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Background: Most current measures of Huntington's disease (HD) motor symptoms are subjective, categorical, and limited to in-person visits. Wearable sensors enable objective, frequent, and remote data collection in real-world settings. However, longitudinal sensor studies in HD are lacking., Objective: To measure motor symptoms of HD using wearable sensors in a longitudinal study., Methods: Participants with HD, prodromal HD, and without a movement disorder wore five accelerometers, one on each limb and on the trunk, at up to four clinic visits over one year. After each visit, participants wore the sensors at home for two days. Based on the accelerometer data from the trunk, we calculated a "truncal Chorea Index" for periods when the participant was sitting. We also measured gait parameters and activity profiles. To measure group differences, track progression, and observe individual variability, statistical analysis of the data was conducted using a linear mixed-effects model., Results: Fifteen individuals with HD, five with prodromal HD, and 19 controls were enrolled. The average truncal Chorea Index was higher in individuals with HD (26.6, p < 0.001) than in controls (15.6). For participants with HD, the truncal Chorea Index showed a high intra-day variability but minimal change over 12 months. Individuals with HD walked less (HD = 3818, prodromal HD = 6957, controls = 5514 steps/day) and took longer duration steps (HD = 0.97, prodromal HD = 0.78, controls = 0.85 seconds/step) than the other groups. Individuals with HD spent over half their day lying down (HD = 51.1%, prodromal HD = 38.0%, controls = 37.1%)., Conclusions: A novel truncal Chorea Index can assess truncal chorea at home, finds substantial variability, and suggests that truncal chorea may be present in prodromal HD. Individuals with HD walk less and slower and spend more time lying down than controls. These findings require additional investigation, could inform clinical care, and could be used to evaluate new therapies.

Jump performance provides meaningful information both for sporting and clinical needs. Current state of the art in jump performance assessment is laboratory-bound; however, out-of-the-laboratory methods are desirable. Therefore, the purposes of the present investigation were (a) to explore whether utilizing a novel analytical approach minimizes the bias between inertial recording unit (IMU)-based and jump mat-based jump height estimates and (b) to provide a thorough tutorial for a sport scientist (see Appendix S1) to facilitate standardization of jump height estimation. Forty-one women, men, and boys aged 6 to 77 years completed three maximal countermovement jumps without arm swing, which were concurrently registered with a jump mat, and an IMU worn in low lumbar region. Excellent agreement between the novel IMU-based jump height and jump mat jump height was observed (mean IMU 22.6 [8.3] cm, mean jump mat 22.7 [8.9], mean bias -0.1 cm [95% limits of agreement -4.5 cm to 4.4 cm; P = .826], and intra-class correlation coefficient 0.97 [95% CI 0.94 to 0.98, P < .001]). In conclusion, inertial recordings conducted with lightweight IMUs worn on the hip provide a valid and feasible assessment of jump height among people with varying athletic ability. Inertial signals have the potential to afford (at least semi-) automated analysis pipeline with low labor cost thus being potentially feasible in applied settings such as in professional sports or in the clinics., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

We have recently demonstrated that accelerometer-based pump thrombosis and thromboembolic events detection is feasible in vitro. This article focuses on detection of these conditions in vivo. In an open-chest porcine model (n = 7), an accelerometer was attached to the pump casing of an implanted HeartWare HVAD. Pump vibration was analyzed by Fast Fourier Transform of the accelerometer signals, and the spectrogram third harmonic amplitude quantified and compared with pump power. Interventions included injection of thrombi into the left atrium (sized 0.3-0.4 ml, total n = 35) and control interventions; pump speed change, graft obstruction, and saline bolus injections (total n = 47). Graft flow to cardiac output ratio was used to estimate the expected number of thrombi passing through the pump. Sensitivity/specificity was assessed by receiver operating characteristic curve. Graft flow to cardiac output ratio averaged 66%. Twenty-six of 35 (74%) thrombi caused notable accelerometer signal change. Accelerometer third harmonic amplitude was significantly increased in thromboembolic interventions compared with control interventions, 64.5 (interquartile range [IQR]: 18.8-107.1) and 5.45 (IQR: 4.2-6.6), respectively (p < 0.01). The corresponding difference in pump power was 3 W (IQR: 2.9-3.3) and 2.8 W (IQR: 2.4-2.9), respectively (p < 0.01). Sensitivity/specificity of the accelerometer and pump power to detect thromboembolic events was 0.74/1.00 (area under the curve [AUC]: 0.956) and 0.40/1.00 (AUC: 0.759), respectively. Persistent high third harmonic amplitude was evident at end of all experiments, and pump thrombosis was confirmed by visual inspection. The findings demonstrate that accelerometer-based detection of thromboembolic events and pump thrombosis is feasible in vivo and that the method is superior to detection based on pump power.

Purpose: (i) To develop an automated measurement technique for the assessment of both the form and intensity of physical activity undertaken by children during play. (ii) To profile the varying activity across a cohort of children using a multivariate analysis of their movement patterns., Methods: Ankle-worn accelerometers were used to record 40 min of activity during a school recess, for 24 children over five consecutive days. Activity events of 1.1 s duration were identified within the acceleration time trace and compared with a reference motif, consisting of a single walking stride acceleration trace, obtained on a treadmill operating at a speed of 4 km h. Dynamic time warping of motif and activity events provided metrics of comparative movement duration and intensity, which formed the data set for multivariate mapping of the cohort activity using a principal component analysis (PCA)., Results: The two-dimensional PCA plot provided clear differentiation of children displaying diverse activity profiles and clustering of those with similar movement patterns. The first component of the PCA correlated to the integrated intensity of movement over the 40-min period, whereas the second component informed on the temporal phasing of activity., Conclusions: By defining movement events and then quantifying them by reference to a motion-standard, meaningful assessment of highly varied activity within free play can be obtained. This allows detailed profiling of individual children's activity and provides an insight on social aspects of play through identification of matched activity time profiles for children participating in conjoined play.

Objective: Essential tremor (ET) prominently affects the upper-limbs during voluntary movements, but can also affect the lower-limbs, head, and chin. Although deep brain stimulation (DBS) of the ventral intermediate nucleus (VIM) of thalamus improves both clinical ratings and quantitative measures of tremor, no study has quantified effects of DBS on tremor across multiple body parts. Our objective was to quantify therapeutic effects of DBS across multiple body parts in ET., Methods: We performed quantitative assessment of tremor in ET patients who had DBS for at least one year. We assessed tremor on and off VIM-stimulation using triaxial accelerometers on the upper-limbs, lower-limbs, head and chin during seated and standing tasks., Results: VIM-DBS significantly reduced tremor, but there was no statistical difference in degree of tremor reduction across the measured effectors. Compared to healthy controls, ET patients treated with DBS showed significantly greater tremor power (4-8 Hz) across all effectors during seated and standing tasks., Conclusions: VIM-DBS reduced tremor in ET patients. There was no significant difference in the degree of tremor reduction across the measured effectors., Significance: This study provides new quantitative evidence that VIM-DBS is effective at reducing tremor across multiple parts of the body., (Copyright © 2019 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

The inclusion of a barometer in a wearable fall detector has been shown to improve the detection accuracy by measuring the altitude change associated with a fall event. However, the barometer is a power-hungry sensor, and the sensing power of barometer can be the dominant power consumption source in a wearable fall detector. In this study, we propose a triggering method that reduces barometer power consumption and prolongs the battery life. This approach utilizes a hermetically sealed and waterproof enclosure, with a small inlet covered by a semi-permeable membrane (SPM) to delay the time at which equilibrium between the internal and external pressures is reached, allowing the barometer to be woken from an idle low-power mode and capture the rising air pressure caused by the decrease in altitude during the fall. Two alternative signal processing methods were applied to the pressure waveform to detect the rising pressure pattern, a differential moving average filter (DMAF) and a Kalman filter (KF). The proposed fall detector was evaluated with data collected from a laboratory-based trial and a free-living trial, in which the barometric pressure data, recorded in open-air, were passed through a mathematical model of the leaky enclosure and the SPM assembly. The results show that the proposed fall detector with a 3.7 V, 140 mAh lithium-polymer battery provides a long battery life (DMAF 447 days, KF 444 days) while not compromising the sensitivity (DMAF 91.8%, KF 91.9%), specificity (DMAF 95.2% and KF 95.5%), or the false alarm rate (DMAF 0.035 alarms/hour and KF 0.064 alarms/hour).

Background: The relationship of training load to injury using wearable technology has not been investigated in professional American football players. The primary objective of this study was to determine the correlation between player workload and soft tissue injury over the course of a football season utilizing wearable global positioning system (GPS) technology., Hypothesis: Increased training load is associated with a higher incidence of soft tissue injuries., Study Design: Case-control study., Level of Evidence: Level 3., Methods: Player workloads were assessed during preseason and regular-season practice sessions using GPS tracking and triaxial accelerometry from 2014 to 2016. Soft tissue injuries were recorded during each season. Player workload during the week of injury (acute) and average weekly workload during the 4 weeks (chronic) prior to injury were determined for each injury and in uninjured position-matched controls during the same week. A matched-pairs t test was used to determine differences in player workload. Subgroup analysis was also conducted to determine whether observed effects were confounded by training period and type of injury., Results: In total, 136 lower extremity injuries were recorded. Of the recorded injuries, 101 injuries with complete GPS and clinical data were included in the analysis. Injuries were associated with greater increases in workload during the week of injury over the prior month when compared with uninjured controls. Injured players saw a 111% (95% CI, 66%-156%) increase in workload whereas uninjured players saw a 73% (95% CI, 34%-112%) increase in workload during the week of injury ( P = 0.032). Individuals who had an acute to chronic workload ratio higher than 1.6 were 1.5 times more likely to sustain an injury relative to time- and position-matched controls (64.6% vs 43.1%; P = 0.004)., Conclusion: Soft tissue injuries in professional football players were associated with sudden increases in training load over the course of a month. This effect seems to be especially pronounced during the preseason when player workloads are generally higher. These results suggest that a gradual increase of training intensity is a potential method to reduce the risk of soft tissue injury., Clinical Relevance: Preseason versus regular-season specific training programs monitored with wearable technology may assist team athletic training and medical staff in developing programs to optimize player performance.

Inertial measurement units have recently shown great potential for the accurate measurement of joint angle movements in replacement of motion capture systems. In the race towards long duration tracking, inertial measurement units increasingly aim to ensure portability and long battery life, allowing improved ecological studies. Their main advantage over laboratory grade equipment is their usability in a wider range of environment for greater ecological value. For accurate and useful measurements, these types of sensors require a robust orientation estimation that remains accurate over long periods of time. To this end, we developed the Allumo software for the preprocessing and calibration of the orientation estimate of triaxial accelerometers. This software has an automatic orientation calibration procedure, an automatic erroneous orientation-estimate detection and useful visualization to help process long and short measurement periods. These automatic procedures are detailed in this paper, and two case studies are presented to showcase the usefulness of the software. The Allumo software is open-source and available online.

Chronic obstructive pulmonary disease (COPD) claimed 3.0 million lives in 2016 and ranked 3rd among the top 10 global causes of death. Moreover, once diagnosed and discharged from the hospital, the 30-day readmission risk in COPD patients is found to be the highest among all chronic diseases. The existing diagnosis methods, such as Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2019, Body-mass index, airflow Obstruction, Dyspnea, and Exercise (BODE) index, modified Medical Research Council (mMRC), COPD assessment test (CAT), 6-minute walking distance, which are adopted currently by physicians cannot predict the potential readmission of COPD patients, especially within the 30 days after discharge from the hospital. In this paper, a statistical model was proposed to predict the readmission risk of COPD patients within 30-days by monitoring their physical activity (PA) in daily living with accelerometer-based wrist-worn wearable devices. This proposed model was based on our previously reported PA models for activity index (AI) and regularity index (RI) and it introduced a new parameter, quality of activity (QoA), which incorporates previously proposed parameters, such as AI and RI, with other activity-based indices to predict the readmission risk. Data were collected from continuous PA monitoring of 16 COPD patients after hospital discharge as test subjects and readmission prediction criteria were proposed, with a 63% sensitivity and a 37.78% positive prediction rate. Compared to other clinical assessment, diagnosis, and prevention methods, the proposed model showed significant improvement in predicting the 30-day readmission risk.

Study Objectives: Normal timing and duration of sleep is vital for all physical and mental health. However, many sleep-related studies depend on self-reported sleep measurements, which have limitations. This study aims to investigate the association of physical activity and sociodemographic characteristics including age, gender, coffee intake and social status with objective sleep measurements., Methods: A cross-sectional analysis was carried out on 82995 participants within the UK Biobank cohort. Sociodemographic and lifestyle information were collected through touch-screen questionnaires in 2007-2010. Sleep and physical activity parameters were later measured objectively using wrist-worn accelerometers in 2013-2015 (participants were aged 43-79 years and wore watches for 7 days). Participants were divided into 5 groups based on their objective sleep duration per night (<5 hours, 5-6 hours, 6-7 hours, 7-8 hours and >8 hours). Binary logistic models were adjusted for age, gender and Townsend Deprivation Index., Results: Participants who slept 6-7 hours/night were the most frequent (33.5%). Females had longer objective sleep duration than males. Short objective sleep duration (<6 hours) correlated with older age, social deprivation and high coffee intake. Finally, those who slept 6-7 hours/night were most physically active., Conclusions: Objectively determined short sleep duration was associated with male gender, older age, low social status and high coffee intake. An inverse 'U-shaped' relationship between sleep duration and physical activity was also established. Optimal sleep duration for health in those over 60 may therefore be shorter than younger groups., Competing Interests: The authors have declared that no competing interests exist.

Stroke is a cerebral artery disease that negatively affects activities of daily living (ADLs) and quality of life (QoL). Smartphones have demonstrated strong potential in assessing balance performance. However, such smartphone-based tools have thus far not been applied to stroke survivors. The purpose of this study was to develop a smartphone-based balance assessment system for subjects who have experienced strokes and evaluate the system feasibility. The smartphone-based balance assessment application was developed with Android Studio, and reliability and validity tests were conducted. The smartphone was used to record data using a built-in accelerometer and gyroscope, and increased changes represented greater instability. Six postures were tested for 30 s each. Ten healthy adults were recruited in the reliability test, and the intraclass correlation coefficient (ICC) was used to analyze the within-day and between-day reliabilities. Eight subjects with chronic stroke and eight healthy adults were recruited for the validity test, in which balance performance was compared to represent the application validity. The ICC values of the reliability tests were at least 0.76 ( p = 0.00). The acceleration data exhibited no difference between individuals who have experienced stroke and healthy subjects; however, all six postures were found to differ significantly between the two groups in the gyroscope data. The study demonstrates that the smartphone application provides a convenient, reliable, and valid tool for the balance assessments of subjects who have experienced chronic stroke.

Inertial measurement units (IMUs) allow accurate quantification of gait impairment of people with multiple sclerosis (pwMS). Nonetheless, it is not clear how IMU-based metrics might be influenced by pragmatic aspects associated with clinical translation of this approach, such as data collection settings and gait protocols. In this study, we hypothesised that these aspects do not significantly alter those characteristics of gait that are more related to quality and energetic efficiency and are quantifiable via acceleration related metrics, such as intensity, smoothness, stability, symmetry, and regularity. To test this hypothesis, we compared 33 IMU-based metrics extracted from data, retrospectively collected by two independent centres on two matched cohorts of pwMS. As a worst-case scenario, a walking test was performed in the two centres at a different speed along corridors of different lengths, using different IMU systems, which were also positioned differently. The results showed that the majority of the temporal metrics (9 out of 12) exhibited significant between-centre differences. Conversely, the between-centre differences in the gait quality metrics were small and comparable to those associated with a test-retest analysis under equivalent conditions. Therefore, the gait quality metrics are promising candidates for reliable multi-centric studies aiming at assessing rehabilitation interventions within a routine clinical context.

Inertial sensors are a useful instrument for long term monitoring in healthcare. In many cases, inertial sensor devices can be worn as an accessory or integrated into smart textiles. In some situations, it may be beneficial to have data from multiple inertial sensors, rather than relying on a single worn sensor, since this may increase the accuracy of the analysis and better tolerate sensor errors. Integrating multiple sensors into clothing improves the feasibility and practicality of wearing multiple devices every day, in approximately the same location, with less likelihood of incorrect sensor orientation. To facilitate this, the current work investigates the consequences of attaching lightweight sensors to loose clothes. The intention of this paper is to discuss how data from these clothing sensors compare with similarly placed body worn sensors, with additional consideration of the resulting effects on activity recognition. This study compares the similarity between the two signals (body worn and clothing), collected from three different clothing types (slacks, pencil skirt and loose frock), across multiple daily activities (walking, running, sitting, and riding a bus) by calculating correlation coefficients for each sensor pair. Even though the two data streams are clearly different from each other, the results indicate that there is good potential of achieving high classification accuracy when using inertial sensors in clothing.

In this work, authors address workload computation combining human activity recognition and heart rate measurements to establish a scalable framework for health at work and fitness-related applications. The proposed architecture consists of two wearable sensors: one for motion, and another for heart rate. The system employs machine learning algorithms to determine the activity performed by a user, and takes a concept from ergonomics, the Frimat's score, to compute the corresponding physical workload from measured heart rate values providing in addition a qualitative description of the workload. A random forest activity classifier is trained and validated with data from nine subjects, achieving an accuracy of 97.5%. Then, tests with 20 subjects show the reliability of the activity classifier, which keeps an accuracy up to 92% during real-time testing. Additionally, a single-subject twenty-day physical workload tracking case study evinces the system capabilities to detect body adaptation to a custom exercise routine. The proposed system enables remote and multi-user workload monitoring, which facilitates the job for experts in ergonomics and workplace health.

Background: Patients suffering from cerebellar ataxia have extremely variable gait kinematic features. We investigated whether and how wearable inertial sensors can describe the gait kinematic features among ataxic patients., Methods: We enrolled 17 patients and 16 matched control subjects. We acquired data by means of an inertial sensor attached to an ergonomic belt around pelvis, which was connected to a portable computer via Bluetooth. Recordings of all the patients were obtained during overground walking. From the accelerometric data, we obtained the harmonic ratio (HR), i.e., a measure of the acceleration patterns, smoothness and rhythm, and the step length coefficient of variation (CV), which evaluates the variability of the gait cycle., Results: Compared to controls, patients had a lower HR, meaning a less harmonic and rhythmic acceleration pattern of the trunk, and a higher step length CV, indicating a more variable step length. Both HR and step length CV showed a high effect size in distinguishing patients and controls (p < 0.001 and p = 0.011, respectively). A positive correlation was found between the step length CV and both the number of falls (R = 0.672; p = 0.003) and the clinical severity (ICARS: R = 0.494; p = 0.044; SARA: R = 0.680; p = 0.003)., Conclusion: These findings demonstrate that the use of inertial sensors is effective in evaluating gait and balance impairment among ataxic patients.

Introduction: Surveillance of physical activity at the population level increases the knowledge on levels and trends of physical activity, which may support public health initiatives to promote physical activity. Physical activity assessed by accelerometry is challenged by varying data processing procedures, which influences the outcome. We aimed to describe the levels and prevalence estimates of physical activity, and to examine how triaxial and uniaxial accelerometry data influences these estimates, in a large population-based cohort of Norwegian adults., Methods: This cross-sectional study included 5918 women and men aged 40-84 years who participated in the seventh wave of the Tromsø Study (2015-16). The participants wore an ActiGraph wGT3X-BT accelerometer attached to the hip for 24 hours per day over seven consecutive days. Accelerometry variables were expressed as volume (counts·minute-1 and steps·day-1) and as minutes per day in sedentary, light physical activity and moderate and vigorous physical activity (MVPA)., Results: From triaxial accelerometry data, 22% (95% confidence interval (CI): 21-23%) of the participants fulfilled the current global recommendations for physical activity (≥150 minutes of MVPA per week in ≥10-minute bouts), while 70% (95% CI: 69-71%) accumulated ≥150 minutes of non-bouted MVPA per week. When analysing uniaxial data, 18% fulfilled the current recommendations (i.e. 20% difference compared with triaxial data), and 55% (95% CI: 53-56%) accumulated ≥150 minutes of non-bouted MVPA per week. We observed approximately 100 less minutes of sedentary time and 90 minutes more of light physical activity from triaxial data compared with uniaxial data (p<0.001)., Conclusion: The prevalence estimates of sufficiently active adults and elderly are more than three times higher (22% vs. 70%) when comparing triaxial bouted and non-bouted MVPA. Physical activity estimates are highly dependent on accelerometry data processing criteria and on different definitions of physical activity recommendations, which may influence prevalence estimates and tracking of physical activity patterns over time., Competing Interests: The authors declare no competing interests.

This study aimed to assess the ability of the activPAL Ⓡ monitor (commonly used for measuring Sedentary Behaviour (SB), sitting or reclining with low energy expenditure while awake) to measure moderate to vigorous physical activity (MVPA), by assessing its agreement with the concurrent measurement by ActiGraph Ⓡ monitor (commonly used for measuring MVPA) to identify if a single monitor could be used to measure both MVPA and SB. A convenience sample of 24 adults (79% female; aged 23-60) wore an ActiGraph Ⓡ GT3X+ and an activPAL3 Ⓡ concurrently for one day during free-living activities. Time spent in MVPA was calculated as an outcome measure using published methods (ActiGraph Ⓡ , n = 6; activPAL Ⓡ n = 4). Agreement was assessed between pairs of outcomes using the Bland & Altman method. Participants engaged in between 60 and 145 min of MVPA. The activPAL Ⓡ method summing time walking with a cadence ≥100 steps/min underestimated MVPA compared with the ActiGraph Ⓡ but had the lowest aggregate bias (-16 min). Other activPAL Ⓡ methods, based on acceleration counts and the embedded MET algorithm, overestimated MVPA compared to the ActiGraph Ⓡ . The study was limited by the lack of activPAL Ⓡ acceleration count methods developed for adults. With the recommended methods, the activPAL Ⓡ could be suitable for use as a single monitor to measure both SB and MVPA., (Copyright © 2019. Published by Elsevier Ltd.)

Background: Accelerometers are accurate tools to assess movement and physical activity. However, interpreting standardly used outputs is not straightforward for populations with impaired mobility. Methods: The applicability of GENEActiv was explored in a group of 30 participants with myotonic dystrophy and compared to a group of 14 healthy-controls. All participants performed a set of tests while wearing four different accelerometers (wrists and ankles): [1] standing still; [2] ten-meters walk test; [3] six-minutes walking test; and, [4] ten-meters walk/run test. Results: Relevant findings were: [1] high intra-accelerometer reliability (i.e. 0.97 to 0.99; p  < 0.001); [2] each test acceleration values differ significantly between each other; [3] no inter-accelerometer reliability between wrist-worn devices and ankle-worn; and [4] a significant difference between the myotonic dystrophy group and the healthy-controls detectable at each test (i.e. Left-ankle values at six-minutes walking test: 48±17 for the myotonic dystrophy group, vs, 74±16 for the healthy-controls; p  < 0.001). Conclusions: GENEActiv demonstrated to be valid and reliable, capable of detecting walking periods and discriminating different speeds. However, inter-accelerometer reliability only applied when comparing opposite sides of the same limb. Specific movement characteristics of the myotonic dystrophy group were identified and muscle strength showed not to be a full determinant of limb acceleration.Implications for rehabilitationRehabilitation professionals in the field of neuromuscular disorders should be aware of the potential use of objective monitoring tools such as accelerometers whilst acknowledging the implications of assessing populations with altered movement patterns.Researchers should be cautious when translating accelerometry outputs previously validated in healthy populations to functionally impaired cohorts like myotonic dystrophy.Accelerometers can objectively expose movement disturbances allowing further investigations for the source of these disturbances.

Objective : To explore whether basketball player's self-determined motivation interacts with environmental contexts and coach training to influence percentage time in moderate-to-vigorous physical activity (%MVPA). Methods : A secondary analysis of data from 76 girls (mean ± SD, 10.5 ± 1.0 years) was conducted. Players were classified as high self-determined motivation (HSDM) or low self-determined motivation (LSDM) and randomised to trained (intervention) or untrained (control) coaches. Training included 2 workshops on strategies for activity-promoting practices. Girls were exposed to environmental contexts (practices and games) led by a trained/untrained coach (depending on arm) and one without coaches (free time) daily. Girls wore accelerometers each day. Using mixed random-effects models, the influence of motivation, context and training on %MVPA was analysed. Results : Trained coaches' practices were associated with the greatest %MVPA with no difference between HSDM and LSDM players (38.28 ± 1.77%; 37.64 ± 1.80%; p = 0.66). HSDM players had significantly greater %MVPA versus LSDM players during untrained coaches' practices (23.58 ± 1.77%; 20.51 ± 1.78%; p = 0.03). During games with trained coaches, HSDM players had greater %MVPA compared to LSDM players (23.79 ± 1.76%; 18.56 ± 1.74%; p < 0.001). No between-group difference in %MVPA during free time was found (12.85 ± 0.82%; 13.39 ± 0.84%; p = 0.64). Conclusion : The impact of individual differences in self-determined motivation on %MVPA during practices was attenuated when coaches were trained to implement activity-promoting practices.

Purpose : To compare children's energy expenditure (EE) levels during object projection skill performance (OPSP; e.g., kicking, throwing, striking) as assessed by hip- and wrist-worn accelerometers. Method : Forty-two children (female n = 20, M age = 8.1 ± 0.8 years) performed three, nine-minute sessions of kicking, over-arm throwing, and striking at performance intervals of 6, 12, and 30 seconds. EE was estimated using indirect calorimetry (COSMED k4b2) and accelerometers (ActiGraph GT3X+) worn on three different locations (hip, dominant-wrist, and non-dominant-wrist) using four commonly used cut-points. Bland-Altman plots were used to analyze the agreement in EE estimations between accelerometry and indirect calorimetry (METS). Chi-square goodness of fit tests were used to examine the agreement between accelerometry and indirect calorimetry. Results : Hip- and wrist-worn accelerometers underestimated EE, compared to indirect calorimetry, during all performance conditions. Skill practice at a rate of two trials per minute resulted in the equivalent of moderate PA and five trials per minute resulted in vigorous PA (as measured by indirect calorimetry), yet was only categorized as light and/or moderate activity by all measured forms of accelerometry. Conclusion : This is one of the first studies to evaluate the ability of hip- and wrist-worn accelerometers to predict PA intensity levels during OPSP in children. These data may significantly impact PA intervention measurement strategies by revealing the lack of validity in accelerometers to accurately predict PA levels during OPSP in children.

Objective: Measuring three-dimensional (3-D) foot trajectories with foot-worn inertial measurement units (IMUs) is essential for a variety of applications, such as gait analysis and fall risk assessment. IMU-based foot trajectory is usually reconstructed by double integrating the global coordinate acceleration, in which drifts of signals are accumulated and lead to unbounded error increase. To reduce drift errors, a smoother-based method is proposed in this paper., Methods: The smoother-based method not only corrects initial values of integrations, but also smooths integrating processes through a backward update. Both the orientation estimation and the velocity estimation are improved in this concept, which contribute to the improvement of the trajectory estimation., Results: The final results are compared with an optical motion capture system as reference. Accuracy is evaluated with ground level walking of nine adult participants, 2302 strides in total. Errors are reduced by 62% on stride length and 44% on stride width of the estimation without our method, with final errors [Formula: see text] and [Formula: see text]., Conclusion/significance: Results prove that our method can improve the accuracy of 3-D foot trajectory estimation. Furthermore, this smoother-based method can reduce drift-related errors when estimating trajectories, which will allow it to expand its applications into other IMU-based measurements.

Purpose : The purpose of this study was to examine whether structured physical activity (PA) in a family-based community exercise program affects PA of young children and parents. Method : Twenty-two children (mean ± SD; age, 4.9 ± 2.1 years) and their parents (age, 34.3 ± 7.6 years) participated in unstructured PA sessions followed by either short- or long-duration structured PA sessions, while wearing an ActiGraph GT9X activity monitor on their right hip to estimate PA. Independent t-tests compared children's and parents' PA during short- and long-structured PA sessions. Paired t-tests compared short- versus long-structured PA sessions. A mixed model ANOVA compared PA during unstructured versus structured sessions and between children and parents. Results : Children spent proportionately more time in moderate-to-vigorous PA (MVPA) and had higher accelerometer counts/min than parents during short-structured PA (children:60.9 ± 18.8% vs. parents:17.7 ± 6.8%, children:3870 ± 742 vs. parents:1836 ± 556 counts/min, p < .05) and long-structured PA (children:61.1 ± 20.1% vs. parents:12.6 ± 4.9%, children:3415 ± 758 vs. parents:1604 ± 633 counts/min, p < .05). No statistical differences were found between short- and long-structured PA sessions for proportion of time spent in MVPA or counts/min for children or parents (all, p > .05). Children spent proportionally more time in MVPA and had higher counts/min during unstructured PA compared to structured PA (unstructured MVPA:54.4 ± 3.9% vs. structured MVPA:38.2 ± 4.2%, unstructured counts/min:3830 ± 222 vs. structured counts/min:2768 ± 239 counts/min; p < .05). Conclusions : Children were more active than parents during both the unstructured and structured PA sessions. However, unstructured PA sessions resulted in 63-77% and 10-11% of PA recommendations for children and adults, respectively. Family-based exercise programming can provide an opportunity for children and their parents to attain MVPA during the week.

Wearables are receiving much attention from both epilepsy patients and treating physicians, for monitoring of seizure frequency and warning of seizures. They are also of interest for the detection of seizure-associated risks of patients, for differential diagnosis of rare seizure types and prediction of seizure-prone periods. Accelerometry, electromyography (EMG), heart rate and further autonomic parameters are recorded to capture clinical seizure manifestations. Currently, a clinical use to document nocturnal motor seizures is feasible. In this review the available devices, data on the performance in the documentation of seizures, current options for clinical use and developments in data analysis are presented and critically discussed.

The sliding window technique is widely used to segment inertial sensor signals, i.e., accelerometers and gyroscopes, for activity recognition. In this technique, the sensor signals are partitioned into fix sized time windows which can be of two types: (1) non-overlapping windows, in which time windows do not intersect, and (2) overlapping windows, in which they do. There is a generalized idea about the positive impact of using overlapping sliding windows on the performance of recognition systems in Human Activity Recognition. In this paper, we analyze the impact of overlapping sliding windows on the performance of Human Activity Recognition systems with different evaluation techniques, namely, subject-dependent cross validation and subject-independent cross validation. Our results show that the performance improvements regarding overlapping windowing reported in the literature seem to be associated with the underlying limitations of subject-dependent cross validation. Furthermore, we do not observe any performance gain from the use of such technique in conjunction with subject-independent cross validation. We conclude that when using subject-independent cross validation, non-overlapping sliding windows reach the same performance as sliding windows. This result has significant implications on the resource usage for training the human activity recognition systems.

Study Objectives: Consumer wearable devices may be a helpful method of assessing sleep, but validation is required for their use in clinical practice. Our aim was to validate two models of Fitbit sleep trackers that rely on both accelerometer and heart rate sensors against polysomnography in participants with obstructive sleep apnea (OSA)., Methods: Participants were adults presenting with symptoms of OSA and attending our outpatient sleep clinic. A polysomnography (PSG) was applied to all participants at the same time they were wearing a Fitbit sleep tracker. Using paired t tests and Bland-Altman plots, we compared the sleep measures provided by the wearable devices with those obtained by PSG. Since Fitbit devices' automatic detection of sleep start time can cause bias, we performed a correction using Huber loss function-based linear regression and a leave-one-out strategy., Results: Our sample consisted of 65 patients. Diagnosis of OSA was confirmed on 55 (84.6%). There were statistically significant differences between PSG and Fitbit measures for all sleep outcomes but rapid eye movement sleep. Fitbit devices overestimated total sleep time, and underestimated wake after sleep onset and sleep onset latency. After correction of bias, Fitbit-delivered measures of sleep onset latency did not significantly differ of those provided by PSG., Conclusions: Fitbit wearable devices showed an acceptable sensitivity but poor specificity. Consumer sleep trackers still have insufficient accuracy for clinical settings, especially in clinical populations. Solving technical issues and optimizing clinically-oriented features could make them apt for their use in clinical practice in a nondistant future., (© 2019 American Academy of Sleep Medicine.)

Objectives: To use wrist-worn accelerometers (Axivity AX3) to establish normative physical activity (PA) and acceptability data for the high-risk elderly preoperative population, to assess whether PA could be modified by a prehabilitation intervention as part of routine care, to assess any correlation between accelerometer-measured PA and self-reported PA and to assess the acceptability of wearing wrist-worn accelerometers in this population., Study Design: Prospective, observational, pilot study., Setting: Single National Health Service Hospital., Participants: Frail patients≥65 years awaiting major surgery referred to a multidisciplinary preoperative clinic at which they received a routine intervention aimed at improving their PA. 35 patients were recruited. Average age 79.9 years (SD=5.6)., Primary Outcomes: Normative PA data measured as a mean daily Euclidean norm minus one (ENMO) in milli-gravitational units (m g )., Secondary Outcomes: Measure PA levels (m g ) following a routine preoperative intervention. Determine correlation between patient-reported PA (measured using the Physical Activity Scale for the Elderly) and accelerometer-measured PA (m g ). Assess acceptability of wearing a wrist-worn accelerometer measured using Visual Analogue Scale (VAS) questionnaire and device wear time (hours)., Results: Median baseline daily PA was 14.3 m g (IQR 9.75-22.04) with an improvement in PA detected following the intervention (median ENMO post intervention 20.91 m g (IQR 14.83-27.53), p=0.022). There was no significant correlation between accelerometer-measured and self-reported PA (baseline ρ =0.162 (p=0.4), post intervention ρ =-0.144 (p=0.5)). We found high acceptability ratings (median score of 10/10 on VAS, IQR 8-10) and wear-time compliance (163.2 hours (IQR 150-167.5) preintervention and 166.1 hours (IQR 162.5-167) post intervention)., Conclusions: Accelerometery is acceptable to this population and increases in PA levels measured following an unoptimised routine clinical intervention which indicates that health behavioural change interventions may be successful during the preoperative period. Accelerometers may therefore be a useful tool to design and validate interventions for improving PA in this setting., Trial Registration Number: NCT03737903., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Purpose: The physical activity profile can be described from accelerometer data using two population-independent metrics: average acceleration (ACC, volume) and intensity gradient (IG, intensity). This article aims 1) to demonstrate how these metrics can be used to investigate the relative contributions of volume and intensity of physical activity for a range of health markers across data sets and 2) to illustrate the future potential of the metrics for generation of age and sex-specific percentile norms., Methods: Secondary data analyses were conducted on five diverse data sets using wrist-worn accelerometers (ActiGraph/GENEActiv/Axivity): children (n = 145), adolescent girls (n = 1669), office workers (n = 114), premenopausal (n = 1218) and postmenopausal (n = 1316) women, and adults with type 2 diabetes (n = 475). Open-source software (GGIR) was used to generate ACC and IG. Health markers were (a) zBMI (children), (b) %fat (adolescent girls and adults), (c) bone health (pre- and postmenopausal women), and (d) physical function (adults with type 2 diabetes)., Results: Multiple regression analyses showed that IG, but not ACC, was independently associated with zBMI/%fat in children and adolescents. In adults, associations were stronger and the effects of ACC and IG were additive. For bone health and physical function, interactions showed associations were strongest if IG was high, largely irrespective of ACC. Exemplar illustrative percentile "norms" showed the expected age-related decline in physical activity, with greater drops in IG across age than ACC., Conclusion: The ACC and the IG accelerometer metrics facilitate the investigation of whether volume and intensity of physical activity have independent, additive, or interactive effects on health markers. In future studies, the adoption of data-driven metrics would facilitate the generation of age- and sex-specific norms that would be beneficial to researchers.

Background: Classical posturography techniques have been recently enhanced by the use of different motion tracking devices, but for technical reasons they are not used to track directly the body spatial position of a subject., Objective: To describe and clinically evaluate a wireless inertial measurement unit-based mobile system to track body position changes., Methods: The developed system used a calculus transformation method using the acceleration data corrected by Kalman and Butterworth filters to output position data. A prospective non-randomized clinical study involving 15 healthy subjects was performed to evaluate the agreement between the confidence ellipse areas synchronously measured by the new developed system and a classical posturography system while performing a modified clinical test of sensory interaction in balance., Results: The overall intra-class correlation index was 0.93 (CI 0.89, 0.96). Grouped by conditions, under conditions 1-4, Pearson's correlation was 0.604, 0.78, 0.882, and 0.81, respectively., Conclusion: The developed wireless inertial measurement unit-based posturography system was valid for tracking the sway variances in normal subjects under habitual clinical testing conditions. Further studies are needed to validate this system on patients and also under other posture conditions.

Background: Many large studies have implemented wrist or thigh accelerometry to capture physical activity, but the accuracy of these measurements to infer activity energy expenditure (AEE) and consequently total energy expenditure (TEE) has not been demonstrated. The purpose of this study was to assess the validity of acceleration intensity at wrist and thigh sites as estimates of AEE and TEE under free-living conditions using a gold-standard criterion., Methods: Measurements for 193 UK adults (105 men, 88 women, aged 40-66 years, BMI 20.4-36.6 kg m -2 ) were collected with triaxial accelerometers worn on the dominant wrist, non-dominant wrist and thigh in free-living conditions for 9-14 days. In a subsample (50 men, 50 women) TEE was simultaneously assessed with doubly labelled water (DLW). AEE was estimated from non-dominant wrist using an established estimation model, and novel models were derived for dominant wrist and thigh in the non-DLW subsample. Agreement with both AEE and TEE from DLW was evaluated by mean bias, root mean squared error (RMSE), and Pearson correlation., Results: Mean TEE and AEE derived from DLW were 11.6 (2.3) MJ day -1 and 49.8 (16.3) kJ day -1  kg -1 . Dominant and non-dominant wrist acceleration were highly correlated in free-living (r = 0.93), but less so with thigh (r = 0.73 and 0.66, respectively). Estimates of AEE were 48.6 (11.8) kJ day -1  kg -1 from dominant wrist, 48.6 (12.3) from non-dominant wrist, and 46.0 (10.1) from thigh; these agreed strongly with AEE (RMSE ~12.2 kJ day -1  kg -1 , r ~ 0.71) with small mean biases at the population level (~6%). Only the thigh estimate was statistically significantly different from the criterion. When combining these AEE estimates with estimated REE, agreement was stronger with the criterion (RMSE ~1.0 MJ day -1 , r ~ 0.90)., Conclusions: In UK adults, acceleration measured at either wrist or thigh can be used to estimate population levels of AEE and TEE in free-living conditions with high precision.

This study investigates the role of Perceived Athletic Competence (PAC) and Health-Related Fitness (HRF) in mediating the reciprocal relationship between Motor Competence (MC) and Physical Activity (PA) during the transition from primary to secondary school. MC, PA, PAC and HRF were measured in 224 participants (baseline age 12.26 ± .037 years; 51% female) in final year of primary school and one year later in first year of secondary school. Path analysis in AMOS 23 was used to test the mediating influence of PAC and HRF on the MC-PA relationship. Fit indices showed that, in both directions, HRF and PAC mediated the relationship between MC and PA (PA predicting MC; χ2 = 3.91, p = .272, CFI = .99, RMSEA = .04. MC predicting PA: χ2 = 6.46, p = .167, CFI = .99, RMSEA = .04). Pathways were stronger through HRF than through PAC, indicating that HRF is the more substantial mediator of the MC-PA relationship during the school transition. Pathways were stronger in the direction of PA predicting MC than in the reverse direction. Interventions seeking to influence PA and MC across the school transition should focus on HRF as it is a primary mediator of the MC-PA relationship.

Objectives: To assess the validity of the Polar Team Pro Sensor for measuring speed and distance indoors during continuous locomotive and change-of-direction tasks at low, medium, and high intensities., Design: Descriptive validation study., Methods: 26 recreationally-active participants (age: 32.2 ± 11.0 yr; stature: 173.3 ± 9.9 cm; body mass: 74.2 ± 16.2 kg) completed three trials of low- (walking speed), medium- (jogging speed), and high-intensity (maximal sprinting speed) continuous locomotive and change-of-direction tasks. Participants wore back- and chest-mounted sensors to determine mean speed and total distance covered. One-way analysis of variance, t-tests, Pearson's Product moment correlation, and Bland-Altman plots were utilised to compare the speed and distance measured with the back- and chest-mounted sensors to reference measures (measured distance of the court via a trundle wheel and speed derived from measured distance and electronic timing lights)., Results: Speed and distance measured using the back- and chest-mounted sensors showed wide limits of agreement, which increased at high intensities for speed. The sensors typically underestimated speed and distance by as much as 2.76 km h -1 and 32.6 m, and overestimated speed and distance by as much as 4.52 km h -1 and 59.6 m across tasks and intensities compared to reference measures (168.45 and 40.00 m)., Conclusions: There was low agreement between both back- and chest-mounted sensors and the reference devices for measuring speed and distance indoors. Practitioners should understand the limitations and potential for error when using the Polar Team Pro Sensors indoors to measure speed and distance during continuous locomotive and change-of-direction tasks., (Copyright © 2019 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.)

Objective: Systolic time intervals, such as the pre-ejection period (PEP), are important parameters for assessing cardiac contractility that can be measured non-invasively using seismocardiography (SCG). Recent studies have shown that specific points on accelerometer- and gyroscope-based SCG signals can be used for PEP estimation. However, the complex morphology and inter-subject variation of the SCG signal can make this assumption very challenging and increase the root mean squared error (RMSE) when these techniques are used to develop a global model., Methods: In this study, we compared gyroscope- and accelerometer-based SCG signals, individually and in combination, for estimating PEP to show the efficacy of these sensors in capturing valuable information regarding cardiovascular health. We extracted general time-domain features from all the axes of these sensors and developed global models using various regression techniques., Results: In single-axis comparison of gyroscope and accelerometer, angular velocity signal around head to foot axis from the gyroscope provided the lowest RMSE of 12.63 ± 0.49 ms across all subjects. The best estimate of PEP, with a RMSE of 11.46 ± 0.32 ms across all subjects, was achieved by combining features from the gyroscope and accelerometer. Our global model showed 30% lower RMSE when compared to algorithms used in recent literature., Conclusion: Gyroscopes can provide better PEP estimation compared to accelerometers located on the mid-sternum. Global PEP estimation models can be improved by combining general time domain features from both sensors., Significance: This work can be used to develop a low-cost wearable heart-monitoring device and to generate a universal estimation model for systolic time intervals using a single- or multiple-sensor fusion.

Introduction: Compensatory behaviours may be one of the reasons for the limited success of sedentary time interventions in older adults, but this possibility remains unexplored. Activity compensation is the idea that if we change activity levels at one time we compensate for them at a later time to maintain a set point. We aimed to assess, among adults aged ≥60 years, whether sedentary time and time spent in prolonged sedentary bouts (≥30 mins) on one day were associated with sedentary time and time spent in prolonged sedentary bouts (≥30 mins) on the following day. We also sought to determine whether these associations varied by sociodemographic and comorbid factors., Methods: Sedentary time was assessed for seven days using hip-worn accelerometers (ActiGraph GT1M) for 3459 adults who participated in the EPIC-Norfolk Study between 2004 and 2011. We assessed day-to-day associations in total and prolonged bouts of sedentary time using multi-level regressions. We included interaction terms to determine whether associations varied by age, sex, smoking, body mass index, social class, retirement, education and comorbid factors (stroke, diabetes, myocardial infarction and cancer)., Results: Participants (mean age = 70.3, SD = 6.8 years) accumulated 540 sedentary mins/day (SD = 80.1). On any given day, every 60 minutes spent in sedentary time was associated with 9.9 extra sedentary minutes on the following day (95% CI 9.0, 10.2). This association was greater in non-retired compared to retired participants (non-retired 2.57 extra minutes, p = 0.024) and in current compared to former and never-smokers (5.26 extra mins for current vs former; 5.52 extra mins for current vs never, p = 0.023 and 0.017, respectively). On any given day, every 60 minutes spent in prolonged bouts was associated with 7.8 extra minutes in these bouts the following day (95% CI 7.6, 8.4). This association was greater in older individuals (0.18 extra minutes/year of age, 95% CI 0.061, 0.29), and for retired versus non-retired (retired 2.74 extra minutes, 95% CI 0.21, 5.74)., Conclusion: Older adults did not display day-to-day compensation. Instead, individuals demonstrate a large stable component of day-to-day time spent sedentary and in prolonged bouts with a small but important capacity for positive variation. Therefore older adults appear to be largely habitual in their sedentary behaviour. Strategies to augment these patterns may be possible, given they may differ by age, smoking, and working status., Competing Interests: The authors have declared that no competing interests exist.

Background: Many recent commercial devices aim at providing a practical way to measure energy expenditure. However, those devices are limited in accuracy., Objective: This study aimed to build a model of energy consumption during walking applicable to a range of sloped surfaces, used in conjunction with a simple, wearable device., Methods: We constructed a model of energy consumption during gradient walking by using arguments based in mechanics. We built a foot monitoring system that used pressure sensors on the foot insoles. We did experiments in which participants walked on a treadmill wearing the foot monitoring system, and indirect calorimetry was used for validation. We found the parameters of the model by fitting to the data., Results: When walking at 1.5 m/s, we found that the model predicted a calorie consumption rate of 5.54 kcal/min for a woman with average height and weight and 6.89 kcal/min for an average man. With the obtained parameters, the model predicted the data with a root-mean-square deviation of 0.96 kcal/min and median percent error of 12.4%., Conclusions: Our model was found to be an accurate predictor of energy consumption when walking on a range of slopes. The model uses few variables; thus, it can be used in conjunction with a convenient wearable device., (©Soon Ho Kim, Jong Won Kim, Jung-Jun Park, Myung Jun Shin, MooYoung Choi. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 23.10.2019.)

Objectives: (1) To describe the fast Fourier transform (FFT) multijoint as monopodal postural stability measurement in well-trained athletes, (2) to compare the within-subject FFT between laterality, joints, and body segments, and (3) to establish the within- and between-subject relationship between joints., Methods: Twelve national-level basketball players participated voluntarily in this investigation. The participants performed two 60-second repetitions of a monopodal stability test (1 repetition with each lower limb), separated by 3 minutes of active recovery. All tests were recorded by 4 WIMU PRO™ inertial devices located on the ankle, knee, lumbar spine, and thoracic spine. The main variable was total acceleration, where the FFT was applied., Results: The higher instability results were found in the ankle and in the nondominant lower limb (dominant = 1.131 [0.122] a.u. (arbitrary units); nondominant = 1.141 [0.172] a.u). In the body segment analysis, the greater percentage of differences (%diff) were shown between lumbar spine and knee in the dominant (%diff = -2.989%; d = 0.87) and nondominant (%diff = -3.243%; d = 0.90) lower limb. Finally, very large between-subjects variability was found in all joints and body segments., Conclusions: The described protocol is proposed for monopodal postural stability assessment, being useful to provide information about the stability of joints and the body segment between joints. Besides, a within-subject analysis is recommended, and the FFT calculation will enable a linear analysis of each test.

Objective: Physical activity plays a key role in cancer survivorship. The purpose of this investigation was to (a) describe the post-surgical physical activity trajectories of endometrial (n = 65) and ovarian (n = 31) cancer patients and (b) identify clinical and demographic predictors of physical activity over time., Methods: 96 participants wore an Actiwatch accelerometer for three days at each of three time points (one week, one month and four months) after surgical intervention for their endometrial or ovarian cancer diagnosis. Analyses were conducted using linear mixed effects regression modeling in SAS 9.4., Results: For both tumor types, although physical activity levels increased with time after surgery, even at four months patients were performing only a small fraction of the 150 minutes of recommended weekly moderate to vigorous physical activity. At 1 week, subjects were completing on average 14 minutes/week (SD = 4) of moderate-to-vigorous physical activity, compared to 14 minutes/week (SD = 2) of moderate-to-vigorous physical activity at four months post-surgery (p < .05). Better self-rated health was associated with higher physical activity (p = 0.02) in endometrial cancer survivors only. BMI, age, surgery type and use of neoadjuvant chemotherapy were not associated with activity over time., Conclusions: Our findings suggest that physical activity levels are different for those with better self-rated health, but those individuals are still insufficiently active. This study adds new information describing the trajectories and variables that influence physical activity in gynecologic cancer survivors after surgery and highlights the need for health promotion interventions in this population., Competing Interests: MR reports grants from P30 CA014520 (UW Carbone Cancer Center Support Grant), during the conduct of the study; grants from Merck and NIH (MH095778), outside the submitted work. All other authors have nothing to disclose. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Background: Wrist-worn activity trackers are popular, and an increasing number of these devices are equipped with heart rate (HR) measurement capabilities. However, the validity of HR data obtained from such trackers has not been thoroughly assessed outside the laboratory setting., Objective: This study aimed to investigate the validity of HR measures of a high-cost consumer-based tracker (Polar A370) and a low-cost tracker (Tempo HR) in the laboratory and free-living settings., Methods: Participants underwent a laboratory-based cycling protocol while wearing the two trackers and the chest-strapped Polar H10, which acted as criterion. Participants also wore the devices throughout the waking hours of the following day during which they were required to conduct at least one 10-min bout of moderate-to-vigorous physical activity (MVPA) to ensure variability in the HR signal. We extracted 10-second values from all devices and time-matched HR data from the trackers with those from the Polar H10. We calculated intraclass correlation coefficients (ICCs), mean absolute errors, and mean absolute percentage errors (MAPEs) between the criterion and the trackers. We constructed decile plots that compared HR data from Tempo HR and Polar A370 with criterion measures across intensity deciles. We investigated how many HR data points within the MVPA zone (≥64% of maximum HR) were detected by the trackers., Results: Of the 57 people screened, 55 joined the study (mean age 30.5 [SD 9.8] years). Tempo HR showed moderate agreement and large errors (laboratory: ICC 0.51 and MAPE 13.00%; free-living: ICC 0.71 and MAPE 10.20%). Polar A370 showed moderate-to-strong agreement and small errors (laboratory: ICC 0.73 and MAPE 6.40%; free-living: ICC 0.83 and MAPE 7.10%). Decile plots indicated increasing differences between Tempo HR and the criterion as HRs increased. Such trend was less pronounced when considering the Polar A370 HR data. Tempo HR identified 62.13% (1872/3013) and 54.27% (5717/10,535) of all MVPA time points in the laboratory phase and free-living phase, respectively. Polar A370 detected 81.09% (2273/2803) and 83.55% (9323/11,158) of all MVPA time points in the laboratory phase and free-living phase, respectively., Conclusions: HR data from the examined wrist-worn trackers were reasonably accurate in both the settings, with the Polar A370 showing stronger agreement with the Polar H10 and smaller errors. Inaccuracies increased with increasing HRs; this was pronounced for Tempo HR., (©Andre Matthias Matthias Müller, Nan Xin Wang, Jiali Yao, Chuen Seng Tan, Ivan Cherh Chiet Low, Nicole Lim, Jeremy Tan, Agnes Tan, Falk Müller-Riemenschneider. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 02.10.2019.)

Background: Sport watches and fitness trackers provide a feasible way of obtaining energy expenditure (EE) estimations in daily life as well as during exercise. However, today's popular wrist-worn technologies show only poor-to-moderate EE accuracy. Recently, the invention of optical heart rate measurement and the further development of accelerometers in wrist units have opened up the possibility of measuring EE., Objective: This study aimed to validate the new multisensory wristwatch Polar Vantage and its EE estimation in healthy individuals during low-to-high-intensity activities against indirect calorimetry., Methods: Overall, 30 volunteers (15 females; mean age 29.5 [SD 5.1] years; mean height 1.7 [SD 0.8] m; mean weight 67.5 [SD 8.7] kg; mean maximal oxygen uptake 53.4 [SD 6.8] mL/min·kg) performed 7 activities-ranging in intensity from sitting to playing floorball-in a semistructured indoor environment for 10 min each, with 2-min breaks in between. These activities were performed while wearing the Polar Vantage M wristwatch and the MetaMax 3B spirometer., Results: After EE estimation, a mean (SD) of 69.1 (42.7) kcal and 71.4 (37.8) kcal per 10-min activity were reported for the MetaMax 3B and the Polar Vantage, respectively, with a strong correlation of r=0.892 (P<.001). The systematic bias was 2.3 kcal (3.3%), with 37.8 kcal limits of agreement. The lowest mean absolute percentage errors were reported during the sitting and reading activities (9.1%), and the highest error rates during household chores (31.4%). On average, 59.5% of the mean EE values obtained by the Polar Vantage were within ±20% of accuracy when compared with the MetaMax 3B. The activity intensity quantified by perceived exertion (odds ratio [OR] 2.028; P<.001) and wrist circumference (OR -1.533; P=.03) predicted 29% of the error rates within the Polar Vantage., Conclusions: The Polar Vantage has a statistically moderate-to-good accuracy in EE estimation that is activity dependent. During sitting and reading activities, the EE estimation is very good, whereas during nonsteady activities that require wrist and arm movement, the EE accuracy is only moderate. However, compared with other available wrist-worn EE monitors, the Polar Vantage can be recommended, as it performs among the best., (©Rahel Gilgen-Ammann, Theresa Schweizer, Thomas Wyss. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 02.10.2019.)

The purpose of this study was to examine reactivity to accelerometer measurement in children with visual impairments (VI), their sighted siblings, and their parents. A sample of 66 participants (including 22 children with VI, 22 siblings, and 22 parents) completed a demographic survey and wore triaxial accelerometers for at least 4 consecutive days for 8 hr. An analysis of covariances with repeated measures was conducted, controlling for participant gender. Children with VI had 8.1% less moderate to vigorous physical activity time on Day 1 than Days 2-4 average. Their sighted siblings and parents had 7.8% and 7.1% more moderate to vigorous physical activity time on Day 1 than their Days 2-4 average, respectively. The reactivity percentage for parents and children without VI is consistent with existing literature. However, an inverse reactivity for children with VI was found, which is a unique contribution to the literature and will have implications for researchers using accelerometers for this population.

Body-worn devices that estimate physical behavior have tremendous potential to address key research gaps. However, there is no consensus on how devices and processing methods should be developed and evaluated, resulting in large differences in summary estimates and confusion for end users. We propose a phase-based framework for developing and evaluating devices that emphasizes robust validation studies in naturalistic conditions.

Accelerometer measurements are frequently reported as total weekly activity counts (AC). Methods of utilizing activity parameters to allow differentiation of activity intensities (i.e., manually derived cut-points) have been described. While this information may provide valuable data for researchers, only few investigators have utilized these methods. This may, in part, be due to the challenge associated with data processing. Some devices, however, generate activity intensity data automatically. This study was conducted to evaluate a novel accelerometer that allows for remote download of data via Wi-Fi (Heyrex), to compare automatically generated parameters quantifying activity levels to previously established cut-points (Actical) and to describe the variability of accelerometer data in dogs with osteoarthritis. Twelve client-owned dogs with osteoarthritis were fitted with a collar with two accelerometers (Heyrex and Actical). Accelerometer data were recorded for 28 days. Pearson bivariate correlations and coefficient of variation (CV%) were calculated for accelerometer data. There was a strong correlation between the AC reported by Heyrex and Actical devices. Several automatically generated parameters showed strong correlations to previously validated cut-points and displayed lower CV% than weekly AC. The activity intensity derived from the Heyrex was associated with the lowest CV% of all parameters from both accelerometers. Automatically generated activity intensity parameters should be considered as potential outcome measures in clinical trials for dogs with osteoarthritis. This novel technology may allow for convenient acquisition of activity intensity data in companion animals. However, technical difficulties (e.g., lack of Wi-Fi connectivity) may pose challenges when using this novel device., (Published by Elsevier Ltd.)

Demands for precise health information tracking techniques are increasing, especially for daily dietry requirements to prevent obesity, diabetes, etc. Many commercially available sensors that detect dynamic motions of the body lack accuracy, while novel strain sensors at the research level mostly lack the capability to analyze measurements in real life conditions. Here, a stretchable, patch-type calorie expenditure measurement system is demonstrated that integrates an ultrasensitive crack-based strain sensor and Bluetooth-enabled wireless communication circuit to offer both accurate measurements and practical diagnosis of motion. The crack-based strain gauge transformed into a pop-up-shaped structure provides reliable measurements and broad range of strain (≈100%). Combined with the stretchable analysis circuit, the skin attachable tool translates variation of the knee flexion angle into calorie expenditure amount, using relative resistance change (R/R 0 ) data from the flexible sensor. As signals from the knee joint angular movement translates velocity and walking/running behavior, the total amount of calorie expenditure is accurately analyzed. Finally, theoretical, experimental, and simulation analysis of signal stability, dynamic noises, and calorie expenditure calculation obtained from the device during exercise are demonstrated. For further applications, the devices are expected to be used in broader range of dynamic motion of the body for diagnosis of abnormalities and for rehabilitation., (© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Background: Wearable inertial sensors have been shown to provide valid mean gait characteristics assessments, however, assessment of variability is less convincingly established., Research Question: What level of concurrent validity, and session-to-session reliability does an ankle-worn inertial measurement unit (IMU)-based gait assessment with a novel angular velocity-based gait event detection algorithm have among older adults?, Methods: Twenty seven (women N = 17) participants volunteered (age 74.4 (SD 4.3) years, body mass 74.5 (12.0) kg, height 165.9 (9.9) cm). Right leg stance, swing, and stride duration and stride length, and stride velocity were concurrently assessed with motion capture and with an IMU from a 3 min self-paced walk up and back a 14 m track repeated twice a week apart. Gait variability was assessed as the SD of all of the registered strides., Results: Significant difference was observed between methods for many of the mean stride characteristics and stride variability (all p < 0.05), fair to excellent agreement was observed for mean values of all of the five stride characteristics evaluated (intra-class correlation coefficient [ICC] from 0.43 to 1.00). However, poor agreement was observed for the SD of all of the evaluated stride characteristics (ICC from -0.25 to 0.00). Both methods indicated excellent session to session reliability for all of the five stride characteristics evaluated (ICC from 0.84 to 0.98, CV% RMS from 1.6% to 3.6%), whereas the variability characteristics exhibited poor to good reliability (ICC from 0.0 to 0.69, CV% RMS from 18.0% to 34.4%)., Significance: Excellent concurrent validity and reliability was observed for mean spatiotemporal stride characteristics, however, gait variability exhibited poor concurrent validity and reliability. Although IMUs and the presented algorithm could be used to assess mean spatiotemporal stride characteristics among older individuals, either a more reliable gait event detection algorithm or alternative analytical approaches should be used for gait variability., (Copyright © 2019 Elsevier B.V. All rights reserved.)

This review re-examines the use of accelerometer and oxygen uptake data for the assessment of activity intensity. Accelerometers capture mechanical work, while oxygen uptake captures the energy cost of this work. Frequency filtering needs to be considered when processing acceleration data. A too restrictive filter attenuates the acceleration signal for walking and, to a higher degree, for running. This measurement error affects shorter (children) more than taller (adults) individuals due to their higher movement frequency. Less restrictive filtering includes more movement-related signals and provides measures that better capture mechanical work, but may include more noise. An optimal filter cut-point is determined where most relevant acceleration signals are included. Further, accelerometer placement affects what part of mechanical work being captured. While the waist placement captures total mechanical work and therefore contributes to measures of activity intensity equivalent by age and stature, the thigh and wrist placements capture more internal work and do not provide equivalent measures. Value calibration of accelerometer measures is usually performed using measured oxygen uptake with the metabolic equivalent of task (MET) as reference measure of activity intensity. However, the use of MET is not stringent and is not a measure of activity intensity equivalent by age and stature. A candidate measure is the mass-specific net oxygen uptake, VO 2 net (VO 2 tot - VO 2 stand). To improve measurement of physical activity intensity using accelerometers, research developments are suggested concerning the processing of accelerometer data, use of energy expenditure as reference for activity intensity, and calibration procedure with absolute versus relative intensity., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

The objective of this study was to develop a mouthpiece sensor with improved head kinematic measurement for use in non-helmeted and helmeted sports through laboratory validation and pilot field deployment in female youth soccer. For laboratory validation, data from the mouthpiece sensor was compared to standard sensors mounted in a headform at the center of gravity as the headform was struck with a swinging pendulum. Linear regression between peak kinematics measured from the mouthpiece and headform showed strong correlation, with r 2 values of 0.95 (slope = 1.02) for linear acceleration, 1.00 (slope = 1.00) for angular velocity, and 0.97 (slope = 0.96) for angular acceleration. In field deployment, mouthpiece data were collected from four female youth soccer players and time-synchronized with film. Film-verified events (n = 915) were observed over 9 practices and 5 games, and 632 were matched to a corresponding mouthpiece event. This resulted in an overall sensitivity of 69.2% and a positive predictive value of 80.3%. This validation and pilot field deployment data demonstrates that the mouthpiece provides highly accurate measurement of on-field head impact data that can be used to further study the effects of impact exposure in both helmeted and non-helmeted sports.

Obtaining physiological data from animals in a non-obtrusive and continuous manner is important to veterinary science. This paper demonstrates the design and deployment of a miniaturized capsule-based system for subdermal injection to provide real-time and continuous heart-rate, movement, and core-body-temperature measurements. The presented device incorporates sensors for photoplethysmography, motion detection, and temperature measurements. A bluetooth-low-energy enabled microcontroller configures the sensors, digitizes the sensor information, and wirelessly connects with external devices. The device is powered by a CR425 battery for this paper, and various other battery solutions are available based upon the use case. The design uses only commercially available integrated circuits in order to reduce the development cost and be modular. The encapsulation is a combination of medical epoxy and poly(methyl methacrylate) that fits within a 6-gauge hypodermic needle. The preliminary evaluation of the device included an in vitro assessment of its thermal response and measurement accuracy, the impact of one-month implantation on surrounding tissue, the power consumption with duty cycling of various sensors, and a measurement of physiological signals in a rat and a chicken. Having a form factor and implantation method similar to existing devices for animals, this novel system is a useful platform for both scientists and veterinarians to better study a diverse range of animals.

Oropharyngeal dysphagia is prevalent in several at-risk populations, including post-stroke patients, patients in intensive care and the elderly. Dysphagia contributes to longer hospital stays and poor outcomes, including pneumonia. Early identification of dysphagia is recommended as part of the evaluation of at-risk patients, but available bedside screening tools perform inconsistently. In this study, we developed algorithms to detect swallowing impairment using a novel accelerometer-based dysphagia detection system (DDS). A sample of 344 individuals was enrolled across seven sites in the United States. Dual-axis accelerometry signals were collected prospectively with simultaneous videofluoroscopy (VFSS) during swallows of liquid barium stimuli in thin, mildly, moderately and extremely thick consistencies. Signal processing classifiers were trained using linear discriminant analysis and 10,000 random training-test data splits. The primary objective was to develop an algorithm to detect impaired swallowing safety with thin liquids with an area under receiver operating characteristic curve (AUC) > 80% compared to the VFSS reference standard. Impaired swallowing safety was identified in 7.2% of the thin liquid boluses collected. At least one unsafe thin liquid bolus was found in 19.7% of participants, but participants did not exhibit impaired safety consistently. The DDS classifier algorithms identified participants with impaired thin liquid swallowing safety with a mean AUC of 81.5%, (sensitivity 90.4%, specificity 60.0%). Thicker consistencies were effective for reducing the frequency of penetration-aspiration. This DDS reached targeted performance goals in detecting impaired swallowing safety with thin liquids. Simultaneous measures by DDS and VFSS, as performed here, will be used for future validation studies.

Background: People with dysvascular lower limb amputation (LLA) achieve one-third of the recommended steps per day and experience severe disability. Although physical function improves with rehabilitation after dysvascular LLA, physical activity remains largely unchanged, and factors contributing to limited daily step count are unknown., Objectives: To identify factors that contribute to daily step count after dysvascular LLA., Design: Cross-sectional, secondary data analysis., Setting: Outpatient rehabilitation facilities., Participants: Fifty-eight patients with dysvascular major LLA (age: 64 ± 9 years, body mass index: 30 ± 8 kg/m 2 , male: 95%, transtibial LLA: 95%)., Methods: Data were collected by a blinded assessor after dysvascular LLA. Candidate explanatory variables included (1) demographics, (2) LLA characteristics, (3) comorbidities and health behaviors, and (4) physical function. Variables with univariate associations with log steps/day (transformed due to non-normality) were included in a multiple linear regression model using backward elimination to identify factors that explained significant variability in log steps/day., Primary Outcome Measure: The primary outcome, daily step count, was measured with accelerometer-based activity monitors worn by participants for 10 days., Results: Participants took an average (± SD) of 1450 ± 1309 steps/day. After backward elimination, the final model included four variables explaining 62% of the overall daily step count (P < .0001): 2-minute walk distance (32%), assistive device use (11%), cardiovascular disease (10%), and pre-amputation walking time (11%)., Conclusions: Average daily step count of 1450 steps/day reflects the lowest category of sedentary behavior. Physical function, cardiovascular disease, and pre-amputation walking time explain 62% of daily step count after dysvascular LLA. Although physical rehabilitation commonly focuses on improving physical function, interventions to increase daily step count after dysvascular LLA should also consider chronic disease and health behaviors that predate LLA., Level of Evidence: III., (© 2019 American Academy of Physical Medicine and Rehabilitation. This article has been contributed to by US Government employees and their work is in the public domain in the USA.)