No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Contribution to the design of wearable and environmental sensors for measuring respiration and vertical jumping
ResearchGate has not been able to resolve any citations for this publication.
Sensors for respiratory monitoring can be classified into wearable and non-wearable systems. Wearable sensors can be worn in several positions, the chest being one of the most effective. In this paper, we have studied the performance of a new piezoresistive breathing sensing system to be worn on the chest with a belt. One of the main problems of belt-attached sensing systems is that they present trends in measurements due to subject movements or differences in subject constitution. These trends affect sensor performance. To mitigate them, it is possible to post-process the data to remove trends in measurements, but relevant data from the respiration signal may be lost. In this study, two different detrending methods are applied to respiration signals. After conducting an experimental study with 21 subjects who breathed in different positions with a chest piezoresistive sensor attached to a belt, detrending method 2 proved to be better at improving the quality of respiration signals.
Background
Vertical jump height is widely used in health care and sports fields to assess muscle strength and power from lower limb muscle groups. Different approaches have been proposed for vertical jump height measurement. Some commonly used approaches need no sensor at all; however, these methods tend to overestimate the height reached by the subjects. There are also novel systems using different kind of sensors like force-sensitive resistors, capacitive sensors, and inertial measurement units, among others, to achieve more accurate measurements.
Objective
The objective of this study is twofold. The first objective is to validate the functioning of a developed low-cost system able to measure vertical jump height. The second objective is to assess the effects on obtained measurements when the sampling frequency of the system is modified.
Methods
The system developed in this study consists of a matrix of force-sensitive resistor sensors embedded in a mat with electronics that allow a full scan of the mat. This mat detects pressure exerted on it. The system calculates the jump height by using the flight-time formula, and the result is sent through Bluetooth to any mobile device or PC. Two different experiments were performed. In the first experiment, a total of 38 volunteers participated with the objective of validating the performance of the system against a high-speed camera used as reference (120 fps). In the second experiment, a total of 15 volunteers participated. Raw data were obtained in order to assess the effects of different sampling frequencies on the performance of the system with the same reference device. Different sampling frequencies were obtained by performing offline downsampling of the raw data. In both experiments, countermovement jump and countermovement jump with arm swing techniques were performed.
Results
In the first experiment an overall mean relative error (MRE) of 1.98% and a mean absolute error of 0.38 cm were obtained. Bland-Altman and correlation analyses were performed, obtaining a coefficient of determination equal to R2=.996. In the second experiment, sampling frequencies of 200 Hz, 100 Hz, and 66.6 Hz show similar performance with MRE below 3%. Slower sampling frequencies show an exponential increase in MRE. On both experiments, when dividing jump trials in different heights reached, a decrease in MRE with higher height trials suggests that the precision of the proposed system increases as height reached increases.
Conclusions
In the first experiment, we concluded that results between the proposed system and the reference are systematically the same. In the second experiment, the relevance of a sufficiently high sampling frequency is emphasized, especially for jump trials whose height is below 10 cm. For trials with heights above 30 cm, MRE decreases in general for all sampling frequencies, suggesting that at higher heights reached, the impact of high sampling frequencies is lesser.
Respiratory rate is an important parameter for many health, home care, work, or sport applications. In this paper, a new wearable sensing system based on a piezoresistive FlexiForce sensor has been developed. The sensor can be attached to any common chest strap. A compact 3D casing has been designed and printed with a 3D printer. This casing integrates the sensor and all auxiliary elements of the system: microcontroller, battery, Bluetooth module, connections, battery charger, and acquisition circuit. To the best of our knowledge, this is the first study presenting a FlexiForce respiration sensor that includes all system elements in a single compact casing. The source files with the design of the casing have been published as supplementary material to be reused by any interested researcher. The sensing system was tested with twenty-one subjects for different breathing rates. Two different algorithms were developed to obtain the respiratory rate from the voltage signals recorded by the sensor. Statistical tests were performed to determine the optimal computation time window and algorithm. This approach is also novel in this field. Low error values were obtained for a time window of 27 s with an algorithm based on the calculation of time between zero-crossings (4.02%) and with an algorithm based on counting them (3.40%). To promote research transparency and reusability, the dataset with the recorded data and the source code of the algorithms and statistical tests have also been published. Therefore, an open, replicable, low-error, wearable, wireless, and compact sensing system to measure respiratory rate was developed and tested.
In this paper, a novel human respiration detection method, which is based on angular velocity, is proposed for continuous acquisition and analysis of respiratory signals. Using patient-specific infor-mation derived from a wearable sensor, our proposed system is capable of monitoring human respiration, and assists in identifying the potential respiratory disorders by relying on pre-defined simple procedures. Specifically, our signal verification platform is equipped with a carbon dioxide concentration detection de-vice in order to acquire a synchronous signal. In addition, a median filter method is used to extract the res-piratory waveform from the original signal. The obtained angular velocity waveform pertaining to human respiration is then compared with the respiratory carbon dioxide concentration waveform, and the validity of our designated parameters is verified. The test results demonstrate that our implemented system is ap-propriate for unobtrusive respiratory signals acquisition and analysis and therefore, it can be considered as a potential alternative for physiological monitoring and respiratory disorders screening.
The purpose of this study was to develop and deploy a low cost vertical jump platform using readily available materials for Science, Technology, Engineering, and Mathematics (STEM) education and outreach in the inner city. The platform was used to measure the jumping ability of participants to introduce students to the collection and analysis of scientific data in an engaging, accessible manner. This system was designed and fabricated by a student team of engineers as part of a socially informed engineering and design class. The vertical jump platform has been utilized in 10 classroom lectures in physics and biology. The system was also used in an after school program in which high school volunteers prepared a basketball based STEM outreach program, and at a community outreach events with over 100 participants. At present, the same group of high school students are now building their own set of vertical jump platform under the mentorship of engineering undergraduates. The construction and usage of the vertical jump platform provides an accessible introduction to the STEM fields within the urban community.
Objective:
Consumers are living longer, creating more pressure on the health system and increasing their requirement for self-care of chronic conditions. Despite rapidly-increasing numbers of mobile health applications ('apps') for consumers' self-care, there is a paucity of research into consumer engagement with electronic self-monitoring. This paper presents a qualitative exploration of how health consumers use apps for health monitoring, their perceived benefits from use of health apps, and suggestions for improvement of health apps.
Materials and methods:
'Health app' was defined as any commercially-available health or fitness app with capacity for self-monitoring. English-speaking consumers aged 18 years and older using any health app for self-monitoring were recruited for interview from the metropolitan area of Perth, Australia. The semi-structured interview guide comprised questions based on the Technology Acceptance Model, Health Information Technology Acceptance Model, and the Mobile Application Rating Scale, and is the only study to do so. These models also facilitated deductive thematic analysis of interview transcripts. Implicit and explicit responses not aligned to these models were analyzed inductively.
Results:
Twenty-two consumers (15 female, seven male) participated, 13 of whom were aged 26-35 years. Eighteen participants reported on apps used on iPhones. Apps were used to monitor diabetes, asthma, depression, celiac disease, blood pressure, chronic migraine, pain management, menstrual cycle irregularity, and fitness. Most were used approximately weekly for several minutes per session, and prior to meeting initial milestones, with significantly decreased usage thereafter. Deductive and inductive thematic analysis reduced the data to four dominant themes: engagement in use of the app; technical functionality of the app; ease of use and design features; and management of consumers' data.
Conclusions:
The semi-structured interviews provided insight into usage, benefits and challenges of health monitoring using apps. Understanding the range of consumer experiences and expectations can inform design of health apps to encourage persistence in self-monitoring.
Individuals with obstructive sleep apnea (OSA) can experience partial or complete collapse of the upper airway during sleep. This condition affects between 10-17% of adult men and 3-9% of adult women, requiring arousal to resume regular breathing. Frequent arousals disrupt proper sleeping patterns and cause daytime sleepiness. Untreated OSA has been linked to serious medical issues including cardiovascular disease and diabetes. Unfortunately, diagnosis rates are low (~20%) and current sleep monitoring options are expensive, time-consuming, and uncomfortable. Towards the development of a convenient, non-contact OSA monitoring system, this paper presents a simple, computer vision-based method to monitor cardiopulmonary signals (respiratory and heart rates) during sleep. System testing was performed with 17 healthy participants in five different simulated sleep positions. To monitor cardiopulmonary rates, distinctive points are automatically detected and tracked in infrared image sequences. Blind source separation is applied to extract candidate signals of interest. The optimal respiratory and heart rates are determined using periodicity measures based on spectral analysis. Estimates were validated by comparison to polysomnography recordings. The system achieved a mean percentage error of 3.4% and 5.0% for respiratory rate and heart rate respectively. This study represents an important step in building an accessible, unobtrusive solution for sleep apnea diagnosis.
We present a study evaluating two respiratory rate estimation algorithms using videos obtained from placing a finger on the camera lens of a mobile phone. The two algorithms, based on Smart Fusion and Empirical Mode Decomposition (EMD), consist of previously developed signal processing methods to detect features and extract respiratory induced variations in photoplethysmographic signals to estimate respiratory rate. With custom-built software on an Android phone, photoplethysmographic imaging videos were recorded from 19 healthy adults while breathing spontaneously at respiratory rates between 6 to 32 breaths/min. Signals from two pulse oximeters were simultaneously recorded to compare the algorithms' performance using mobile phone data and clinical data. Capnometry was recorded to obtain reference respiratory rates. Two hundred seventy-two recordings were analyzed. The Smart Fusion algorithm reported 39 recordings with insufficient respiratory information from the photoplethysmographic imaging data. Of the 232 remaining recordings, a root mean square error (RMSE) of 6 breaths/min was obtained. The RMSE for the pulse oximeter data was lower at 2.3 breaths/min. RMSE for the EMD method was higher throughout all data sources as, unlike the Smart Fusion, the EMD method did not screen for inconsistent results. The study showed that it is feasible to estimate respiratory rates by placing a finger on a mobile phone camera, but that it becomes increasingly challenging at respiratory rates greater than 20 breaths/min, independent of data source or algorithm tested.
The objective of the study was to assess the use of maximum (Vmax) and final propulsive phase (FPV) bar velocity to predict jump height in the weighted jump squat. FPV was defined as the velocity reached just before bar acceleration was lower than gravity (-9.81 m∙s-2). Vertical jump height was calculated from the take-off velocity (Vtake-off) provided by a force platform. Thirty swimmers belonging to the National Slovenian swim-ming team performed a jump squat incremental loading test, lifting 25%, 50%, 75% and 100% of body weight in a Smith machine. Jump performance was simultaneously monitored using an AMTI portable force platform and a linear velocity transducer attached to the barbell. Simple linear regression was used to estimate jump height from the Vmax and FPV recorded by the linear velocity transducer. Vmax (y = 16.577x - 16.384) was able to explain 93% of jump height variance with a standard error of the estimate of 1.47 cm. FPV (y = 12.828x - 6.504) was able to explain 91% of jump height variance with a standard error of the estimate of 1.66 cm. Despite that both variables resulted to be good predictors, heteroscedasticity in the differ-ences between FPV and Vtake-off was observed (r2 = 0.307), while the differences between Vmax and Vtake-off were homogenously distributed (r2 = 0.071). These results suggest that Vmax is a valid tool for estimating vertical jump height in a loaded jump squat test performed in a Smith machine.
In this paper we present a respiration sensor suitable for an integration into a wireless body sensor worn around the chest. The thorax expansion and contraction during in- and exhalation is captured using a force-sensing resistor. Based on the captured thoracic movements, the breaths are determined with a peak detection algorithm. For evaluation, a treadmill experiment with five subjects was conducted using an ergospirometry system as a reference. Overall, an average deviation of −0.32±0.68 min−1 in the respiration rate between the ergospirometry and our sensor was observed. In general, the captured thoracic movements showed breaths as distinctive oscillations, but in some cases a non-optimal pressure transfer between thorax and sensor was observed. Therefore, a mechanical housing mechanism was developed. A comparison of our construction with a respiratory inductance plethysmography (RIP)-based sensor shows a close relationship with the captured thoracic movements during normal and deep respiration.
The purpose of this investigation was to analyze the concurrent validity and reliability of an iPhone app (called: My Jump) for measuring vertical jump performance. Twenty recreationally-active healthy men (age: 22.1 ± 3.6 years) completed five maximal countermovement jumps (CMJ), which were evaluated using a force platform (time in the air –TIA– method) and a specially designed iPhone app. My jump was developed to calculate the jump height from flight time using the high-speed video recording facility on the iPhone 5s. Jump heights of the 100 jumps measured, for both devices, were compared using the intraclass correlation coefficient (ICC), Pearson product-moment correlation coefficient (r), Cronbach’s alpha (α), coefficient of variation (CV) and Bland-Altman plots. There was an almost perfect agreement between the force platform and My Jump for the CMJ height (ICC = 0.997, p < 0.001; Bland-Altman bias= 1.1 ±0.5cm, p < 0.001). In comparison with the force platform, My Jump showed good validity for the CMJ height (r = 0.995, p < 0.001). The results of the present study show that CMJ height can be easily, accurately, and reliably evaluated using a specially developed iPhone 5s app.
A method of estimating force using an accelerometer is presented. This model is based on estimating the resultant acceleration of a body at its centre of mass using a tri-axial accelerometer. A data set of ground reaction forces are gathered using a force platform, which is used as the control for this experiment. Signal processing techniques for resampling the accelerometer signals, along with a method of cross correlation to align the force platform and accelerometer traces are used. The purpose of this study was to compare force calculated using accelerometer data from the SHIMMER device, with force platform data on counter movement and drop jumps, for use in sports biomechanics. The method was validated using twelve physically active adults who performed 5 counter movement jumps and 5 drop jumps from a height of 0.30 m. An accelerometer was attached near the participant's centre of mass and simultaneous force and acceleration data were obtained for the jumps. Minimum eccentric force and peak concentric force were calculated concurrently for countermovement jumps and peak landing forces were calculated concurrently for drop jumps. The results showed moderate to low levels of agreement in forces and a consistent systematic bias between the results from the force platform and accelerometer. However, good agreement between the accelerometer and force platform was observed during the eccentric phase of the countermovement jump.
Several devices are available to measure vertical jump (VJ) height based on flight time, VJ reach height, or ground reaction forces. The purpose of this study was to determine the accuracy of a VJ mat for measuring flight time and VJ height, compared to a VJ tester or a force plate. Seventeen men and 18 women (X±SD; age=20.9±0.7 yrs, hgt=176.1±0.9 cm, wgt=72.6±13.5 kg) served as subjects. Subjects performed counter-movement vertical jumps (CMVJ) while standing on both a force plate (1000 Hz), and a VJ mat. A Vertec VJ tester was used to measure jump reach. Compared to the force plate, the VJ mat reported greater VJ height (VJ mat = 0.50±0.12 m, force plate = 0.34±0.10 m) and flight time (VJ mat = 0.629±0.078 s, force plate = 0.524±0.077 s). Comparison of VJ heights from the VJ mat and the Vertec revealed no significant differences (Vertec = 0.48±0.11 m). Regression analyses indicated strong relationships between testing methods, and suggested high VJ performances may be underestimated with the VJ mat. This particular VJ mat compared favorably with the Vertec but not the force plate. It appears that the different flight times derived from the VJ mat may permit the VJ mat to be in closer agreement with VJ heights from the Vertec. Also, the VJ mat may not be an appropriate tool for assessing high VJ performances (i.e., ≥ 0.70 m; ≈ 28 in.). Practitioners and researchers using similar VJ mats may not obtain accurate flight times and may underestimate high performers.
Flight time is the most accurate and frequently used variable when assessing the height of vertical jumps. The purpose of this study was to analyze the validity and reliability of an alternative method (i.e., the HSC-Kinovea method) for measuring the flight time and height of vertical jumping using a low-cost, high-speed Casio-Exilim FH-25 camera (HSC). To this end, 25 subjects performed a total of 125 vertical jumps on an infrared (IR) platform while simultaneously being recorded with a HSC at 240 fps. Subsequently, two observers with no experience in video analysis analyzed the 125 videos independently using the open-license Kinovea 0.8.15 software. The flight times obtained were then converted into vertical jump heights and the intra-class correlation coefficient (ICC), Bland-Altman plot, and Pearson correlation coefficient calculated for those variables. The results showed a perfect correlation agreement (ICC=1, p<0.0001) between both observers' measurements of flight time and jump height and a highly reliable agreement (ICC=0.997, p<0.0001) between the observers' measurements of flight time and jump height using the HSC-Kinovea method and those obtained using the IR system, thus explaining 99.5% (p□0.0001) of the differences (shared variance) obtained using the IR platform. As a result, besides requiring no previous experience in the use of this technology the HSC-Kinovea method can be considered to provide similarly valid and reliable measurements of flight time and vertical jump height as more expensive equipment (i.e., IR). As such, coaches from many sports could use the HSC-Kinovea method to measure the flight time and height of their athletes' vertical jumps.
This paper shows experimentally that standard wireless networks which measure
received signal strength (RSS) can be used to reliably detect human breathing
and estimate the breathing rate, an application we call "BreathTaking". We show
that although an individual link cannot reliably detect breathing, the
collective spectral content of a network of devices reliably indicates the
presence and rate of breathing. We present a maximum likelihood estimator (MLE)
of breathing rate, amplitude, and phase, which uses the RSS data from many
links simultaneously. We show experimental results which demonstrate that
reliable detection and frequency estimation is possible with 30 seconds of
data, within 0.3 breaths per minute (bpm) RMS error. Use of directional
antennas is shown to improve robustness to motion near the network.
Physical activity and physical performance have been linked to fall risk in the elderly. The authors examined the relation
between physical activity and physical performance with incident falls in the Osteoporotic Fractures in Men Study, a large
prospective cohort study of 5,995 community-dwelling men in the United States at least 65 years of age. The authors also examined
what types of activities are associated with falling. Incident falls between 2000 and 2005 were captured from up to 17 triannual
follow-up questionnaires per participant and analyzed with generalized estimating equations. Follow-up averaged 4.5 years.
The average risk of falling in the first 4 months of follow-up was 6.6%. The most active quartile had a significantly greater
fall risk than did the least active quartile (relative risk = 1.18, 95% confidence interval (CI): 1.07, 1.29). Men with greater
leg power and grip strength had significantly reduced fall risk (for highest leg power quartile vs. lowest: relative risk
= 0.82, 95% CI: 0.73, 0.92; for highest grip strength quartile vs. lowest: relative risk = 0.76, 95% CI: 0.69, 0.85). Partitioning
components of activity showed no association between fall risk and leisure activities but a positive association with household
activities (for highest quartile vs.lowest: relative risk = 1.17, 95% CI: 1.07, 1.28).
Today, the term “wearable” goes beyond the traditional definition of clothing; it refers to an accessory that enables personalized mobile information processing. In this chapter, we define the concept of wearables, present their attributes, and discuss their role at the core of an ecosystem for harnessing big data. We, then present the taxonomy for wearables and trace their advancements over the years. We discuss the practical challenges associated with the use of wearables and propose the concept of a meta-wearable – in the form of a wearable motherboard – as a feasible solution. We gaze into the future of wearables and propose a transdisciplinary approach to realizing this future that will transform the field and contribute to enhancing the quality of life for everyone.
Recent advances in piezoresistive materials have opened the possibility of developing pressure sensitive flexible mats that cover large areas. They are composed of arrays of sensitive cells. However, in many configurations proposed in the literature, the measurement of a single cell does not recover the cell resistance itself but the equivalent resistance between the row and column conductive strips that select it. If this effect is not corrected, unloaded regions can appear with non negligible pressure, as a kind of ghost object. Diodes can be placed to overcome the problem, but this makes the fabrication more complex, especially for prototypes. In this paper, we propose a novel software solution based on a circuit analysis of the mat. The set of cell resistances is obtained from the set of equivalent resistances between row and columns. Several algorithms are compared. For simulated values of the array, the true cell resistance can be recovered with a great accuracy. A good compromise between execution speed and error is achieved by a Newton-Krylov nonlinear solver. Nevertheless, this algorithm presents convergence problems when facing values of a real mat. In this case a fixed-point formulation is more appropriate. For
arrays, it can achieve relative errors with a mean value of 0.0258 in less than 0.1 s running on a regular PC. The removal of ghost objects is also shown visually.
Vertical jump (VJ) height is a fundamental performance analysis parameter in several sports involving frequent jump-landing maneuvers such as netball. Recent studies have largely examined performance parameters associated with vertical jump height (VJH) in isolation from each other. This study presents an investigation into the relationship between integrated performance parameters (IPP) and VJH during single-leg (VJSL) and double-leg (VJDL) vertical jump tests. IPP considered include; electromyography (EMG) activity of eight lower extremity (LE) muscles, 3D Kinematics of the knee and ankle joints, body height (BH), reach height (RH), and Jump duration (JT). Thirteen healthy national female netball players participated in this study. Each subject performed VJSL and VJDL in three trials while simultaneously and synchronously recording their LE-EMG activity, 3D kinematics, and VJH in each jump trial. LE-EMG activity acquisition was through wirelessly transmitting BioRadio units (CleveMed Inc. USA), while 3D kinematics were obtained through a six-3D marker-based motion capture camera system (Qualisys Inc. Sweden). VJH reading was obtained from a vertec device (Power Systems Inc. USA). A total of 22 IPP were extracted from raw data of both VJSL tests (i.e VJSL Right-Leg (VJSLR), and VJSL Left-Leg (VJSLL)), while 44 IPP were extracted from raw data of VJDL. The relationship between the reduced datasets' parameters and response variable (VJH) was then modeled using Multilayer Perceptron Feed Forward Neural Networks (FFNNs). Significant features were further selected through stepwise regression analysis. Results showed that FFNNs trained with Scaled conjugate gradient back-propagation (SCG) algorithm achieved the best VJH prediction with accuracy of 97.39% for VJSLL, 94.52% for VJSLR, and of 96.74% for VJDL. These results demonstrate that the integration of 3D Kinematics and EMG using wearable sensors interfaced with motion capture system for IPP, has led to more accurate prediction of VJH. Thus, this serves as quantifiable feedback to coaches and players for performance enhancement as well as injury prevention in jump landing tasks investigated.
Fiber Bragg grating (FBG) sensors have gained popularity in medicine for some valuable features such as small size, immunity to electromagnetic interferences, and good metrological properties. Among several applications, this technology has been used in the analysis of gases in mechanical ventilation. In this field, in particular during invasive ventilation, the gas delivered by the ventilator must be warmed and humidified in order to reach the patients with optimal conditions (100% of relative humidity and 37 °C). The most popular device used to accomplish this task are the heated wire humidifiers (HWHs). Unfortunately, their performances are influenced by ventilatory settings (e.g., respiratory frequency) and environmental conditions. The aim of this work is to fabricate a probe based on FBG sensor able to monitor both the gas relative humidity and the respiratory frequency. These information can be used as a feedback to improve the performance of the HWHs. The probe consists of a needle which houses an FBG sensor coated by hygroscopic material (i.e., agar). This solution allows an easy insertion of the probe within the ducts connecting the ventilator to the patient. The proposed system has been assessed during mechanical ventilation at different respiratory frequency. Future testing will be focused on the development of a system able to monitor other parameters that influence the HWHs performances (e.g., gas temperature, minute volume). IEEE
Given the difficulty of invasive methods to assess muscle action during natural human movement, surface electromyography (sEMG) has been increasingly used to capture muscle activity in relation to kinesiological analysis of specific tasks. Isolated isometric, concentric and eccentric forms of muscle action have been receiving the most attention for research purposes. Nevertheless natural muscle action frequently involves the use of a preceding eccentric muscle action as a form of potentiation of immediate muscle concentric action, in what is designated as muscle stretch-shortening cycle (SSC). The most frequently applied protocols for the evaluation of SSC on vertical jumps are by virtue of their reproducibility and control of experimental conditions, squat jump (SJ) without countermovement (CM), countermovement jump (CMJ) with long CM and drop jump (DJ) with short CM. The methods used to extract information and relationship of the captured signals also present a high diversity, with the question about the consistency of the methods and obtained results. The objective of this study is to evaluate the consistency of the analysis and results by applying different EMGs signal analysis techniques related to strategic muscle groups of the lower limbs at different countermovement evaluated in vertical jumps. Raw sEMG signals of 5 lower limb muscles of 6 subjects during SJ, CMJ and DJ were rectified, filtered and obtained their envelope, and then correlated (CR) for detection of synergistic, agonist and antagonist activity, applied principal component analysis (PCA) for the detection of uncorrelated components explaining maximum variability and normalized cross-correlation (CCRN) for detection of maximum correlations and time lag. CR of EMG envelopes presented higher coactivities (CoA) in DJ relative to SJ and these CoA superior to CMJ with greater synergy in DJ relative to SJ and CMJ that present several loop cycles corresponding to time lag of activity. CCRN of the EMG envelopes presented also higher CoA in DJ when compared to SJ and both higher CoA to CMJ. PCA allowed to detect a principal component (PC) explaining 92.2% of the variability of EMG in DJ, 90.6% in SJ and 78.7% in CMJ, the second PC responsible for the explanation of 4.9% variability in DJ, 6.7% in SJ and 15.3% in CMJ.
The physical challenges of human development reflected in the sport are increasingly technology-related. This relationship can be demonstrated in several lines; design on sports elements using high technology as well as sports analysis systems that trying to enhance technical indicators in every discipline. The analysis systems facilitate the feedback process to coaches and athletes, based on mathematical models using derived measures, avoiding precision errors of human observations. One meaningful measure for coaches, strength and conditioning professionals, and sport professionals in general is the vertical jump height. In this paper the initial development of a vertical jump height measurement system is presented, that allows to know the flight height of a person in the development of exercise, and his flight time. The system relies on information from an Inertial Measurement Unit (IMU) consisting of an triaxial accelerometer, a triaxial gyroscope and a triaxial magnetometer and two pressure sensors that fuse the jump measured data. The equipment is completely portable and wireless allowing measurements under standard conditions and these can be developed at the same time with the sporting activity. In average were obtained a flight time of 0.4720s and a maximum height of 0.3160m. The results evidence that these systems based on initiatives of low-cost national technology can be at the level of the products used commercially. Finally, it is important to note that the development of these devices can be complemented with specific applications that automatically process data to support the practice of sports.
This paper proposes accurate respiratory rate estimation using nasal breath sound recordings from a smartphone. Specifically, the proposed method detects nasal airflow using a built-in smartphone microphone or a headset microphone placed underneath the nose. In addition, we also examined if tracheal breath sounds recorded by the built-in microphone of a smartphone placed on the paralaryngeal space can also be used to estimate different respiratory rates ranging from as low as 6 breaths/min to as high as 90 breaths/min. The true breathing rates were measured using inductance plethysmography bands placed around the chest and the abdomen of the subject. Inspiration and expiration were detected by averaging the power of nasal breath sounds. We investigated the suitability of using the smartphone-acquired breath sounds for respiratory rate estimation using two different spectral analyses of the sound envelope signals: the Welch periodogram and the autoregressive spectrum. To evaluate the performance of the proposed methods, data were collected from 10 healthy subjects. For the breathing range studied (6-90 breaths/min), experimental results showed that our approach achieves an excellent performance accuracy for the nasal sound as the median errors were less than 1% for all breathing ranges. The tracheal sound, however, resulted in poor estimates of the respiratory rates using either spectral method. For both nasal and tracheal sounds, significant estimation outliers resulted for high breathing rates when subjects had nasal congestion, which often resulted in the doubling of the respiratory rates. Finally, we show that respiratory rates from the nasal sound can be accurately estimated even if a smartphone?s microphone is as far as 30 cm away from the nose.
The primary aim of this study was to determine reliability and factorial validity of squat (SJ) and countermovement jump (CMJ) tests. The secondary aim was to compare 3 popular methods for the estimation of vertical jumping height. Physical education students (n = 93) performed 7 explosive power tests: 5 different vertical jumps (Sargent jump, Abalakow's jump with arm swing and without arm swing, SJ, and CMJ) and 2 horizontal jumps (standing long jump and standing triple jump). The greatest reliability among all jumping tests (Cronbach's alpha = 0.97 and 0.98) had SJ and CMJ. The reliability alpha coefficients for other jumps were also high and varied between 0.93 and 0.96. Within-subject variation (CV) in jumping tests ranged between 2.4 and 4.6%, the values being lowest in both horizontal jumps and CMJ. Factor analysis resulted in the extraction of only 1 significant principal component, which explained 66.43% of the variance of all 7 jumping tests. Since all jumping tests had high correlation coefficients with the principal component (r = 0.76-0.87), it was interpreted as the explosive power factor. The CMJ test showed the highest relationship with the explosive power factor (r = 0.87), that is, the greatest factorial validity. Other jumping tests had lower but relatively homogeneous correlation with the explosive power factor extracted. Based on the results of this study, it can be concluded that CMJ and SJ, measured by means of contact mat and digital timer, are the most reliable and valid field tests for the estimation of explosive power of the lower limbs in physically active men.
Integration of a low-cost global positioning system (GPS) with a microelectromechanical system-based inertial measurement unit (MEMS-IMU) is a widely used method that takes advantage of the individual superiority of each system to get a more accurate and robust navigation performance. However, because of poor observations as well as multipath effects, the GPS has low accuracy in the vertical direction. As a result, the navigation accuracy even in an integrated GPS/MEMS-IMU system is more challenged in the vertical direction than the horizontal direction. To overcome this problem, this paper investigates the integration of a MEMS barometric pressure sensor with the MEMS-IMU for vertical position/velocity tracking without the GPS that has applications in sports. A cascaded two-step Kalman filter consisting of separate orientation and position/velocity subsystems is proposed for this integration. Slow human movements in addition to more rapid sport activities such as vertical and step-down jumps can be tracked using the proposed algorithm. The height-tracking performance is benchmarked against a reference camera-based motion-tracking system and an error analysis is performed. The experimental results show that the vertical trajectory tracking error is less than 28.1 cm. For the determination of jump vertical height/drop, the proposed algorithm has an error of less than 5.8 cm.
The purpose of this study was to compare three methods to assess vertical jump height, to determine their limitations and to propose solutions to mitigate their effects. The chosen methods were the contact mat, the optical system and the Sargent jump. The testing environment was designed such that all three systems simultaneously measured the vertical jump height. A total of 41 kinesiology students (18 women, 23 men, mean age 23·2 ± 4·5 years) participated in this study. Data show that the contact mat and the optical system essentially provide similar results (P = 0·912) and that the correlation coefficient between the two systems was 0·972 (r(2) = 0·944). However, it was found that the Sargent jump has a tendency to overestimate the height, providing a measurement that is significantly different from the other two methods as the jumps are higher than 30·64 cm (P = 0·044). Through the design of the experiment, several sources of errors were identified and mathematically modelled. These sources include optical sensor placement, flat-footed landing and hip/knee bend. Whenever possible, the errors were quantified and solutions were proposed.
A wireless portable monitoring system for respiratory diseases using microsensors is proposed. The monitoring system consists of two sensor nodes integrating with Bluetooth transmitters that measure user's respiratory airflow, blood oxygen saturation, and body posture. The utility of micro-hot-film flow sensor makes the monitor can acquire comprehensive respiration parameters which are useful for diagnoses of obstructive sleep apnea, chronic obstructive pulmonary disease, and asthma. The system can serve as both sleep recorder and spirometer. Additionally, a mobile phone or a PC connected to the Internet serving as a monitoring and transfer terminal makes telemedicine achievable. Several experiments were conducted to verify the feasibility and effectiveness of the proposed system for monitoring and diagnosing OSA, COPD, and asthma.
Simultaneous monitoring of respiratory function and activity level would be of benefit in the monitoring of chronic conditions such as chronic obstructive pulmonary disorder (COPD), but is ill-addressed by existing methods. Current solutions for monitoring respiratory function are obtrusive and not suitable for pervasive monitoring in the home, while existing activity monitors, not equipped to measure parameters of respiration, do not differentiate between causes of sedentary behaviour. Previous work has validated a method for obtaining angular rates of breathing motion of the chest wall using a tri-axial accelerometer against nasal pressure. We have used this method to perform respiratory monitoring during periods of low activity while simultaneously monitoring activity using a single wireless device. We observe that the optimal placement for respiratory monitoring does not preclude successful activity monitoring. We propose an activity monitoring algorithm based on direct estimation of motion energy observed by the device. We show favourable comparison against three commercial activity monitors validated against indirect calorimetry during a programme of exercise activities in healthy subjects.
The aim of this work is to show, to which the swings of arms are applied, is effective to perform vertical jumping movements by using a dynamometric platform. The force plate's analog to digital convector and range amplifier was electronically zeroed and calibrated prior to each subject's. In this paper two vertical jumping can be performed with and without an arm swing. The reported data and signals were obtained from an athlete who is familiar with performing a correct jump. The best jumping recording by the force platform are presented. Consequently, it is concluded that the swings of arms contribute to high-performance jumping movements.
Please don't be shy about sending even vague pointers to people who may have complete or partial resolutions of the problems mentioned in any of the open questions columns that have appeared as earlier complexity theory columns. Though I don't give a ...
The purpose of this investigation was to assess the intrasession and intersession reliability of the Vertec, Just Jump System, and Myotest for measuring countermovement vertical jump (CMJ) height. Forty male and 39 female university students completed 3 maximal-effort CMJs during 2 testing sessions, which were separated by 24-48 hours. The height of the CMJ was measured from all 3 devices simultaneously. Systematic error, relative reliability, absolute reliability, and heteroscedasticity were assessed for each device. Systematic error across the 3 CMJ trials was observed within both sessions for males and females, and this was most frequently observed when the CMJ height was measured by the Vertec. No systematic error was discovered across the 2 testing sessions when the maximum CMJ heights from the 2 sessions were compared. In males, the Myotest demonstrated the best intrasession reliability (intraclass correlation coefficient [ICC] = 0.95; SEM = 1.5 cm; coefficient of variation [CV] = 3.3%) and intersession reliability (ICC = 0.88; SEM = 2.4 cm; CV = 5.3%; limits of agreement = -0.08 ± 4.06 cm). Similarly, in females, the Myotest demonstrated the best intrasession reliability (ICC = 0.91; SEM = 1.4 cm; CV = 4.5%) and intersession reliability (ICC = 0.92; SEM = 1.3 cm; CV = 4.1%; limits of agreement = 0.33 ± 3.53 cm). Additional analysis revealed that heteroscedasticity was present in the CMJ when measured from all 3 devices, indicating that better jumpers demonstrate greater fluctuations in CMJ scores across testing sessions. To attain reliable CMJ height measurements, practitioners are encouraged to familiarize athletes with the CMJ technique and then allow the athletes to complete numerous repetitions until performance plateaus, particularly if the Vertec is being used.
The objectives of this study were (a) to determine the concurrent validity of the flight time(FT) and double integration of vertical reaction force (DIF) methods in the estimation of vertical jump height with the video method (VID) as reference; (b) to verify the degree of agreement among the 3 methods; (c) to propose regression equations to predict the jump height using the FT and DIF. Twenty healthy male and female nonathlete college students participated in this study. The experiment involved positioning a contact mat (CTM) on the force platform (FP), with a video camera 3 m from the FP and perpendicular to the sagittal plane of the subject being assessed. Each participant performed 15 countermovement jumps with 60-second intervals between the trials. Significant differences were found between the jump height obtained by VID and the results with FT (p # 0.01) and DIF (p # 0.01), showing that the methods are not valid. Additionally, the DIF showed a greater degree of agreement with the reference method than the FT did, and both presented a systematic error. From the linear regression test was determined the prediction equations with a high degree of linearity between the methods VID vs. DIF (R2 = 0.988) and VID vs. FT (R2 = 0.979). Therefore, the prediction equations suggested may allow coaches to measure the vertical jump performance of athletes by the FTand DIF, using a CTM or an FP, which represents more practical and viable approaches in the sports field; comparisons can then be made with the results of other athletes evaluated by VID.
The aim of the present study was to verify the validity and reliability of the Myotest accelerometric system (Myotest SA, Sion, Switzerland) for the assessment of vertical jump height. Forty-four male basketball players (age range: 9-25 years) performed series of squat, countermovement and repeated jumps during 2 identical test sessions separated by 2-15 days. Flight height was simultaneously quantified with the Myotest system and validated photoelectric cells (Optojump). Two calculation methods were used to estimate the jump height from Myotest recordings: flight time (Myotest-T) and vertical takeoff velocity (Myotest-V). Concurrent validity was investigated comparing Myotest-T and Myotest-V to the criterion method (Optojump), and test-retest reliability was also examined. As regards validity, Myotest-T overestimated jumping height compared to Optojump (p < 0.001) with a systematic bias of approximately 7 cm, even though random errors were low (2.7 cm) and intraclass correlation coefficients (ICCs) where high (>0.98), that is, excellent validity. Myotest-V overestimated jumping height compared to Optojump (p < 0.001), with high random errors (>12 cm), high limits of agreement ratios (>36%), and low ICCs (<0.75), that is, poor validity. As regards reliability, Myotest-T showed high ICCs (range: 0.92-0.96), whereas Myotest-V showed low ICCs (range: 0.56-0.89), and high random errors (>9 cm). In conclusion, Myotest-T is a valid and reliable method for the assessment of vertical jump height, and its use is legitimate for field-based evaluations, whereas Myotest-V is neither valid nor reliable.
Sleep disordered breathing (SDB), i.e., obstructive, central or mixed sleep apneas, has been recognized as a common occurrence in the elderly. Aging is per se associated with a decrease in the quality of sleep; SDB may further disrupt the sleep architecture in older subjects. The prevalence of obstructive sleep apnea (OSA) increases with aging; available studies report prevalence rates of 11-62%. Furthermore, OSA has been associated with increased mortality in older adults. Central apneas and periodic breathing occur with increased frequency either in subjects with neurological disorders such as infarction, tumor, sequelae of infection, diffuse encephalopathies, or in chronic heart failure. Patients with cerebrovascular disease (stroke, or transient ischemic attacks) have a markedly high prevalence of SDB, mainly OSA. In these patients, SDB is associated with a poorer functional prognosis at 3 and 12 months after the acute event, and a higher mortality. The clinical impact of SDB on cognitive function appears to be modest in patients without dementia, although there is a moderate increase in daytime sleepiness. In Alzheimer's disease (AD) however, SDB occurs more frequently than in non-demented older subjects, and its severity is correlated with the degree of cognitive impairment. The hypothesis of a causal relationship between AD and SDB remains a subject of controversy. The possibility of SDB should be considered in the elderly in the differential diagnosis of "reversible dementias", increased daytime sleepiness, or unexplained right-sided heart failure.
The primary aim of this study was to determine reliability and factorial validity of squat (SJ) and countermovement jump (CMJ) tests. The secondary aim was to compare 3 popular methods for the estimation of vertical jumping height. Physical education students (n = 93) performed 7 explosive power tests: 5 different vertical jumps (Sargent jump, Abalakow's jump with arm swing and without arm swing, SJ, and CMJ) and 2 horizontal jumps (standing long jump and standing triple jump). The greatest reliability among all jumping tests (Cronbach's alpha = 0.97 and 0.98) had SJ and CMJ. The reliability alpha coefficients for other jumps were also high and varied between 0.93 and 0.96. Within-subject variation (CV) in jumping tests ranged between 2.4 and 4.6%, the values being lowest in both horizontal jumps and CMJ. Factor analysis resulted in the extraction of only 1 significant principal component, which explained 66.43% of the variance of all 7 jumping tests. Since all jumping tests had high correlation coefficients with the principal component (r = 0.76-0.87), it was interpreted as the explosive power factor. The CMJ test showed the highest relationship with the explosive power factor (r = 0.87), that is, the greatest factorial validity. Other jumping tests had lower but relatively homogeneous correlation with the explosive power factor extracted. Based on the results of this study, it can be concluded that CMJ and SJ, measured by means of contact mat and digital timer, are the most reliable and valid field tests for the estimation of explosive power of the lower limbs in physically active men.
Vertical jump height is frequently used by coaches, health care professionals, and strength and conditioning professionals to objectively measure function. The purpose of this study is to determine the concurrent validity of the jump and reach method (Vertec) and the contact mat method (Just Jump) in assessing vertical jump height when compared with the criterion reference 3-camera motion analysis system. Thirty-nine college students, 25 females and 14 males between the ages of 18 and 25 (mean age 20.65 years), were instructed to perform the countermovement jump. Reflective markers were placed at the base of the individual's sacrum for the 3-camera motion analysis system to measure vertical jump height. The subject was then instructed to stand on the Just Jump mat beneath the Vertec and perform the jump. Measurements were recorded from each of the 3 systems simultaneously for each jump. The Pearson r statistic between the video and the jump and reach (Vertec) was 0.906. The Pearson r between the video and contact mat (Just Jump) was 0.967. Both correlations were significant at the 0.01 level. Analysis of variance showed a significant difference among the 3 means F(2,235) = 5.51, p < 0.05. The post hoc analysis showed a significant difference between the criterion reference (M = 0.4369 m) and the Vertec (M = 0.3937 m, p = 0.005) but not between the criterion reference and the Just Jump system (M = 0.4420 m, p = 0.972). The Just Jump method of measuring vertical jump height is a valid measure when compared with the 3-camera system. The Vertec was found to have a high correlation with the criterion reference, but the mean differed significantly. This study indicates that a higher degree of confidence is warranted when comparing Just Jump results with a 3-camera system study.
Fiber bragg grating probe for relative humidity and respiratory frequency estimation: assessment during mechanical ventilation
- C Massaroni
- D L Presti
- P Saccomandi
- M A Caponero
- R Damato
- E Schena
Contribución al diseño de sensores vestibles y ambientales para medir la respiración y el salto vertical en adultos mayores y frágiles
- E A V Vásquez
Delmar's comprehensive medical assisting: administrative and clinical competencies
- W Q Lindh
- M Pooler
- C D Tamparo
- B M Dahl
- J Morris
Ganong's review of medical physiology twenty
- K E Barrett
- S Boitano
- S M Barman
- H L Brooks
Breathing data from a piezoresistive breathing sensor
- E Vanegas
- R Igual
- I Plaza