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Scatterplots, histograms and Bland-Altman graphs that compare the data acquired by the Strideway (SW) and the SmartInsoles Cyber-Physical System (CPS) (IN). Scatterplots, histograms and Bland-Altman graphs that compare the data acquired by the Strideway (SW) and the SmartInsoles Cyber-Physical System (CPS) (IN).
Source publication
A SmartInsoles Cyber-Physical System (CPS) is designed and implemented for the purpose of measuring gait parameters of multiple users in a restriction-free environment. This CPS comprises a master software installed on a computer and numerous multi-sensory health devices in the form of smart insoles. Each of these insoles contains 12 Force-Sensitiv...
Contexts in source publication
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... data used to plot the graphs in Figure 4 were the results produced after averaging left and right foot data for each of the seven analyzed gait parameters. This way, a single value was produced for each trial by each system. ...
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... way, a single value was produced for each trial by each system. MATLAB (R2018) was used for all statistical analysis and to generate all graphs in Figure 4. In some cases, during the experiment, one of the systems could fail to deliver results for a specific test. ...
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... trend line (or a line of best fit) on a scatterplot was used to represent the trend of the data and indicated the likelihood of results if other data were present. In each parameter's scatterplot shown in Figure 4, a trend line is shown as a continuous straight line. Since this was a comparison between the results of two systems measuring the same information, the trend line should ideally fall exactly on the 45-degree reference line (y = x), which is shown as a straight dashed line. ...
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... show the number of occurrences of a value in a specific range. The values shown in the histograms in Figure 4 represent the time difference between the Strideway data and the insoles' data for each of the analyzed parameters. The width of each bar (bin) represents the range of error, and the y-axis shows how many times an error falls within this bin's range during our experiment. ...
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... the differences were normally distributed, 95% of the values would be between these two limit lines [36]. Table 1 shows a numerical analysis and a summary of the data in Figure 4. The first column represents the analyzed parameters, and the mean difference is shown in the second column. ...
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... these histograms, values should follow a bell-shaped normal distribution, and the peak y-axis value should be around the zero x-axis value. Figure 4. Scatterplots, histograms and Bland-Altman graphs that compare the data acquired by the Strideway (SW) and the SmartInsoles Cyber-Physical System (CPS) (IN). ...
Citations
... Similarly, floor sensing products and smart insoles integrate pressure measurement technologies, including capacitive, resistive, piezoelectric, and piezoresistive sensors. Floor sensing products, such as gait pressure measurement mats [20], priced at around 25,000 USD [21], are cumbersome and limited to capturing only a few steps within a restricted space, resulting in missed gait patterns. Smart insoles face challenges in long-term reliability due to the limited lifespan of sensors and the absence of spatial parameter measurements [22] [23]. ...
We developed a shoe-mounted gait monitoring system capable of tracking up to 17 gait parameters, including gait length, step time, stride velocity, and others. The system employs a stereo camera mounted on one shoe to track a marker placed on the opposite shoe, enabling the estimation of spatial gait parameters. Additionally, a Force Sensitive Resistor (FSR) affixed to the heel of the shoe, combined with a custom-designed algorithm, is utilized to measure temporal gait parameters. Through testing on multiple participants and comparison with the gait mat, the proposed gait monitoring system exhibited notable performance, with the accuracy of all measured gait parameters exceeding 93.61%. The system also demonstrated a low drift of 4.89% during long-distance walking. A gait identification task conducted on participants using a trained Transformer model achieved 95.7% accuracy on the dataset collected by the proposed system, demonstrating that our hardware has the potential to collect long-sequence gait data suitable for integration with current Large Language Models (LLMs). The system is cost-effective, user-friendly, and well-suited for real-life measurements.
... Smart Insoles gait measurement system dubbed Cyber-Physical System (CPS) fashioned and applied for restriction-free environment gait parameters measurement of multiple users was presented by [88]. This CPS consists of installed master software on a computer and several multi-sensor health device units in the form of smart insoles. ...
... Even though we placed smart insoles under soft systems, there are related insole systems that also essentially feature commercially available microsensors, computing, and wireless technologies and this category of sensors does not qualify as soft sensors [88]. Those that suit our classification are soft sensors such as parallel capacitance-based pressure sensors, using conductive textiles etc. [90]. ...
Wearable devices for gait measurement are devices worn on the body to measure the gait of the wearers. During gait measurement, several parameters are measured and the choice of parameters is influenced by the application and by extension the gait index. Two approaches have been adopted in this research. One is the provision of an overview of wearable devices for gait measurement with a bias towards textile-based “soft” smart wearable systems using information from varied academic sources and databases. The second approach is to map out key scientific research trends within the wearable device classes using the Web of Science database. The focus is to make a case for textile-based gait measurement devices and systems while exploring the key determinants of wearable gait sensor placements and application efficiency. These soft smart wearable systems describe flexible material sensor-based systems which have their sensing mechanisms based on material deformation after being subjected to stress or pressure. This study could therefore serve as an apt reference for the development of soft smart wearable gait measurement systems as it throws light on the various soft wearable gait measurement applications, the bottlenecks in soft wearable device design, opportunities for developing new devices and the merit that soft gait analysis systems possess over their hard gait measurement counterparts.
... However, the mark-based methods own very accurate indications and are closer to the actual values [18]. When the marks are installed on the body and the person begins gait, these signs also begin to move, and the movement of the lower bones can be understood from the movement of these signs [36]. The problem here is that the movement of the skin of the body is accompanied by the movement of the following bones, which leads to the wrong movement of the marks, and as a result, the accuracy of the measurement is reduced [36]. ...
... When the marks are installed on the body and the person begins gait, these signs also begin to move, and the movement of the lower bones can be understood from the movement of these signs [36]. The problem here is that the movement of the skin of the body is accompanied by the movement of the following bones, which leads to the wrong movement of the marks, and as a result, the accuracy of the measurement is reduced [36]. ...
... On the other hand, these methods are less accurate than marks-based methods [37]. In the first method, there is a large amount of data for processing from which the desired properties must be extracted, whereas in the marks-based methods, the desired information was provided concerning that particular location [36]. Here, data is collected from a marks-independent method that results in performing the test in the fastest possible way by the candidates. ...
Abstract Today, the elderly population is increasing, and there are many drawbacks for them, especially defects in their knee joints which lead to improper gait. To solve this problem, their knee joint can be replaced with knee arthroplasty. In this letter, level of improvement in the human gait before and after total knee arthroplasty (TKA) surgery is investigated using the dynamic time warping (DTW) algorithm. For this purpose, several volunteers who have problems with their knees are incorporated in a test before and after TKA surgery. Then, the data of gait analysis is collected and the data is compared with a reference using the DTW algorithm. The outcome results illustrate an improvement of 89%–97% by the proposed algorithm after TKA surgery. Therefore, patients can see improvement with high accuracy and very fast that result in more use this technique in TKR surgery.
... Whilst many systems exist that are capable of recording plantar pressures and spatio-temporal parameters of gait in isolation, few systems are available that can record these features concurrently. Systems such as Strideway ™ incorporate both plantar pressure analysis and spatio-temporal parameters, using a tiled walkway embedded with force sensors [8]. Strideway ™ provides a comprehensive evaluation of an individual's gait pressure and spatio-temporal parameters through quantitative analysis [8]. ...
... Systems such as Strideway ™ incorporate both plantar pressure analysis and spatio-temporal parameters, using a tiled walkway embedded with force sensors [8]. Strideway ™ provides a comprehensive evaluation of an individual's gait pressure and spatio-temporal parameters through quantitative analysis [8]. However, there is little research available regarding the reliability or validity of Strideway ™ for either research or clinical purposes [8]. ...
... Strideway ™ provides a comprehensive evaluation of an individual's gait pressure and spatio-temporal parameters through quantitative analysis [8]. However, there is little research available regarding the reliability or validity of Strideway ™ for either research or clinical purposes [8]. Furthermore, whilst the benefits of a system capable of providing such extensive data are evident, more cost-effective alternatives may be required by practitioners. ...
Background
Clinical gait analysis is widely used to aid the assessment and diagnosis of symptomatic pathologies. Foot function pressure systems such as F-scan and analysis of the spatial–temporal parameters of gait using GAITRite® can provide clinicians with a more comprehensive assessment. There are systems however, such as Strideway™ that can measure these parameters simultaneously but can be expensive. F-Scan in-shoe pressure data is normally collected whilst the person is walking on a hard floor surface. The effects of the softer Gaitrite® mat upon the F-Scan in-shoe sensor pressure data is unknown. This study therefore aimed to assess the agreement between F-Scan pressure measurements taken from a standard walkway (normal hard floor), and those from a GAITRite® walkway to establish whether these two pieces of equipment (in-shoe F-Scan and GAITRite®) can be used simultaneously, as a cost-effective alternative.
Method
Twenty-three participants first walked on a standard floor and then on a GAITRite® walkway wearing F-Scan pressure sensor insoles with same footwear. They repeated these walks three times on each surface. Mid gait protocols were utilised by analysing the contact pressure of the first and second metatarsophalangeal joint of the third, fifth and seventh step from each walk. For both joints, 95% Bland–Altman Limits of Agreement was used to determine a level of agreement between the two surfaces, using mean values from pressure data collected from participants who successfully completed all required walks. The intraclass correlation coefficient (ICC) and Lin’s concordance correlation coefficient were calculated as indices of reliability.
Findings
ICC results for the hard surface and the GAITRrite® walkway at the first and second metatarsophalangeal joints were 0.806 and 0.991 respectively. Lin’s concordance correlation coefficient for the first and second metatarsophalangeal joints were calculated to be 0.899 and 0.956 respectively. Both sets of statistics indicate very good reproducibility. Bland–Altman plots revealed good repeatability of data at both joints.
Conclusion
The level of agreement in F-Scan plantar pressures observed between walking on a normal hard floor and on a GAITRite® walkway was very high, suggesting that it is feasible to use F-Scan with GAITRite® together in a clinical setting, as an alternative to other less cost-effective standalone systems. Although it is assumed combining F-Scan with GAITRite® does not affect spatiotemporal analysis, this was not validated in this study.
... A Bland-Altman graph was employed to analyze the agreement between data sets acquired by two systems. The y-axis represents the difference between the two values, while the x-axis represents the average of these values [19]. The computation of a coefficient of the agreement provided a quantitative index of the reliability of the testing system [16]. ...
Background: Biomechanical alterations are the primary changes that result in development, progression, or increased risk of injury/disease. The use of wearable has gained significant importance in clinical research for early diagnosis and prediction of injury/disease, thereby providing rehabilitation based on the information received from such devices. Objective: This study aims to develop a wearable device for real-time assessment and feedback of limb load asymmetry (LLA) and dynamic plantar pressure asymmetry (PPA). Method: A focus group discussion was conducted with an experienced group of physiotherapists to identify the needs of the clinicians for the assessment and rehabilitation of patients with gait and balance disorders in knee osteoarthritis. The prototype device (DT-walk) was fabricated in a pair of insole-based devices, using two inertial measurement unit (IMU) sensors, ten force-sensitive resistors (FSR), and a pair of insoles-shaped custom-made pressure-sensitive matrix made of 16×8 using velostat and copper tape. A set of five FSRs are used in each insole that lies underneath the custom pressure sensitive matrix. Each controller unit incorporates one microcontroller, wireless communication module, storage, and power unit. The data was sent to a mobile computing device for real-time analysis and visualization. Results: DT-walk showed excellent intra-rater and inter-rater reliability and good to excellent validity against the WinTrack platform for static LLA and dynamic PPA in KOA. The reliability had ICC>0.9, SEM=0.002-0.00668, MDC= 0.00556-0.01852 and CV=5.43-13.15%. Validity had ICC>0.9, SEM=0.00234-0.98608, MDC= 0.00648-2.73327 and CV=2.31-82.68%. Conclusion: The DT-walk, a wearable device, was equally effective in assessing asymmetries in limb loading and plantar pressure compared to the platform-based device. Future studies should evaluate the validity of this device in healthy and diseased conditions.
... Otro sistema es el sensor FSR portátil que se utiliza para medir la distribución de la presión y los cambios en una plantilla, puede recopilar la información de cambios de presión y posiciones aplicadas de la fuerza al caminar, correr, saltar [164]. Por su parte, el tekscan de análisis de la marcha incluye placas de fuerza, captura de movimiento y sistemas EMG, para la investigación y evaluación de la marcha a través de datos objetivos y cuantificables; y se ha utilizado para validar un sistema ciberfísico SmartInsoles para medir los parámetros de la marcha de múltiples usuarios en un entorno libre de restricciones [7]. 25 ...
Gait recognition is a computational approach to the analysis of human gait. This
approach is based on the evaluation and comparison of each individual walking patterns. This work focuses on the development of a framework for the analysis and automatic recognition of gait abnormalities based on human kinematics. The first stage of the framework consists of the development of forward kinematic of position modeling of an 8 degrees of freedom (DoF) system and a reduced 3 DoF system that represent the lower limbs during the gait cycle. In this stage, the conventional methods based on geometry and Denavit-Hartenberg are used, and a novel approach for calculating the kinematics based on quaternion algebra is proposed. Derived from the above, the analysis and visualization of normal gait and crouch gait in Cartesian space in the 3 anatomical planes based on unconventional metrics is performed. In the second stage of the research work, a method based on geometry and coordinate transformation is proposed for the calculation of the inverse kinematics of position of the same kinematic models of 8 DoF and 3 DoF, respectively. In this phase, the analysis and visualization of the normal gait and crouched gait is conducted in the 3 anatomical planes in the joint space.
The last stage consists in the development of a framework for antalgic and non-antalgic gait recognition, based on an experimental system for the measurement of activity using the gyroscope of a smartphone. In this stage, a detailed description of each of the phases of the workflow is provided, emphasizing the experimental design, data validation, as well as features extraction/selection. The classification algorithms used are k-nearest neighbors, Naive Bayes, support vector machines, linear discriminant analysis, decision trees, and classifier ensemble. The metrics used to evaluate the performance of the classification stage are accuracy, f-measure, sensitivity, specificity, and precision.
... Calibrated shoe implemented as a novel rehabilitation strategy and demonstrated the significant result in terms of improvement in gait analysis through monitoring gait variables; step length, stride length, single limb support and walking speed (Elbaz et al., 2014). Instrumented wireless smart insole for mobile gait analysis demonstrated the optimal results in obtaining the spatiotemporal parameters of gait (Arafsha et al., 2018). ...
Early monitoring in knee arthroplasty is a critical issue to tackle deviation from expected healing, patient satisfaction and ensuring quality of life. There are various methods suggested and implemented over years with varied degree of performance. This paper presents a relevant review of technology assisted gait analysis in knee arthroplasty. The systematic search 2 S. Raghav et al. revealed 272 studies, of which 13 were added retrospectively through reference screening of the included articles. After title and abstract screening, only 20 studies were included in this review. This review paper provides a comprehensive overview of applications of technology assisted gait analysis to monitor and quantify the status of waking. There is moderate-quality of evidence showed technology-assisted; in particular, sensor-based technology, motion sensors and motion analysis results in a statistically significant improvement in monitoring of gait parameters.
... However, the marks-based methods own very accurate indications and are closer to the actual values [29]. When the marks are installed on the body and the person begins to gait, these signs also begin to move, and the movement of the lower bones can be understood from the movement of these signs [31]. The problem here is that the movement of the skin of the body is accompanied by the movement of the following bones, which leads to the wrong movement of the marks and as a result, the accuracy of the measurement is reduced [31]. ...
... When the marks are installed on the body and the person begins to gait, these signs also begin to move, and the movement of the lower bones can be understood from the movement of these signs [31]. The problem here is that the movement of the skin of the body is accompanied by the movement of the following bones, which leads to the wrong movement of the marks and as a result, the accuracy of the measurement is reduced [31]. Other methods are mark's independent in that no sign or sensor is installed on the body. ...
... Because in the first method there is a large amount of data for processing from which the desired properties must be extracted. Whereas in the marks-based methods, the desired information was provided concerning that particular location [31]. In this letter, data is collected from a mark's independent method that results in performing the test in the fastest possible way by candidates. ...
Today, the elderly population is increasing and they endure many drawbacks, especially defects in their knee joints which lead to improper gait. To solve this problem, their knee joint can be replaced with knee arthroplasty. In this letter, the level of improvement in the human gait before and after total knee arthroplasty (TKA) surgery is investigated using the Dynamic Time Wrapping (DTW) algorithm. For this purpose, several volunteers who have problems with their knees incorporate in a test before and after TKA surgery, and data of gait analysis is collected. Then, the obtained data is compared with a reference using the DTW algorithm. The outcome results illustrate an improvement of 89\% - 97\% by the proposed algorithm after TKA surgery. Therefore, patients can see improvement with high speed and accuracy that result in more promising for using TKA surgery.
... (2017), on the other hand, developed the eSHOE, which consists of four FSR sensors, a three-axis accelerometer, and a three-axis gyroscope, and reported good agreement with the gait parameters obtained from the GAITRite mat (89). Various other studies have also examined the applicability of shoebased systems for gait analysis (85,(90)(91)(92). ...
Background
Despite being available for more than three decades, quantitative gait analysis remains largely associated with research institutions and not well leveraged in clinical settings. This is mostly due to the high cost/cumbersome equipment and complex protocols and data management/analysis associated with traditional gait labs, as well as the diverse training/experience and preference of clinical teams. Observational gait and qualitative scales continue to be predominantly used in clinics despite evidence of less efficacy of quantifying gait.
Research objective
This study provides a scoping review of the status of clinical gait assessment, including shedding light on common gait pathologies, clinical parameters, indices, and scales. We also highlight novel state-of-the-art gait characterization and analysis approaches and the integration of commercially available wearable tools and technology and AI-driven computational platforms.
Methods
A comprehensive literature search was conducted within PubMed, Web of Science, Medline, and ScienceDirect for all articles published until December 2021 using a set of keywords, including normal and pathological gait, gait parameters, gait assessment, gait analysis, wearable systems, inertial measurement units, accelerometer, gyroscope, magnetometer, insole sensors, electromyography sensors. Original articles that met the selection criteria were included.
Results and significance
Clinical gait analysis remains highly observational and is hence subjective and largely influenced by the observer's background and experience. Quantitative Instrumented gait analysis (IGA) has the capability of providing clinicians with accurate and reliable gait data for diagnosis and monitoring but is limited in clinical applicability mainly due to logistics. Rapidly emerging smart wearable technology, multi-modality, and sensor fusion approaches, as well as AI-driven computational platforms are increasingly commanding greater attention in gait assessment. These tools promise a paradigm shift in the quantification of gait in the clinic and beyond. On the other hand, standardization of clinical protocols and ensuring their feasibility to map the complex features of human gait and represent them meaningfully remain critical challenges.
... However, the institution of sophisticated hardware for non-wearable sensor-based setups in the laboratory makes them more expensive than wearable ones. Therefore, some hybrid form of wearable sensor-based setups such as (CONTEMPLAS [28], BTS GaitLab [29], and Tekscan: Pressure Mapping [30]) are developed for cost-effective gait analysis with improved accuracy. Similarly, two or more non-wearable sensor-based setups combine to form a hybrid one, such as M3D gait analysis system [31] (motion sensors and force places). ...
A Comparative Performance Analysis of Backpropagation Training
Optimizers to Estimate Clinical Gait Mechanics” indicates that the clinical gait analysis
of healthy people of different age groups plays a significant role in the early estimation
of different physiological and neurological disorders. However, due to complicated data
acquisition setups and in-person requirements, the estimation of the gait analysis has
been quite tough to follow. To avoid such issues, a ML-based approach has been proposed
in this work to estimate the biomechanical gait parameters. Three backpropagation neural
network models with Levenberg-Marquardt method, resilient backpropagation method,
and gradient descent method optimizers have been designed to estimate the joint angles,
joint moments, and ground reaction forces in the sagittal plane. The dataset used in the
neural network models has been taken from an open-source repository. The anthropometric, biological, and spatiotemporal parameters of 50 different subjects have been
exploited as input dataset.
