many scales for the assessment of patients with PD, but in recent research, the scale "Movement Disorder Society - Unified Parkinson's Disease-Rating Rating Scale" (MDS-UPDRS) has gained great notoriety. However, evaluation is in a subjective way and depends a lot on the patient's momentary status and the results shown are qualitative only, and the subtle differences not detected. This paper presents results with wireless sensors networks Bluetooth and XBee, respectively, as well as the first stage of a diffuse model to analyse, evaluate and classify the gait according to the parameters established by the MDS-UPDRS, with multi-axial signals from inertial measurement units. The model presented good results for evaluation and classification, always backed-up by the help of medical experts.
... During functional tasks (such as balance, gait and rising from a chair) and dual task walk, an inertial sensor unit (XSENS, Xsens Technologies B.V. Enschede, Netherlands) will be attached over the lumbarspine (L3) to record raw acceleration data. Afterwards, the raw signal we be processed to compute kinematic parameters related to physical frailty [98][99][100] by using the software designed by Movalys (Movalsys SL, Pamplona, Spain). ...
Article
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Background Falls represent important drivers of intrinsic capacity losses, functional limitations and reduced quality of life in the growing older adult’s population, especially among those presenting with frailty. Despite exercise- and cognitive training-based interventions have shown effectiveness for reducing fall rates, evidence around their putative cumulative effects on falls and fall-related complications (such as fractures, reduced quality of life and functional limitations) in frail individuals remains scarce. The main aim of this study is to explore the effectiveness program combining an individualized exercise program and an executive function-based cognitive training (VIVIFRAIL-COGN) compared to usual care in the prevention of falls and fall-related outcomes over a 1-year follow-up. Methods This study is designed as a four-center randomized clinical trial with a 12-week intervention period and an additional 1-year follow-up. Three hundred twenty frail or pre-frail (≥ 1 criteria of the Frailty Phenotype) older adults (≥ 75 years) with high risk of falling (defined by fall history and gait performance) will be recruited in the Falls Units of the participating centers. They will be randomized in a 1:1 ratio to the intervention group (IG) or the control group (CG). The IG will participate in a home-based intervention combining the individualized Vivifrail multicomponent (aerobic, resistance, gait and balance and flexibility) exercise program and a personalized executive function-based cognitive training (VIVIFRAIL-COGN). The CG group will receive usual care delivered in the Falls Units, including the Otago Exercise Program. Primary outcome will be the incidence of falls (event rate/year) and will be ascertained by self-report during three visits (at baseline, and 6 and 12 weeks) and telephone-based contacts at 6, 9 and 12 months after randomization. Secondarily, effects on measures of physical and cognitive function, quality of life, nutritional, muscle quality and psychological status will be evaluated. Discussion This trial will provide new evidence about the effectiveness of an individualized multidomain intervention by studying the effect of additive effects of cognitive training and physical exercise to prevent falls in older frail persons with high risk of falling. Compared to usual care, the combined intervention is expected to show additive effects in the reduction of the incidence of falls and associated adverse outcomes. Trial registration NCT04911179 02/06/2021.
... However, the main limitation was that correlation coefficients do not necessarily represent cause and effect relationships between outcomes, and the associations observed here should be carefully interpreted. However, previous studies have shown that muscle quality, maximal strength and maximal power output are associated with functional tests performance in older populations (Cadore et al., 2012;Casas-Herrero et al., 2013;Izquierdo et al., 1999;Millor et al., 2014;Rech et al., 2014;Reid and Fielding, 2012;Wilhelm et al., 2014), and associations among neuromuscular outcomes and kinematical variables during functional tests reinforce these relationships. The main strength of the present study is that, to the best of our knowledge, this is one of the first studies to examine for associations between kinematic parameters during balance, gait, sit-to-stand and balance tests with muscle quality, maximal strength and maximal power output in frail individuals. ...
Article
Frailty is an important concept in clinical and demographic research in the elderly because of its incidence level and its relationship with adverse outcomes. Functional ability declines with advanced age, likely due to changes in muscle function. This study aimed to examine the relationship between muscle quality and muscle power with kinematics from functional tests in a population of 21 institutionalized frail nonagenarian (91.3 ± 3.1 years). Here, muscle quality was measured by segmenting areas of high- and low-density fibers with computerized tomography. In addition, muscle strength and muscle power were obtained through maximal strength and power tests using resistance exercises. Finally, functional capacity outcomes (i.e., gait velocity, sit-to-stand ability and balance), as well as kinematic parameters, were evaluated from a tri-axial sensor used during a battery of functional tests. Our results show that lower limb muscle quality, maximal strength and power output present statistically significant relationships with different kinematic parameters, especially during the sit-to-stand and gait tests (e.g. leg power and maximum power during sit-to-stand (r=0.80) as well as quadriceps muscle mass and step asymmetry (r=- 0,71). In particular, frail individuals with greater muscle quality needed less trunk range of motion to make the transition between sitting and standing, took less time to stand up, and exerted a major peak power of force. As a conclusion, a loss of muscle quality and power may lead to motor control impairments such as gait, sit-to-stand and balance that can be the cause of adverse events such as falls.
... Consequently, assessing lower body strength, and thus functional performance through the STS test has been considered a reliable way to differentiate between subjects with different functional levels [27]. While in clinical practice typically only the kinematics of the STS is analyzed [25][26][27][28], dynamics parameters such as the internal joint loads [29], muscle forces [30], external wrench (EW) distribution, or the trajectory of the center of mass or center of pressure [27] have been the target of recent research. The proposed method relies on two main steps to identify, without force plate measurements, the external wrench distribution as described in Fig. 5. ...
... El análisis cinemático por medio de sistemas de análisis de movimiento de laboratorio ha demostrado su capacidad de diferenciar entre PM frágiles y personas jóvenes, particularmente las transiciones sedente-bípedo, bípedo-sedente y duración total de TUG 13 . El registro de acelerometría de laboratorio ha sido ampliamente utilizado para caracterizar y diferenciar las características de las PM autovalentes, frágiles o con enfermedades neurológicas 14 , siendo las transiciones sedente-bípedo, bípedo-sedente y giro las más utilizadas. Galán-Mercant y Cuesta-Vargas utilizaron la UMI de un smartphone Iphone 4 © para registrar parámetros cinemáticos lineales y angulares de las transiciones sedente-bípedo y bípedosedente en forma aislada, demostrando diferencias entre PM frágiles y no frágiles 15 en una muestra con características demográficas similares a las del presente estudio, sin embargo, sus conclusiones se basan en el análisis de la diferencia de promedios de los valores máximos de las aceleraciones lineal y angular, sin reportar el tiempo transcurrido en las transiciones. ...
Article
Introduction: Inertial Measurement Units (IMU) incorporated in smartphones can provide records that match registers obtained by laboratory instruments. This means that the use of smartphones would be feasible for recording three-dimensional kinematics parameters like velocity and acceleration, enabling more robust analyses, such as the Timed Up and Go (TUG) test, that assess the risk of falls older people (OP) living in the community. Method: The study included 35 female OP, users of the Family Health Centres (CESFAM) Juan Pablo II and Corvallis from Antofagasta city, Chile. They were evaluated with the TUG, with linear and angular acceleration and velocity being recorded simultaneously using a smartphone equipped with a three-dimensional IMU. Using a computer macro application, the start and end time of each sub-stage of the test was determined by two independent observers. Reproducibility of the times of each sub-stage of TUG was assessed using the Intraclass Correlation Coefficient (ICC). Results: The ICC gave values of 0.78 to 0.99, with an acceptable confidence interval, (0.45-1.00), thus providing a reproducible and reliable recording. Conclusions: The reproducibility of the times of the sub-stages of TUG, recorded with inertial measurement units from a smartphone enables it to be used in clinical practices with OP groups, in order to improve the evaluation and prevention of the risk of falls.
... Consequently, assessing lower body strength, and thus functional performance through the STS test has been considered a reliable way to differentiate between subjects with different functional levels [27]. While in clinical practice typically only the kinematics of the STS is analyzed [25][26][27][28], dynamics parameters such as the internal joint loads [29], muscle forces [30], external wrench (EW) distribution, or the trajectory of the center of mass or center of pressure [27] have been the target of recent research. The proposed method relies on two main steps to identify, without force plate measurements, the external wrench distribution as described in Fig. 5. ...
Chapter
In human motion science, the dynamics plays an important role. It relates the movement of the human to the forces necessary to achieve this movement. It also relates the human and its environment through interaction forces. Estimating subject-specific dynamic models is a challenging problem, due to the need for both accurate measurement and modeling formalisms. In the past decade, we have developed solutions for the computation of the dynamic quantities of humans, based on individual (subject specific) models, inspired largely by Robotics geometric and dynamic calibration. In this chapter, we will present the state of the art and our latest advances in this area and show examples of applications to both humans and humanoid robots. With these research results we hope to contribute beyond the field of robotics to the fields of biomechanics and ergonomics, by providing accurate dynamic models of beings.
... Although STS performance has traditionally been correlated with lower-limb muscle strength and power 15,16 , it does not represent per se an estimate of muscle strength or power, since the latter need to be expressed as N and W, respectively. Thus, time-based or repetition-based STS performance should remain as an independent and relevant measure of functional capacity, while more sophisticated procedures and advanced instruments are required to obtain yet other STS-related measures 17,18 . To enable a transition into direct power assessment, previous studies have evaluated STS muscle power by using force platforms [19][20][21] , linear position transducers [22][23][24] or 3D accelerometers 25,26 . ...
Article
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This study aimed to assess the validity and functional relevance of a standardized procedure to assess lower limb muscle power by means of the 30-s sit-to-stand (STS) test when compared to leg extension power (LEP), traditional STS performance and handgrip strength. A total of 628 community-dwelling older subjects (60–93 years) from the Copenhagen Sarcopenia Study were included. Physical performance was assessed by the 30-s STS and 10-m maximal gait speed tests. Handgrip strength and LEP were recorded by a hand-held dynamometer and the Nottingham power rig, respectively. STS muscle power was calculated using the subjects’ body mass and height, chair height and the number of repetitions completed in the 30-s STS test. We found a small albeit significant difference between LEP and unilateral STS power in older men (245.5 ± 88.8 vs. 223.4 ± 81.4 W; ES = 0.26; p < 0.05), but not in older women (135.9 ± 51.9 vs. 138.5 ± 49.6 W; ES = 0.05; p > 0.05). Notably, a large positive correlation was observed between both measures (r = 0.75; p < 0.001). Relative STS power was more strongly related with maximal gait speed than handgrip strength, repetition-based STS performance and relative LEP after adjusting for age (r = 0.53 vs 0.35–0.45; p < 0.05). In conclusion, STS power obtained from the 30-s STS test appeared to provide a valid measure of bilateral lower limb power and was more strongly related with physical performance than maximal handgrip strength, repetition-based STS performance and LEP.
... Several studies have been published in which the standard STS has been augmented with the use of technology such as cameras or body-worn sensors [15]. There has been one previous review of instrumented STS, however this was performed in 2014, with many newer studies having been published [16]. In addition, this review focused only on motion sensor devices, with no studies of video technology included in the review, while the effectiveness of the iSTS were not evaluated with respect to any diagnostic accuracy. ...
Article
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The Sit-to-Stand (STS) is a widely used test of physical function to screen older people at risk of falls and frailty and is also one of the most important components of standard screening for sarcopenia. There have been many recent studies in which instrumented versions of the STS (iSTS) have been developed to provide additional parameters that could improve the accuracy of the STS test. This systematic review aimed to identify whether an iSTS is a viable alternative to a standard STS to identify older people at risk of falling, frailty, and sarcopenia. A total of 856 articles were found using the search strategy developed, with 12 articles retained in the review after screening based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Six studies evaluated the iSTS in fallers, five studies in frailty and only one study in both fallers and frailty. The results showed that power and velocity parameters extracted from an iSTS have the potential to improve the accuracy of screening when compared to a standard STS. Future work should focus on standardizing the segmentation of the STS into phases to enable comparison between studies and to develop devices integrated into the chair used for the test to improve usability.
... With respect to the elderly, some researchers have revealed that acceleration parameters are critical factors for the smoothness of STS movements, compared with velocity parameters. 34,35 Based on these reports, we can consider that our results indicated apathyrelated deterioration of the physical functions of STS movements through their acceleration parameters. Thus, although the degree of change in STS movements related to apathy was not high and was not clearly reflected by the velocity parameters, the acceleration parameters that were more sensitive to even slight deteriorations in physical functions indicated the differences between the apathetic and nonapathetic groups in our results. ...
Article
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This paper presents a Doppler radar apathy-screening technique applied to elderly people based on their basic daily activities of walking and movements of sit-to-stand and stand-to-sit (STS). Our Doppler radar system remotely measured the kinematic parameters of the movements of 78 community-dwelling elderly adults (27 apathetic participants and 51 non-apathetic ones). Subsequently, logistic regression models using the measured kinematic parameters of gait and sit-to-stand/stand-to-sit movements were constructed for screening. The experimental results verified that, although the model using gait parameters could screen an apathetic group with a sensitivity of 85.2% and a specificity of 58.8%, the model using the STS parameters achieved better screening accuracies with a sensitivity of 88.9% and a specificity of 76.5%. These results reveal that the kinematic information of STS movements is significantly more effective at detecting apathy than is the gait information, which is otherwise regarded to be effective in conventional epidemiological studies.
... In its most general form, a sensor is some kind of device (analog or digital) that responds to some input from the physical environment. Examples are light [1,2], motion [3,4], pressure [5,6], moisture [7,8] sensors just to cite a few. The output is typically some human-readable information that can be visualised directly on the sensor or can be transmitted over a network for further analysis or processing. ...
Article
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The determination of multiple parameters via luminescence sensing is of great interest for many applications in different fields, like biosensing and biological imaging, medicine, and diagnostics. The typical approach consists in measuring multiple quantities and in applying complex and frequently just approximated mathematical models to characterize the sensor response. The use of machine learning to extract information from measurements in sensors have been tried in several forms before. But one of the problems with the approaches so far, is the difficulty in getting a training dataset that is representative of the measurements done by the sensor. Additionally, extracting multiple parameters from a single measurement has been so far an impossible problem to solve efficiently in luminescence. In this work a new approach is described for building an autonomous intelligent sensor, which is able to produce the training dataset self-sufficiently, use it for training a neural network, and then use the trained model to do inference on measurements done on the same hardware. For the first time the use of machine learning additionally allows to extract two parameters from one single measurement using multitask learning neural network architectures. This is demonstrated here by a dual oxygen concentration and temperature sensor.
... Transitions from or to sitting positions are some of the most common motor tests performed in geriatric screening (e.g., as part of the timed up and go [39] or as sit-to-stand test [40]) and are considered to reflect different aspects of physical functions such as leg strength, postural control, and general physical fitness. The most commonly used read-out is the time needed for the sit-to-stand transition (stand up time) [41], for which only few normative data are available for younger age groups. Performance times in a small UK sample (n = 15, mean age 26 years ± 6 years SD) [42] were 1.43s and thus very similar to our observations, while somewhat slower performance (2.42s) was reported from a small Italian cohort (n=13, mean age 35 years ± 5 years SD) [43] which may be explained by differences in age, instruction bias, cultural bias, or even chance, given the small sample sizes. ...
Article
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Background Quantification of motor performance has a promising role in personalized medicine by diagnosing and monitoring, e.g. neurodegenerative diseases or health problems related to aging. New motion assessment technologies can evolve into patient-centered eHealth applications on a global scale to support personalized healthcare as well as treatment of disease. However, uncertainty remains on the limits of generalizability of such data, which is relevant specifically for preventive or predictive applications, using normative datasets to screen for incipient disease manifestations or indicators of individual risks. Objective This study explored differences between healthy German and Japanese adults in the performance of a short set of six motor tests. Methods Six motor tasks related to gait and balance were recorded with a validated 3D camera system. Twenty-five healthy adults from Chiba, Japan, participated in this study and were matched for age, sex, and BMI to a sample of 25 healthy adults from Berlin, Germany. Recordings used the same technical setup and standard instructions and were supervised by the same experienced operator. Differences in motor performance were analyzed using multiple linear regressions models, adjusted for differences in body stature. Results From 23 presented parameters, five showed group-related differences after adjustment for height and weight ( R ² between .19 and .46, p<.05). Japanese adults transitioned faster between sitting and standing and used a smaller range of hand motion. In stepping-in-place, cadence was similar in both groups, but Japanese adults showed higher knee movement amplitudes. Body height was identified as relevant confounder (standardized beta >.5) for performance of short comfortable and maximum speed walks. For results of posturography, regression models did not reveal effects of group or body stature. Conclusions Our results support the existence of a population-specific bias in motor function patterns in young healthy adults. This needs to be considered when motor function is assessed and used for clinical decisions, especially for personalized predictive and preventive medical purposes. The bias affected only the performance of specific items and parameters and is not fully explained by population-specific ethnic differences in body stature. It may be partially explained as cultural bias related to motor habits. Observed effects were small but are expected to be larger in a non-controlled cross-cultural application of motion assessment technologies with relevance for related algorithms that are being developed and used for data processing. In sum, the interpretation of individual data should be related to appropriate population-specific or even better personalized normative values to yield its full potential and avoid misinterpretation.
... The stride velocity, cadence and stride length data were obtained during walking in a straight line, turning peak velocity data were taken during turning 180 , sit-tostand peak velocity data were acquired during standing up from a chair, duration of turn-to-sit data were obtained during turning to sit and finally stand-to-sit peak velocity data were taken while returning to sit on the chair (starting point). These parameters have been validated and found to be discriminative variables, with high sensitivity and specificity, between people with and without mobility impairments [17,18,19,20,24]. ...
Article
Full-text available
... camera-based systems) have restrictions which limits their suitability for clinical settings (cost, volume, occlusions) [3]. Recent advances in wearables have brought new alternatives for mobility assessment, among which inertial measurement units (IMUs) stand out because of their portability, their size and their relatively low cost [4][5][6][7][8][9][10]. IMUs are composed of 3-axis accelerometers and gyroscopes, enabling static 2D orientation and dynamic change in orientation to be estimated. ...
Article
Joint kinematics can be assessed using orientation estimates from Attitude and Heading Reference Systems (AHRS). However, magnetically-perturbed environments affect the accuracy of the estimated orientations. This study investigates, both in controlled and human mobility conditions, a trial calibration technic based on a 2D photograph with a pose estimation algorithm to correct initial difference in AHRS Inertial reference frames and improve joint angle accuracy. In controlled conditions, two AHRS were solidly affixed onto a wooden stick and a series of static and dynamic trials were performed in varying environments. Mean accuracy of relative orientation between the two AHRS was improved from 24.4° to 2.9° using the proposed correction method. In human conditions, AHRS were placed on the shank and the foot of a participant who performed repeated trials of straight walking and walking while turning, varying the level of magnetic perturbation in the starting environment and the walking speed. Mean joint orientation accuracy went from 6.7° to 2.8° using the correction algorithm. The impact of starting environment was also greatly reduced, up to a point where one could consider it as non-significant from a clinical point of view (maximum mean difference went from 8° to 0.6°). The results obtained demonstrate that the proposed method improves significantly the mean accuracy of AHRS joint orientation estimations in magnetically-perturbed environments and can be implemented in post processing of AHRS data collected during biomechanical evaluation of motion.
... Indeed, an instrumented 5xSTS test allows an in-depth analysis of the PTs by detailed quantification of their detailed biomechanical features [16]. This in-depth analysis is based on the extraction of parameters that lie mostly into temporal, kinematic, kinetic, and smoothness categories [17]. ...
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Background: Falls are a major cause of injuries in older adults. To evaluate the risk of falls in older adults, clinical assessments such as the 5-time sit-to-stand (5xSTS) test can be performed. The development of inertial measurement units (IMUs) has provided the possibility of a more in-depth analysis of the movements' biomechanical characteristics during this test. The goal of the present study was to investigate whether an instrumented 5xSTS test provides additional information to predict multiple or serious falls compared to the conventional stopwatch-based method. Methods: Data from 458 community-dwelling older adults were analyzed. The participants were equipped with an IMU on the trunk to extract temporal, kinematic, kinetic, and smoothness movement parameters in addition to the total duration of the test by the stopwatch. Results: The total duration of the test obtained by the IMU and the stopwatch was in excellent agreement (Pearson's correlation coefficient: 0.99), while the total duration obtained by the IMU was systematically 0.52 s longer than the stopwatch. In multivariable analyses that adjusted for potential confounders, fallers had slower vertical velocity, reduced vertical acceleration, lower vertical power, and lower vertical jerk than nonfallers. In contrast, the total duration of the test measured by either the IMU or the stopwatch did not differ between the 2 groups. Conclusions: An instrumented 5xSTS test provides additional information that better discriminates among older adults those at risk of multiple or serious falls than the conventional stopwatch-based assessment.
... The variability of the position of the sensor can be an additional limiting factor during free-living. In previous clinical experiments involving inertial sensors, the lower back position at the L3 to L5 vertebrae has been a popular location due to its closeness to the center of mass [48,49], and acceptable for long-term studies at-home use [50,51]. Nevertheless, proper fitting of the sensor by clinical professionals during the first visit would minimize the impact of possible sensor detachment or displacement. ...
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In addition to routine clinical examination, unobtrusive and physical monitoring of Rheumatoid Arthritis (RA) patients provides an important source of information to enable understanding the impact of the disease on quality of life. Besides an increase in sedentary behaviour, pain in RA can negatively impact simple physical activities such as getting out of bed and standing up from a chair. The objective of this work is to develop a method that can generate fine-grained actigraphies to capture the impact of the disease on the daily activities of patients. A processing methodology is presented to automatically tag activity accelerometer data from a cohort of moderate-to-severe RA patients. A study of procesing methods based on machine learning and deep learning is provided. Thirty subjects, 10 RA patients and 20 healthy control subjects, were recruited in the study. A single tri-axial accelerometer was attached to the position of the fifth lumbar vertebra (L5) of each subject with a tag prediction granularity of 3 s. The proposed method is capable of handling unbalanced datasets from tagged data while accounting for long-duration activities such as sitting and lying, as well as short transitions such as sit-to-stand or lying-to-sit. The methodology also includes a novel mechanism for automatically applying a threshold to predictions by their confidence levels, in addition to a logical filter to correct for infeasible sequences of activities. Performance tests showed that the method was able to achieve around 95% accuracy and 81% F-score. The produced actigraphies can be helpful to generate objective RA disease-specific markers of patient mobility in-between clinical site visits.
... The component of acceleration along the vertical axis a v showed a clear change in the signal value as the position of the human body changed while performing the two activities under consideration, Si2St and St2Si. Hence, we used the a v signal for calculating the RQA parameters in this study [29,46,[51][52][53][54]. ...
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Standing up and sitting down are prerequisite motions in most activities of daily living scenarios. The ability to sit down in and stand up from a chair or a bed depreciates and becomes a complex task with increasing age. Hence, research on the analysis and recognition of these two activities can help in the design of algorithms for assistive devices. In this work, we propose a reliability analysis for testing the internal consistency of nonlinear recurrence features for sit-to-stand (Si2St) and stand-to-sit (St2Si) activities for motion acceleration data collected by a wearable sensing device for 14 healthy older subjects in the age range of 78 ± 4.9 years. Four recurrence features—%recurrence rate, %determinism, entropy, and average diagonal length—were calculated by using recurrence plots for both activities. A detailed relative and absolute reliability statistical analysis based on Cronbach’s correlation coefficient (α) and standard error of measurement was performed for all recurrence measures. Correlation values as high as α = 0.68 (%determinism) and α = 0.72 (entropy) in the case of Si2St and α = 0.64 (%determinism) and α = 0.69 (entropy) in the case of St2Si—with low standard error in the measurements—show the reliability of %determinism and entropy for repeated acceleration measurements for the characterization of both the St2Si and Si2St activities in the case of healthy older adults.
... Recently, many groups have reported on various motion sensors for possible real-time personal health monitoring, human-robot interfaces, and industrial robot applications [1][2][3][4][5][6][7][8]. Motion sensing is achieved by attaching sensors at, or near, joints in robots or humans and monitoring their displacement or rotational angle. ...
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In this article, we report on a flexible sensor based on a sandpaper molded elastomer that simultaneously detects planar displacement, rotation angle, and vertical contact pressure. When displacement, rotation, and contact pressure are applied, the contact area between the translating top elastomer electrode and the stationary three bottom electrodes change characteristically depending on the movement, making it possible to distinguish between them. The sandpaper molded undulating surface of the elastomer reduces friction at the contact allowing the sensor not to affect the movement during measurement. The sensor showed a 0.25 mm⁻¹ displacement sensitivity with a ±33 µm accuracy, a 0.027 degree-1 of rotation sensitivity with ~0.95 degree accuracy, and a 4.96 kP⁻¹ of pressure sensitivity. For possible application to joint movement detection, we demonstrated that our sensor effectively detected the up-and-down motion of a human forefinger and the bending and straightening motion of a human arm.
... The decrease in our physical abilities that accompanies age leads to more conservative behavior when performing physically challenging motion tasks. In itself, this speaks for their level of difficulty: dynamic motions like running, climbing stairs, jumping, or standing up from a chair Sloot et al. (2020) require proper leg muscle output, coordination, mobility, and the control of balance at the same time Millor et al. (2014). Implementing such motion sequences on a humanoid robot is equally challenging, as it also demands the aforementioned aspects from the underlying mechanical system Gu and Ballard (2006). ...
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To enable the application of humanoid robots outside of laboratory environments, the biped must meet certain requirements. These include, in particular, coping with dynamic motions such as climbing stairs or ramps or walking over irregular terrain. Sit-to-stand transitions also belong to this category. In addition to their actual application such as getting out of vehicles or standing up after sitting, for example, at a table, these motions also provide benefits in terms of performance assessment. Therefore, they have long been used as a sports medical and geriatric assessment for humans. Here, we develop optimized sit-to-stand trajectories using optimal control, which are characterized by their dynamic and humanlike nature. We implement these motions on the humanoid robot REEM-C. Based on the obtained sensor data, we present a unified benchmarking procedure based on two different experimental protocols. These protocols are characterized by their increasing level of difficulty for quantifying different aspects of lower limb performance. We report performance results obtained by REEM-C using two categories of indicators: primary, scenario-specific indicators that assess overall performance (chair height and ankle-to-chair distance) and subsidiary, general indicators that further describe performance. The latter provide a more detailed analysis of the applied motion and are based on metrics such as the angular momentum, zero moment point, capture point, or foot placement estimator. In the process, we identify performance deficiencies of the robot based on the collected data. Thus, this work is an important step toward a unified quantification of bipedal performance in the execution of humanlike and dynamically demanding motions.
... These disorders effect the overall human mobility. In order to perform these movements, patient requires lot of strength, muscular power and optimal coordination [12]. There are different activities performed from upper and lower limbs on daily basis. ...
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The aim of this study is to analyze a common method to measure the acceleration of a daily activity pattern by using a smartphone. In this sense, a numerical approach is proposed to transform the relative acceleration signal, recorded by a triaxial accelerometer, into an acceleration referred to an inertial reference. The integration of this acceleration allows to determine the velocity and position with respect to an inertial reference. Two different kinematic parameters are suggested to characterize the profile of the velocity during the sit-to-stand and stand-to-sit transitions for Parkinson and control subjects. The results show that a dimensionless kinematic parameter, which is linked to the time of sit-to-stand and stand-to-sit transitions, has the potential to differentiate between Parkinson and control subjects.
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Frailty is becoming an important component of health care outcomes in patients with a diagnosis of heart failure. A literature search was completed to determine whether a best practice guideline existed to assess frailty in patients who were considering ventricular assist device placement. The literature search revealed that best practice guidelines did not exist. A second comprehensive literature search was completed specifically for frailty including the definition, criteria, assessment, and outcomes. The studies revealed that there were challenges with defining frailty, the age of frailty, assessments tools, and study designs. Cardiologists are primarily interested in screening for frailty, but other physician specialty practices are interested in a frailty screening tool as well. This article discusses the inconsistent research studies and the need for a valid and reliable tool to assess for frailty. It is important that nurse leaders and those working with heart failure patients determine the best practice guidelines for assessing frailty.
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Purpose of Review The goal of this paper is to provide a review of recent work on the use of wearable devices for measuring physical activity (PA) in the elderly. Recent Findings In older adults, PA is related to independence in activities of daily living and maintaining a good quality of life. With aging, there is a reduction in PA, which may explain reduced energy expenditure (EE) during rest and PA. In addition, there is also a reduction in the spatial extent of mobility (life-space). Sensors used for measuring PA include pedometers, uni-axial, bi-axial and tri-axial accelerometers, heart rate monitors combined with accelerometers, and complex systems using multiple types of sensors. Summary Wearable sensors are accurate at measuring step counts, PA intensity, and EE, but need to improve accuracy of measuring type of PA, spatial extent of PA, and measuring non-ambulatory PA. Clear standards for measurement, algorithms used for computing clinically relevant measures, need to be developed.
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This study aims at the online estimation of the hip and knee angle in the sagittal plane for the motion surveillance only using the tri-axis accelerometers and gyroscopes of IMU, without considering the magnetic disturbance. The proposed method utilizes the projection of gravity acceleration on each sensor coordinate system to estimate the joint angle which rotating around the horizontal axis and approximately horizontal axis. With the third row of the rotation matrix independent of the yaw angle, the proposed method first calculates the projection of the gravity acceleration on each IMU sensor coordinate system only using accelerometer and gyroscope. And then, the rotation matrix between two adjacent coordinate systems is directly calculated. After evaluating the body to sensor rotation matrix, the rotation matrix between two adjacent body segments can be calculated, ultimately. Two types of experiments are adopted in the paper. The results show that the proposed method obtains the outstanding performance with the RMSE lower than 0.8 deg in the horizontal rotation experiment. In the limb joint experiment, the RMSE of the hip joint is lower than 3.12 deg, while the RMSE of the knee joint is lower than 3.83 deg for all predefined locomotion modes. The characteristic of our approach is that it can be run online without any parameter adjustment and additional time latency while ensuring estimation accuracy.
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Background The Timed Up and Go test is a well-known clinical test for assessing of mobility and fall risk. It has been shown that the IMU which use an accelerometer and gyroscope are capable of analysing the quantitative parameters of the sit-to-stand transition. Research question Which signals obtained by the inertial sensors are suitable for continuous Timed Up & Go test sit-to-stand transition analysis? Methods In the study we included 29 older adult volunteers and 31 de-novo Parkinson disease (PD) patients. All subjects performed an instrumented extended TUG wearing a gyro-accelerometer. The sit-to-stand transition was detected from an angular velocity signal. The sit-to-stand signal pattern within the subject group was analyzed via an intra-class correlation between curves. Inter-subjects’ variability was visualized using prediction bands. Results The angular velocity about the pitch axis exhibited the best signal match across subjects in both groups (0.50 < ICC < 0.75). When analysing acceleration, the acceleration along the antero-posterior axis showed moderate inter-subjects signal pattern match (0.50 < ICC < 0.75) in the reference group. The analysis of other signals revealed a poor signal pattern in both subject groups. Significance For optimal interpretation of the analysis of continuous curves, the signal pattern must be considered. Also, the inter-subject variability along this pattern can be informative and useful.
Article
This work analyses different concepts for frailty diagnosis based on affordable standard technology such as smartphones or wearable devices. The goal is to provide ideas that go beyond classical diagnostic tools such as magnetic resonance imaging or tomography, thus changing the paradigm; enabling the detection of frailty without expensive facilities, in an ecological way for both patients and medical staff and even with continuous monitoring. Fried's five-point phenotype model of frailty along with a model based on trials and several classical physical tests were used for device classification. This work provides a starting point for future researchers who will have to try to bridge the gap separating elderly people from technology and medical tests in order to provide feasible, accurate and affordable tools for frailty monitoring for a wide range of users.
Chapter
Although rollators are often given to older adults, the quality of support has yet to be quantified. This paper evaluates static and dynamic balance during STS in older and younger adults during 3 conditions: unassisted, with a normal rollator, and with a low-handled rollator. We found that older adults get up faster while maintaining both static and dynamic balance less conservatively with the support of a rollator. As such, the assistance reduced the difference in balance that was previously noted between older and younger adults during unassisted STS, and even slightly more so with the low-handled rollator. These results seem to indicate that rollator assistance compensated for reduced physical ability or confidence rather than impaired balance control in these participants. Such insight into the effect of rollator support is necessary to further development of individualized smart robotic rollators.
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The five times sit-to-stand test (FTSS) is an established functional test, used clinically as a measure of lower-limb strength, endurance and falls risk. We report a novel method to estimate and classify cognitive function, balance impairment and falls risk using the FTSS and body-worn inertial sensors. 168 community dwelling older adults received a Comprehensive Geriatric Assessment which included the Mini-Mental State Examination (MMSE) and the Berg Balance Scale (BBS). Each participant performed an FTSS, with inertial sensors on the thigh and torso, either at home or in the clinical environment. Adaptive peak detection was used to identify phases of each FTSS from torso or thigh-mounted inertial sensors. Features were then extracted from each sensor to quantify the timing, postural sway and variability of each FTSS. The relationship between each feature and MMSE and BBS was examined using Spearman’s correlation. Intraclass correlation coefficients were used to examine the intra-session reliability of each feature. A Poisson regression model with an elastic net model selection procedure was used to estimate MMSE and BBS scores, while logistic regression and sequential forward feature selection was used to classify participants according to falls risk, cognitive decline and balance impairment. BBS and MMSE were estimated using cross-validation with low root mean squared errors of 2.91 and 1.50, respectively, while the cross-validated classification accuracies for balance impairment, cognitive decline, and falls risk were 81.96, 72.71, and 68.74%, respectively. The novel methods reported provide surrogate measures which may have utility in remote assessment of physical and cognitive function.
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Timed-Up-and-Go (TUG) is a simple, easy to administer, and frequently used test for assessing balance and mobility in elderly and people with Parkinson's disease. An instrumented version of the test (iTUG) has been recently introduced to better quantify subject's movements during the test. The subject is typically instrumented by a dedicated device designed to capture signals from inertial sensors that are later analyzed by healthcare professionals. In this paper we introduce a smartphone application called sTUG that completely automates the iTUG test so it can be performed at home. sTUG captures the subject's movements utilizing smartphone's built-in accelerometer and gyroscope sensors, determines the beginning and the end of the test and quantifies its individual phases, and optionally uploads test descriptors into a medical database. We describe the parameters used to quantify the sTUG test and algorithms to extract the parameters from signals captured by the smartphone sensors.
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Background: Clinical frailty syndrome is a common geriatric syndrome, which is characterized by physiological reserve decreases and increased vulnerability. The changes associated to ageing and frailties are associated to changes in gait characteristics and the basic functional capacities. Traditional clinical evaluation of Sit-to-Stand (Si-St) and Stand-to-Sit (St-Si) transition is based on visual observation of joint angle motion to describe alterations in coordination and movement pattern. The latest generation smartphones often include inertial sensors with subunits such as accelerometers and gyroscopes, which can detect acceleration. Objective: Firstly, to describe the variability of the accelerations, angular velocity, and displacement of the trunk during the Sit-to-Stand and Stand-to-Sit transitions in two groups of frail and physically active elderly persons, through instrumentation with the iPhone 4 smartphone. Secondly, we want to analyze the differences between the two study groups. Methods: A cross-sectional study that involved 30 subjects over 65 years, 14 frail and 16 fit subjects. The participants were classified with frail syndrome by the Fried criteria. Linear acceleration was measured along three orthogonal axes using the iPhone 4 accelerometer. Each subject performed up to three successive Si-St and St-Si postural transitions using a standard chair with armrest. Results: Significant differences were found between the two groups of frail and fit elderly persons in the accelerometry and angular displacement variables obtained in the kinematic readings of the trunk during both transitions. Conclusions: The inertial sensor fitted in the iPhone 4 is able to study and analyze the kinematics of the Si-St and St-Si transitions in frail and physically active elderly persons. The accelerometry values for the frail elderly are lower than for the physically active elderly, while variability in the readings for the frail elderly is also lower than for the control group.
Conference Paper
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Timed-Up-and-Go (TUG) is a simple, easy to administer, and frequently used test for assessing balance and mobility in elderly and people with Parkinson's disease. An instrumented version of the test (iTUG) has been recently introduced to better quantify subject's movements during the test. The subject is typically instrumented by a dedicated device designed to capture signals from inertial sensors that are later analyzed by healthcare professionals. In this paper we introduce a smartphone application called sTUG that completely automates the iTUG test so it can be performed at home. sTUG captures the subject's movements utilizing smartphone's built-in accelerometer and gyroscope sensors, determines the beginning and the end of the test and quantifies its individual phases, and optionally uploads test descriptors into a medical database. We describe the parameters used to quantify the iTUG test and algorithms to extract the parameters from signals captured by the smartphone sensors.
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Increasing leg strength, leg power and overall balance can improve mobility and reduce fall risk. Sensor-based assessment of peak power during the sit-to-stand (STS) transfer may be useful for detecting changes in mobility and fall risk. Therefore, this study investigated whether sensor-based STS peak power and related measures are sensitive to the effects of increasing leg strength, leg power and overall balance in older adults. A further aim was to compare sensitivity between sensor-based STS measures and standard clinical measures of leg strength, leg power, balance, mobility and fall risk, following an exercise-based intervention. To achieve these aims, 26 older adults (age: 70-84 years) participated in an eight-week exercise program aimed at improving leg strength, leg power and balance. Before and after the intervention, performance on normal and fast STS transfers was evaluated with a hybrid motion sensor worn on the hip. In addition, standard clinical tests (isometric quadriceps strength, Timed Up and Go test, Berg Balance Scale) were performed. Standard clinical tests as well as sensor-based measures of peak power, maximal velocity and duration of normal and fast STS showed significant improvements. Sensor-based measurement of peak power, maximal velocity and duration of normal STS demonstrated a higher sensitivity (absolute standardized response mean (SRM): ≥0.69) to the effects of training leg strength, leg power and balance than standard clinical measures (absolute SRM: ≤0.61). Therefore, the presented sensor-based method appears to be useful for detecting changes in mobility and fall risk.
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Falls are a prevalent issue in the geriatric population and can result in damaging physical and psychological consequences. Fall risk assessment can provide information to enable appropriate interventions for those at risk of falling. Wearable inertial-sensor-based systems can provide quantitative measures indicative of fall risk in the geriatric population. Forty studies that used inertial sensors to evaluate geriatric fall risk were reviewed and pertinent methodological features were extracted; including, sensor placement, derived parameters used to assess fall risk, fall risk classification method, and fall risk classification model outcomes. Inertial sensors were placed only on the lower back in the majority of papers (65%). One hundred and thirty distinct variables were assessed, which were categorized as position and angle (7.7%), angular velocity (11.5%), linear acceleration (20%), spatial (3.8%), temporal (23.1%), energy (3.8%), frequency (15.4%), and other (14.6%). Fallers were classified using retrospective fall history (30%), prospective fall occurrence (15%), and clinical assessment (32.5%), with 22.5% using a combination of retrospective fall occurrence and clinical assessments. Half of the studies derived models for fall risk prediction, which reached high levels of accuracy (62-100%), specificity (35-100%), and sensitivity (55-99%). Inertial sensors are promising sensors for fall risk assessment. Future studies should identify fallers using prospective techniques and focus on determining the most promising sensor sites, in conjunction with determination of optimally predictive variables. Further research should also attempt to link predictive variables to specific fall risk factors and investigate disease populations that are at high risk of falls.
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Aging-related decline in functional mobility is associated with loss of independence. This decline may be mitigated through programs of physical activity. Despite reports of aging-related mobility impairment in middle-aged adults, this age group has been largely overlooked in terms of exercise programs that target functional mobility and the preservation of independence in older age. A method to quantitatively assess changes in functional mobility could direct rehabilitation in a proactive rather than reactive manner. Thirty-three healthy but sedentary middle-aged adults participated in a four week low-volume, vigorous intensity stepping exercise program. Two baseline testing sessions and one post-training testing session were conducted. Functional mobility was assessed using the timed up and go (TUG) test, with its constituent sit-to-walk and walk-to-sit phases examined using a novel inertial sensor-based method. Additionally, semi-tandem balance and knee extensor muscle isometric torque were assessed. Trunk acceleration during walk-to-sit reduced significantly post-training, suggesting altered movement control due to the exercise program. No significant training-induced changes in sit-to-walk acceleration, TUG time, balance or torque were observed. The novel method of functional mobility assessment presented provides a reliable means to quantify subtle changes in mobility during postural transitions. Over time, this exercise program may improve functional mobility.
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The aim of this review was to recommend training strategies, which improve the functional capacity in physically frail older adults based on scientific literature, focusing specially in supervised exercise programs that improved muscle strength, fall risk, balance and gait ability. Scielo, Science Citation Index, MEDLINE, Scopus, Sport Discus and ScienceDirect databases were searched from 1990 to 2012. Studies must have mentioned the effects of exercise training on at least one of the following four parameters: incidence of falls, gait, balance and lower-body strength. Twenty studies which investigated the effects of multi-component exercise training (10), resistance training (6), endurance training (1) and balance training (3) were included in the present revision. Ten trials investigated the effects of exercise on the incidence of falls in elderly with physical frailty. Seven of them have found a fewer falls incidence after physical training when compared with the control group. Eleven trials investigated the effects of exercise intervention on the gait ability. Six of them showed enhancements in the gait ability. Ten trials investigated the effects of exercise intervention on the balance performance and seven of them demonstrated enhanced balance. Thirteen trials investigated the effects of exercise intervention on the muscle strength and nine of them showed increases in the muscle strength. The multi-component exercise intervention composed by strength, endurance and balance training seems to be the best strategy to improve rate of falls, gait ability, balance and strength performance in physically frail older adults.
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Background Motion sensors offer the possibility to obtain spatiotemporal measures of mobility-related activities such as sit-stand and stand-sit transitions. However, the application of new sensor-based methods for assessing sit-stand-sit performance requires the detection of crucial events such as seat on/off in the sensor-based data. Therefore, the aim of this study was to evaluate the agreement of detecting sit-stand and stand-sit events based on a novel body-fixed-sensor method with a force-plate based analysis. Methods Twelve older adults and 10 patients with mild to moderate Parkinson’s disease with mean age of 70 years performed sit-stand-sit movements while trunk movements were measured with a sensor-unit at vertebrae L2-L4 and reaction forces were measured with separate force plates below the feet and chair. Movement onsets and ends were determined. In addition, seat off and seat on were determined based on forces acting on the chair. Data analysis focused on the agreement of the timing of sit-stand and stand-sit events as detected by the two methods. Results For the start and end of standing-up, only small delays existed for the start of forward trunk rotation and end of backward trunk rotation compared to movement onset/end as detected in the force-plate data. The end of forward trunk rotation had a small and consistent delay compared to seat off, whereas during sitting-down, the end of forward trunk rotation occurred earlier in relation to seat on. In detecting the end of sitting-down, backward trunk rotation ended after reaching the minimum in the below-feet vertical force signal. Since only small time differences existed between the two methods for detecting the start of sitting-down, longer movement durations were found for the sensor-based method. Relative agreement between the two methods in assessing movement duration was high (i.e. ICCs ≥ 0.75), except for duration of standing-up in the Parkinson’s patients (ICC = 0.61). Conclusions This study demonstrated high agreement of body-fixed-sensor based detection of sit-stand and stand-sit events with that based on force plates in older adults and patients with mild to moderate Parkinson’s disease. Further development and testing is needed to establish reliability for unstandardized performance in clinical and home settings.
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The Timed Up and Go (TUG) test is a clinical tool widely used to evaluate balance and mobility, e.g. in Parkinson's disease (PD). This test includes a sequence of functional activities, namely: sit-to-stand, 3-meters walk, 180° turning, walk back, and turn-to-sit. The work introduces a new method to instrument the TUG test using a wearable inertial sen-sor unit (DynaPort Hybrid, McRoberts B.V., NL) attached on the lower back of the person. It builds on Dynamic Time Warping (DTW) for detection and duration assessment of associated state transitions. An automatic assessment to sub-stitute a manual evaluation with visual observation and a stopwatch is aimed at to gain objective information about the patients. The algorithm was tested on data of 10 healthy individuals and 20 patients with Parkinson's disease (10 pa-tients for early and late disease phases respectively). The algorithm successfully extracted the time information of the sit-to-stand, turn and turn-to-sit transitions.
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Several methods exist for the assessment of balance. In the clinical setting, they are often assessed through qualitative tests. In the laboratory, instrumentation can quantitatively and more accurately measure balance. To date, force platforms remain one of the most commonly used tools in balance assessment. They are, however, costly and cumbersome, making them impractical in clinical settings and field studies. Utilization of accelerometers in balance assessment has been studied but has not yet become a laboratory standard due to the unknown accuracy of this method. If proven accurate, the use of accelerometers in laboratory and clinical environments would be ideal because they are inexpensive, noninvasive, and easy to transport. The purpose of this study was to compare the use of accelerometers as an inclinometer to the use of a force platform in the assessment of postural stability. A triaxial accelerometer was placed on the trunk of five subjects. The subjects stood barefoot on a force platform under various conditions which affect balance: all sensory systems intact; impaired visual feedback; impaired proprioceptive feedback; and impaired visual and proprioceptive feedback. During each trial, trunk acceleration and ground reaction forces and moments were collected. Force plate data was used to plot the path of the center of pressure and acceleration data was used to plot a projected path of the trunk acceleration. Behavioral similarities were seen in both methods of balance assessment. Therefore, balance assessment via accelerometers is feasible. This method does, however, require further investigation.
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Timed Up and Go (TUG) test is a widely used clinical paradigm to evaluate balance and mobility. Although TUG includes several complex subcomponents, namely: sit-to-stand, gait, 180° turn, and turn-to-sit; the only outcome is the total time to perform the task. We have proposed an instrumented TUG, called iTUG, using portable inertial sensors to improve TUG in several ways: automatic detection and separation of subcomponents, detailed analysis of each one of them and a higher sensitivity than TUG. Twelve subjects in early stages of Parkinson's disease (PD) and 12 age matched control subjects were enrolled. Stopwatch measurements did not show a significant difference between the two groups. The iTUG, however, showed a significant difference in cadence between early PD and control subjects (111.1 ± 6.2 versus 120.4 ± 7.6 step/min, p <; 0.006) as well as in angular velocity of arm-swing (123 ± 32.0 versus 174.0 ± 50.4°/s, p <; 0.005), turning duration (2.18 ± 0.43 versus 1.79 ± 0.27 s, p <; 0.023), and time to perform turn-to-sits (2.96 ± 0.68 versus 2.40 ± 0.33 s, p <; 0.023). By repeating the tests for a second time, the test-retest reliability of iTUG was also evaluated. Among the subcomponents of iTUG, gait, turning, and turn-to-sit were the most reliable and sit-to-stand was the least reliable.
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An instrumented version of the five-times-sit-to-stand test was performed in the homes of a group of older adults, categorised as fallers or non-fallers. Tri-axial accelerometers were secured to the sternum and anterior thigh of each participant during the assessment. Accelerometer data were then used to examine the timing of the movement, as well as the root mean squared amplitude, jerk and spectral edge frequency of the mediolateral (ML) acceleration during the total assessment, each sit-stand-sit component and each postural transition (sit-stand and stand-sit). Differences between fallers and non-fallers were examined for each parameter. Six parameters significantly discriminated between fallers and non-fallers: sit-stand time, ML acceleration for the total assessment, and the ML spectral edge frequency for the complete assessment, individual sit-stand-sit components, as well as sit-stand and stand-sit transitions. These results suggest that each of these derived parameters would provide improved discrimination of fallers from non-fallers, for the cohort examined, than the standard clinical measure - the total time to complete the assessment. These results indicate that accelerometry may enhance the utility of the five-times-sit-to-stand test when assessing falls risk.
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The Timed Up and Go (TUG) test is a widely used measure of mobility and fall risk among older adults that is typically scored using a stopwatch. We tested the hypothesis that a body-fixed accelerometer can enhance the ability of the TUG to identify community-living older adults with a relatively high fall risk of unknown origin. Twenty-three community-living elderly fallers (76.0 ± 3.9 years) and 18 healthy controls (68.3 ± 9.1 years) performed the TUG while wearing a 3D-accelerometer on the lower back. Acceleration-derived parameters included Sit-to-Stand and Stand-to-Sit times, amplitude range (Range), and slopes (Jerk). Average step duration, number of steps, average step length, gait speed, acceleration-median, and standard-deviation were also calculated. While the stopwatch-based TUG duration was not significantly different between the groups, acceleration-derived TUG duration was significantly higher (p = 0.007) among the fallers. Fallers generally exhibited lower Range and Jerk (p < 0.01). While TUG stopwatch duration successfully identified 63% of the subjects, an accelerometer-derived three-measure-combination correctly classified 87% of the subjects. Accelerometer-derived measures were generally not correlated with TUG duration. These findings demonstrate that fallers have difficulty with specific TUG aspects that can be quantified using an accelerometer. Without compromising simplicity of testing, an accelerometer can apparently be combined with TUG duration to provide complementary, objective measures that allow for a more complete, sensitive TUG-based fall risk assessment.
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