Influence of accelerometer type and placement on physical activity energy expenditure prediction in manual wheelchair users

Energy Expenditure Prediction from Accelerometry Data Using Long Short-Term Memory Recurrent Neural Networks

The accurate estimation of energy expenditure from simple objective accelerometry measurements provides a valuable method for investigating the effect of physical activity (PA) interventions or population surveillance. Methods have been evaluated previously, but none utilize the temporal aspects of the accelerometry data. In this study, we investigated the energy expenditure prediction from acceleration measured at the subjects' hip, wrist, thigh, and back using recurrent neural networks utilizing temporal elements of the data. The acceleration was measured in children (N = 33) performing a standardized activity protocol in their natural environment. The energy expenditure was modelled using Multiple Linear Regression (MLR), stacked long short-term memory (LSTM) networks, and combined convolutional neural networks (CNN) and LSTM. The correlation and mean absolute percentage error (MAPE) were 0.76 and 19.9% for the MLR, 0.882 and 0.879 and 14.22% for the LSTM, and, with the combined LSTM-CNN, the best performance of 0.883 and 13.9% was achieved. The prediction error for vigorous intensities was significantly different (p < 0.01) from those of the other intensity domains: sedentary, light, and moderate. Utilizing the temporal elements of movement significantly improves energy expenditure prediction accuracy compared to other conventional approaches, but the prediction error for vigorous intensities requires further investigation.

Real-Life Wheelchair Mobility Metrics from IMUs

Daily wheelchair ambulation is seen as a risk factor for shoulder problems, which are prevalent in manual wheelchair users. To examine the long-term effect of shoulder load from daily wheelchair ambulation on shoulder problems, quantification is required in real-life settings. In this study, we describe and validate a comprehensive and unobtrusive methodology to derive clinically relevant wheelchair mobility metrics (WCMMs) from inertial measurement systems (IMUs) placed on the wheelchair frame and wheel in real-life settings. The set of WCMMs includes distance covered by the wheelchair, linear velocity of the wheelchair, number and duration of pushes, number and magnitude of turns and inclination of the wheelchair when on a slope. Data are collected from ten able-bodied participants, trained in wheelchair-related activities, who followed a 40 min course over the campus. The IMU-derived WCMMs are validated against accepted reference methods such as Smartwheel and video analysis. Intraclass correlation (ICC) is applied to test the reliability of the IMU method. IMU-derived push duration appeared to be less comparable with Smartwheel estimates, as it measures the effect of all energy applied to the wheelchair (including thorax and upper extremity movements), whereas the Smartwheel only measures forces and torques applied by the hand at the rim. All other WCMMs can be reliably estimated from real-life IMU data, with small errors and high ICCs, which opens the way to further examine real-life behavior in wheelchair ambulation with respect to shoulder loading. Moreover, WCMMs can be applied to other applications, including health tracking for individual interest or in therapy settings.

Feasibility study of high-intensity interval training to reduce cardiometabolic disease risks in individuals with acute spinal cord injury

INTRODUCTION

Individuals ageing with spinal cord injury (SCI) experience an accelerated trajectory of diseases and disorders, such as cardiovascular disease and diabetes, that resemble those experienced with ageing alone. Currently, an evidence-based approach toward managing this problem does not exist and therefore the purpose of this study is to determine the feasibility of conducting a high-intensity exercise intervention in individuals with acute (<6 months postinjury) SCI to improve cardiometabolic health.

METHODS AND ANALYSIS

We will conduct a single-centre, two parallel-arm, randomised feasibility study of a high-intensity interval training (HIIT) intervention in individuals with acute SCI. We will enrol 40 individuals (20 intervention, 20 control) with acute SCI attending inpatient rehabilitation at Salisbury District Hospital. Participants will be randomly allocated to the intervention group (HIIT) or control group for 18 weeks. Both groups will participate in standard care throughout the duration of the study. The HIIT group only will also perform supervised HIIT exercise on an arm cycle ergometer three times per week. Over the course of the intervention, most participants will be discharged from the hospital, and at this time, an arm cycle ergometer will be installed in their home and the intervention will transition into outpatient care. We will assess cardiorespiratory fitness, glycaemic control, lipid profile and body habitus as well as qualitative assessments of acceptability at weeks 0, 9 and 18 with the primary outcome being the feasibility of a full Randomised Controlled Trial (RCT).

ETHICS AND DISSEMINATION

This study will inform a longer-term, definitive, multicentre RCT to establish the impact of this exercise intervention in maintaining the cardiometabolic health of patients during the acute phase following SCI. Results will be disseminated in different formats including peer-reviewed journal articles, conference presentations and internet media, to a wide audience including clinicians, researchers and individuals with SCI.

TRIAL REGISTRATION NUMBER

ISRCTN57514022.

The Role of Diets and Dietitians for Para-Athletes: A Pilot Study Based on Interviews

Efforts to provide nutrition support to para-athletes have not been established to date, and are far behind those established for athletes without disabilities. In the present study, we attempted to clarify the actual situation regarding dietary challenges of para-athletes. The aim of this study was to obtain clues to effective intervention methods that encourage the practice of sports nutrition. Six active elite para-athletes (30–70 years, four males) and a female physical therapist without physical disability participated in semi-structured interviews. All para-athletes had lower-limb disabilities and participated in the international wheelchair sports competitions (tennis, softball, and table tennis, with 2–26 years of player history). The interview items were on the ideal diet for improving competitive performance, evaluation of their typical diets, and the role of the dietitian as support. Responses obtained from participants were analyzed using quantitative content analysis by language analysis software. There are differences in the ideal diet based on the characteristics of the sport, but most participants believed that a nutritionally well-balanced diet with abundant vegetables was ideal for improving competitive performance. Para-athletes who use a wheelchair daily pay attention to their total calorie intake, because gaining weight is a critical issue for operating their wheelchairs and transferring themselves to and from their wheelchairs. Despite their world-class competition levels, none of them received routine dietary advice from dietitians. Some para-athletes did not even feel the need to engage with dietitians. Even for these para-athletes at a high level of competition, the “ideal diet” they considered was not always the optimal diet for improving their competitive performance. In addition, there are various barriers to practicing their optimal diet due to disability characteristics. Dietitians need to understand these barriers, their concerns and conflicts, and how to help them plan the optimal diet to improve their performance and maintain overall health.

Technologies measuring manual wheelchair propulsion metrics: a scoping review

The aim of this review is to investigate existing and developing technologies assessing metrics of manual wheelchair propulsion. A scoping review of scientific and gray literature was performed. Five databases were searched - Medline, Scopus, CINAHL, Institute of Electrical and Electronics Engineers (IEEE), and Embase. The 38 retained articles identified 27 devices categorized into accelerometers, wheelchair-mounted devices, instrumented wheels, and wearables. The devices included in this review can be used by manual wheelchair users to monitor propulsion effort and activity goals, by clinicians to assess rehabilitation programs, and to inform and guide future research. The findings support a need for further research into the development of custom algorithms for manual wheelchair user populations as well as further validation in broader free-living environments with equitable participant populations.

Predicting physical activity intensity using raw accelerometer signals in manual wheelchair users with spinal cord injury

STUDY DESIGN

Cross-sectional validation study.

OBJECTIVES

The performance of previously published physical activity (PA) intensity cutoff thresholds based on proprietary ActiGraph counts for manual wheelchair users (MWUs) with spinal cord injury (SCI) was initially evaluated using an out-of-sample dataset of 60 individuals with SCI. Two types of PA intensity classification models based on raw accelerometer signals were developed and evaluated.

SETTING

Research institutions in Pittsburgh PA, Birmingham AL, and Bronx NY.

METHODS

Data were collected from 60 MWUs with SCI who followed a structured activity protocol while wearing an ActiGraph activity monitor on their dominant wrist and portable metabolic cart which measured criterion PA intensity. Data was used to assess published models as well as develop and assess custom models using recall, specificity, precision, as well as normalized Mathew's correlation coefficient (nMCC).

RESULTS

All the models performed well for predicting sedentary vs non-sedentary activity, yielding an nMCC of 0.87-0.90. However, all models demonstrated inadequate performance for predicting moderate to vigorous PA (MVPA) with an nMCC of 0.76-0.82.

CONCLUSIONS

The mean absolute deviation (MAD) cutoff threshold yielded the best performance for predicting sedentary vs non-sedentary PA and may be used for tracking daily sedentary activity. None of the models displayed strong performance for MVPA vs non-MVPA. Future studies should investigate combining physiological measures with accelerometry to yield better prediction accuracies for MVPA.

Classifying Unimanual and Bimanual Upper Extremity Tasks in Individuals Post-Stroke

After stroke, many individuals develop impairments that lead to compensatory motions. Compensation allows individuals to achieve tasks but has long-term detrimental effects and represents maladaptive motor strategies. Increased use of bimanual motions may serve as a biomarker for recovery (and the reduction of reliance on compensatory motion), and tracking such motion using sensor data may provide critical data for health care specialists. However, past work by the authors demonstrated individual variation in motor strategies results in noisy and chaotic sensor data. The goal of the current work is to develop classifiers capable of differentiating unimanual, bimanaual asymmetric, and bimanual symmetric gestures using wearable sensor data. Twenty participants post-stroke (and 20 age-matched controls) performed a set of tasks under the supervision of a trained occupational therapist. Sensor data were recorded for each task. Classifiers were developed using artificial neural networks (ANNs) as a baseline, and the echo state neural network (ESNN) which has demonstrated efficacy with chaotic data. We find that, for control and post-stroke participants, the ESNN results in improved testing accuracy performance (91.3% and 80.3%, respectively). These results suggest a novel method for classifying gestures in individuals post-stroke, and the developed classifiers may facilitate longitudinal monitoring and correction of compensatory motion.

Validation of Using Smartphone Built-In Accelerometers to Estimate the Active Energy Expenditures of Full-Time Manual Wheelchair Users with Spinal Cord Injury

This study aimed to investigate the validity of using built-in smartphone accelerometers to estimate the active energy expenditures of full-time manual wheelchair users with spinal cord injury (SCI). Twenty participants with complete SCI completed 10 5-min daily activities that involved the upper limbs, during which their oxygen consumption and upper limb activity were registered using a portable gas analyzer and a smartphone (placed on the non-dominant arm), respectively. Time series of 1-min averaged oxygen consumption and 55 accelerometer variables (13 variables for each of the four axes and three additional variables for the correlations between axes) were used to estimate three multiple linear models, using a 10-fold cross-validation method. The results showed that models that included either all variables and models or that only included the linear variables showed comparable performance, with a correlation of 0.72. Slightly worse general performance was demonstrated by the model that only included non-linear variables, although it proved to be more accurate at estimating the energy expenditures (EE) during specific tasks. These results suggest that smartphones could be a promising low-cost alternative to laboratory-grade accelerometers to estimate the energy expenditure of wheelchair users with spinal cord injury during daily activities.

Application and Reliability of Accelerometer-Based Arm Use Intensities in the Free-Living Environment for Manual Wheelchair Users and Able-Bodied Individuals

Arm use in manual wheelchair (MWC) users is characterized by a combination of overuse and a sedentary lifestyle. This study aimed to describe the percentage of daily time MWC users and able-bodied individuals spend in each arm use intensity level utilizing accelerometers. Arm use intensity levels of the upper arms were defined as stationary, low, mid, and high from the signal magnitude area (SMA) of the segment accelerations based on in-lab MWC activities performed by eight MWC users. Accelerometry data were collected in the free-living environments from forty MWC users and 40 sex- and age-matched able-bodied individuals. The SMA intensity levels were applied to the free-living data and the percentage of time spent in each level was calculated. The SMA intensity levels were defined as, stationary: ≤0.67 g, low: 0.671-3.27 g, mid: 3.27-5.87 g, and high: >5.871 g. The dominant arm of both MWC users and able-bodied individuals was stationary for most of the day and less than one percent of the day was spent in high intensity arm activities. Increased MWC user age correlated with increased stationary arm time (R = 0.368, p = 0.019). Five and eight days of data are needed from MWC users and able-bodied individuals, respectively, to achieve reliable representation of their daily arm use intensities.

Reliability of ActiGraph GT3X+ placement location in the estimation of energy expenditure during moderate and high-intensity physical activities in young and older adults

WHO defines physical activity (PA) as any bodily movement produced by skeletal muscles that requires energy expenditure (EE). The purpose of this study was to compare the EE estimations by ActiGraph GT3X+ with a gold standard measurement, the portable gas analyser in a set of 3 different PAs. This cross-sectional study involved 56 participants, age range (years, [min, max]: young people [20, 33], older adults [65, 83]). Participants completed a single session of three experimental PAs including biking, treadmill walking, and treadmill running. Each participant wore five GT3X+ triaxial accelerometers and a portable gas analyser used as the gold standard measurement. The GT3X+ were placed on the wrists, the waist (centred at the pelvis), and the ankles. ActiGraph GT3X+ and MetaMax3B records were investigated through intraclass correlation coefficient. Magnitude of measurement error was estimated using Effect Size. The GT3X+ wrist and GT3X+ waist underestimated EE regardless of the PA type. The GT3X+ ankles strongly overestimated EE during biking (mean bias = 489 ± 392%) and walking (mean bias = 106 ± 58%), while it underestimated EE during running (mean bias = -47 ± 27%). The ActiGraph GT3X+ does not provide accurate EE estimates across a range of placement locations during moderate and high-intensity PA.

Comparison of Machine Learning approaches for Classifying Upper Extremity Tasks in Individuals Post-Stroke

After a stroke, individuals often exhibit upper extremity (UE) motor dysfunction, influencing the performance of everyday tasks. Characterizing UE movements is useful to track recovery and response to intervention. Yet, due to the complexity of the recovery process, UE movements may be extremely variable and person-specific. While this renders automatic recognition of these gestures challenging, machine learning methods could be used to classify UE movements in atypical populations. In the current study, we utilize data from 20 individuals post-stroke and 20 age-matched controls to identify an optimal set of sensor-extracted features for the classification of unimanual and bimanual gestures during task performance. We found that using fewer than 100 features along with a random forest classifier produced the best performance across both groups, with both user-dependent and user-independent models.

Comparative validity of energy expenditure prediction algorithms using wearable devices for people with spinal cord injury

STUDY DESIGN

Cross-sectional validation study.

OBJECTIVES

To conduct a literature search for existing energy expenditure (EE) predictive algorithms using ActiGraph activity monitors for manual wheelchairs users (MWUs) with spinal cord injury (SCI), and evaluate their validity using an out-of-sample dataset.

SETTING

Research institution in Pittsburgh, USA.

METHODS

A literature search resulted in five articles containing five sets of predictive equations using an ActiGraph activity monitor for MWUs with SCI. Out-of-sample data were collected from 29 MWUs with chronic SCI who were asked to follow an activity protocol while wearing an ActiGraph GT9X Link on the dominant wrist. They also wore a portable metabolic cart which provided the criterion measure for EE. The out-of-sample dataset was used to evaluate the validity of the five sets of EE predictive equations.

RESULTS

None of the five sets of predictive equations demonstrated equivalence within 20% of the criterion measure based on an equivalence test. The mean absolute error for the five sets of predictive equations ranged from 0.87 to 6.41 kilocalories per minute (kcal min-1) when compared with the criterion measure, and the intraclass correlation estimates ranged from 0.06 to 0.59. The range between the Bland-Altman upper and lower limits of agreement was from 4.70 kcal min-1 to 25.09 kcal min-1.

CONCLUSIONS

The existing EE predictive equations based on ActiGraph monitors for MWUs with SCI showed varied performance when compared with the criterion measure. Their accuracies may not be sufficient to support future clinical and research use. More work is needed to develop more accurate EE predictive equations for this population.

Estimation of Physical Activity Intensity in Spinal Cord Injury Using a Wrist-Worn ActiGraph Monitor

OBJECTIVES

To derive accelerometer count thresholds for classifying time spent in sedentary, light intensity, and moderate-to-vigorous physical activity (MVPA) in manual wheelchair users (MWUs) with spinal cord injury (SCI).

DESIGN

Participants completed 18 activities of daily living and exercises for 10 minutes each with a 3-minute break between activities while wearing a COSMED K4b2 portable metabolic cart and an ActiGraph activity monitor on the dominant wrist. A linear regression was computed between the wrist acceleration vector magnitude and SCI metabolic equivalent of task (MET) for 80% of the participants to obtain thresholds for classifying different activity intensities, and the obtained thresholds were tested for accuracy on the remaining 20% of participants. This cross-validation process was iterated for 1000 times to evaluate the stability of the thresholds on data corresponding to different proportions of sedentary, light intensity, and MVPA. MET values of 1.5 or lower were classified as sedentary behavior, MET values between 1.5 and 3 were classified as light intensity, and MET values of 3 or higher were classified as MVPA. The final thresholds were then validated on an out-of-sample independent dataset.

PARTICIPANTS

MWUs (N=17) with SCI in the out-of-sample validation data set.

INTERVENTIONS

Not applicable.

SETTING

Research lab, community MAIN OUTCOME MEASURES: Accelerometer thresholds to classify sedentary, light intensity, and MVPA were obtained and their accuracy tested using cross-validation and an out-of-sample dataset.

RESULTS

The threshold between sedentary and light intensity was 2057 counts-per-minute, and the threshold between light intensity and MVPA was 11,551 counts per minute. Based on the out-of-sample validation, the obtained thresholds had an overall accuracy of 85.6%, with a sensitivity and specificity of 95.3% and 97.4% for sedentary behavior, 87.8% and 84.5% for light intensity, 68.5% and 96.3% for MVPA, respectively.

CONCLUSION

Accelerometer-based thresholds can be used to accurately identify sedentary behavior. However, thresholds may not provide accurate estimations of MVPA throughout the day when participants engage in more resistance-based activities.

Wearable Sensors in Ambulatory Individuals With a Spinal Cord Injury: From Energy Expenditure Estimation to Activity Recommendations

Inappropriate physical inactivity is a global health problem increasing the risk of cardiometabolic diseases. Wearable sensors show great potential to promote physical activity and thus a healthier lifestyle. While commercial activity trackers are available to estimate energy expenditure (EE) in non-disabled individuals, they are not designed for reliable assessments in individuals with an incomplete spinal cord injury (iSCI). Furthermore, activity recommendations for this population are currently rather vague and not tailored to their individual needs, and activity guidelines provided for the non-disabled population may not be easily translated for this population. However, especially in iSCI individuals with impaired abilities to stand and walk, the assessment of physical activities and appropriate recommendations for a healthy lifestyle are challenging. Therefore, the study aimed at developing an EE estimation model for iSCI individuals able to walk based on wearable sensor data. Additionally, the data collected within this study was used to translate common activity recommendations for the non-disabled population to easily understandable activity goals for ambulatory individuals with an iSCI. In total, 30 ambulatory individuals with an iSCI were equipped with wearable sensors while performing 12 different physical activities. EE was measured continuously and demographic and anthropometric variables, clinical assessment scores as well as wearable-sensor-derived features were used to develop different EE estimation models. The best EE estimation model comprised the estimation of resting EE using the updated Harris-Benedict equation, classifying activities using a k-nearest neighbor algorithm, and applying a multiple linear regression-based EE estimation model for each activity class. The mean absolute estimation error of this model was 15.2 ± 6.3% and the corresponding mean signed error was −3.4 ± 8.9%. Translating activity recommendations of global health institutions, we suggest a minimum of 2,000–3,000 steps per day for ambulatory individuals with an iSCI. If ambulatory individuals with an iSCI targeted the popular 10,000 steps a day recommendation for the non-disabled population, their equivalent would be around 8,000 steps a day. The combination of the presented dedicated EE estimation model for ambulatory individuals with an iSCI and the translated activity recommendations is an important step toward promoting an active lifestyle in this population.

Instruments Measuring Physical Activity in Individuals Who Use a Wheelchair: A Systematic Review of Measurement Properties

OBJECTIVE

To systematically review the evidence evaluating validity or reliability of self-reported and device-based instruments, to measure physical activity (PA) in individuals who use a wheelchair, and to make recommendations for the selection of PA outcomes tools.

DATA SOURCES

PubMed, Embase, and CINAHL were systematically searched.

STUDY SELECTION

Studies reporting measurement properties of instruments to assess PA in individuals who use a wheelchair.

DATA EXTRACTION

The Consensus-Based Standards for the Selection of Health Status Measurement Instruments checklist was used to assess the methodological quality of the included studies. The measurement properties of instruments assessing PA were examined.

DATA SYNTHESIS

The search yielded 5341 records, 61 were considered relevant, 21 articles were included. A best evidence synthesis was performed on 9 studies including 4 self-reported instruments and 13 studies including 8 device-based instruments. One study evaluated both self-reported and device-based instruments. The overall methodological quality of all studies ranged from poor to excellent. Variable levels of evidence were found for both the validity and reliability for self-reported instruments and for criterion validity for device-based instruments.

CONCLUSIONS

The Physical Activity Scale for Individuals with Disabilities (PASIPD) and The Physical Activity Recall Assessment for People with Spinal Cord Injury (PARA-SCI) seem the most promising self-reported instruments for measuring the intensity of PA. Device-based instruments that can be used for measuring both the intensity and type of PA are the GENEActiv, Actigraph GT3X+, Actiheart, or the Physical Activity Monitor System (PAMS), showing moderate evidence for a positive rating of criterion validity. For measuring the type of PA, the PAMS and VitaMove are suitable, showing both good evidence for a positive rating of criterion validity.

Validity of energy expenditure estimation methods during 10 days of military training

Wearable physical activity (PA) monitors have improved the ability to estimate free-living total energy expenditure (TEE) but their application during arduous military training alongside more well-established research methods has not been widely documented. This study aimed to assess the validity of two wrist-worn activity monitors and a PA log against doubly labeled water (DLW) during British Army Officer Cadet (OC) training. For 10 days of training, twenty (10 male and 10 female) OCs (mean ± SD: age 23 ± 2 years, height 1.74 ± 0.09 m, body mass 77.0 ± 9.3 kg) wore one research-grade accelerometer (GENEActiv, Cambridge, UK) on the dominant wrist, wore one commercially available monitor (Fitbit SURGE, USA) on the non-dominant wrist, and completed a self-report PA log. Immediately prior to this 10-day period, participants consumed a bolus of DLW and provided daily urine samples, which were analyzed by mass spectrometry to determine TEE. Bivariate correlations and limits of agreement (LoA) were employed to compare TEE from each estimation method to DLW. Average daily TEE from DLW was 4112 ± 652 kcal·day^-1 against which the GENEActiv showed near identical average TEE (mean bias ± LoA: -15 ± 851 kcal^. day^-1 ) while Fitbit tended to underestimate (-656 ± 683 kcal·day^-1 ) and the PA log substantially overestimate (+1946 ± 1637 kcal·day^-1 ). Wearable physical activity monitors provide a cheaper and more practical method for estimating free-living TEE than DLW in military settings. The GENEActiv accelerometer demonstrated good validity for assessing daily TEE and would appear suitable for use in large-scale, longitudinal military studies.

Predicting ambulatory energy expenditure in lower limb amputees using multi-sensor methods

Purpose

To assess the validity of a derived algorithm, combining tri-axial accelerometry and heart rate (HR) data, compared to a research-grade multi-sensor physical activity device, for the estimation of ambulatory physical activity energy expenditure (PAEE) in individuals with traumatic lower-limb amputation.

Methods

Twenty-eight participants [unilateral (n = 9), bilateral (n = 10) with lower-limb amputations, and non-injured controls (n = 9)] completed eight activities; rest, ambulating at 5 progressive treadmill velocities (0.48, 0.67, 0.89, 1.12, 1.34m.s^-1) and 2 gradients (3 and 5%) at 0.89m.s^-1. During each task, expired gases were collected for the determination of V˙O2 and subsequent calculation of PAEE. An Actigraph GT3X+ accelerometer was worn on the hip of the shortest residual limb and, a HR monitor and an Actiheart (AHR) device were worn on the chest. Multiple linear regressions were employed to derive population-specific PAEE estimated algorithms using Actigraph GT3X+ outputs and HR signals (GT3X+HR). Mean bias±95% Limits of Agreement (LoA) and error statistics were calculated between criterion PAEE (indirect calorimetry) and PAEE predicted using GT3X+HR and AHR.

Results

Both measurement approaches used to predict PAEE were significantly related (P<0.01) with criterion PAEE. GT3X+HR revealed the strongest association, smallest LoA and least error. Predicted PAEE (GT3X+HR; unilateral; r = 0.92, bilateral; r = 0.93, and control; r = 0.91, and AHR; unilateral; r = 0.86, bilateral; r = 0.81, and control; r = 0.67). Mean±SD percent error across all activities were 18±14%, 15±12% and 15±14% for the GT3X+HR and 45±20%, 39±23% and 34±28% in the AHR model, for unilateral, bilateral and control groups, respectively.

Conclusions

Statistically derived algorithms (GT3X+HR) provide a more valid estimate of PAEE in individuals with traumatic lower-limb amputation, compared to a proprietary group calibration algorithm (AHR). Outputs from AHR displayed considerable random error when tested in a laboratory setting in individuals with lower-limb amputation.

Actigraphy-based evaluation of sleep quality and physical activity in individuals with spinal cord injury

Study design

Cross-sectional study.

Background

Sleep disturbances are frequently reported by individuals with spinal cord injury (SCI) and are associated both with poor quality of life and reduced ability to participate in rehabilitation and daily life activities.

Objectives

This study investigated sleep quality based on self-reports and actigraphy in individuals with SCI as compared to able-bodied. We also explored the relationship between sleep quality, physical activity, and neuropathic pain.

Setting

Institute Guttmann, Neurorehabilitation Hospital, Badalona, Barcelona, Spain.

Methods

Fourteen SCI patients (12 males, 43.10 ± 10.59 y.o.) and 10 healthy individuals (7 males, mean age 46.21 ± 12.58 y.o.) were enrolled in the study. Participants wore wrist actigraphs for 7 consecutive days to characterize their sleep-wake cycle, rest-activity circadian rhythm and physical activity. Sleep quality, chronotype, daytime sleepiness, neuropathic pain severity and interference were assessed based on questionnaires.

Results

SCI individuals reported poorer sleep quality compared to healthy individuals. Actigraphy-based sleep measurements revealed that patients woke up later, spent more time in bed and slept longer compared to the healthy controls but did not differ significantly in the estimated sleep efficacy and number of awakenings from the able-bodied controls. In individuals with SCI greater physical activity predicted higher sleep efficacy and less awakening episodes as well as shorter sleep latency and lower sleep disturbance.

Conclusions

The actigraphy-based sleep estimates indicate that patients with SCI spent more time in bed and slept longer but their sleep efficacy was similar to able-bodied controls. Maintaining regular physical activity could improve pain control and sleep quality.

Relationships between muscle size, strength, and physical activity in adults with muscular dystrophy

BACKGROUND

Muscular dystrophy (MD) is characterized by progressive muscle wasting and weakness, yet few comparisons to non-MD controls (CTRL) of muscle strength and size in this adult population exist. Physical activity (PA) is promoted to maintain health and muscle strength within MD; however, PA reporting in adults with MD is limited to recall data, and its impact on muscle strength is seldom explored.

METHODS

This study included 76 participants: 16 non-MD (CTRL, mean age 35.4), 15 Duchenne MD (DMD, mean age 24.2), 18 Becker's MD (BMD, mean age 42.4), 13 limb-girdle MD (LGMD, mean age 43.1), and 14 facioscapulohumeral MD (mean age 47.7). Body fat (%) and lean body mass (LBM) were measured using bioelectrical-impedance. Gastrocnemius medialis (GM) anatomical cross-sectional area (ACSA) was determined using B-mode ultrasound. Isometric maximal voluntary contraction (MVC) was assessed during plantar flexion (PFMVC) and knee extension (KEMVC). PA was measured for seven continuous days using triaxial accelerometry and was expressed as daily average minutes being physically active (TPAmins ) or average daily percentage of waking hours being sedentary (sedentary behaviour). Additionally, 10 m walk time was assessed.

RESULTS

Muscular dystrophy groups had 34-46% higher body fat (%) than CTRL. DMD showed differences in LBM with 21-28% less LBM than all other groups. PFMVC and KEMVC were 36-75% and 24-92% lower, respectively, in MD groups than CTRL. GM ACSA was 47% and 39% larger in BMD and LGMD, respectively, compared with CTRL. PFMVC was associated with GM ACSA in DMD (P = 0.026, R = 0.429) and CTRL (P = 0.015, R = 0.553). MD groups were 14-38% more sedentary than CTRL groups, while DMD were more sedentary than BMD (14%), LGMD (8%), and facioscapulohumeral MD (14%). Sedentary behaviour was associated with LBM in DMD participants (P = 0.021, R = -0.446). TPAmins was associated with KEMVC (P = 0.020, R = 0.540) in BMD participants, while TPAmins was also the best predictor of 10 m walk time (P < 0.001, R2  = 0.540) in ambulant MD, revealed by multiple linear regression.

CONCLUSIONS

Quantified muscle weakness and impaired 10 m walking time is reported in adults with MD. Muscle weakness and 10 m walk time were associated with lower levels of TPA in adults with MD. Higher levels of sedentary behaviour were associated with reduced LBM in DMD. These findings suggest a need for investigations into patterns of PA behaviour, and relevant interventions to reduce sedentary behaviour and encourage PA in adults with MD regardless of impairment severity.

Is Fitbit Charge 2 a feasible instrument to monitor daily physical activity and handbike training in persons with spinal cord injury? A pilot study

Study design

It is a longitudinal pilot study.

Objectives

To investigate the feasibility of a low-cost and widely used fitness tracker with step count and heart rate data to monitor daily physical activity in wheelchair users with spinal cord injury (SCI).

Setting

Dutch community.

Methods

Six participants with SCI who were in training for a handbike event were recruited. They were asked to wear a Fitbit Charge 2^® 24 h a day for at least 2 weeks and were questioned about the utility and user-friendliness of this device.

Results

Five out of six participants managed to wear the device nonstop for 2 weeks, and continued to wear the device after this initial period. Most participants were enthusiastic about the direct feedback provided by the tracker and reported the data to be accurate. Data collected during more than 2 months of three participants and during 8 months on one of them showed the possibility of detecting training days and observing interpersonal and intrapersonal variation in daily physical activity level.

Conclusions

A commercially available, low-cost, self-monitoring multi-sensor wrist device or a fitness tracker like the Fitbit Charge 2^® can be a promising instrument to monitor daily activity levels among wheelchair users with SCI. The free commercial dashboard and log data clearly show trends of variations in physical activity and increases in heart rate, which are of value to both researchers and clinicians interested in identifying training schedules of wheelchair athletes.

Establishing cut-points for physical activity classification using triaxial accelerometer in middle-aged recreational marathoners

The purpose of this study was to establish GENEA (Gravity Estimator of Normal Everyday Activity) cut-points for discriminating between six relative-intensity activity levels in middle-aged recreational marathoners. Nighty-eight (83 males and 15 females) recreational marathoners, aged 30–45 years, completed a cardiopulmonary exercise test running on a treadmill while wearing a GENEA accelerometer on their non-dominant wrist. The breath-by-breath V̇O₂ data was also collected for criterion measure of physical activity categories (sedentary, light, moderate, vigorous, very vigorous and extremely vigorous). GENEA cut-points for physical activity classification was performed via Receiver Operating Characteristic (ROC) analysis. Spearman’s correlation test was applied to determine the relationship between estimated and measured intensity classifications. Statistical analysis were done for all individuals, and separating samples by sex. The GENEA cut-points established were able to distinguish between all six-relative intensity levels with an excellent classification accuracy (area under the ROC curve (AUC) values between 0.886 and 0.973) for all samples. When samples were separated by sex, AUC values were 0.881–0.973 and 0.924–0.968 for males and females, respectively. The total variance in energy expenditure explained by GENEA accelerometer data was 78.50% for all samples, 78.14% for males, and 83.17% for females. In conclusion, the wrist-worn GENEA accelerometer presents a high capacity of classifying the intensity of physical activity in middle-aged recreational marathoners when examining all samples together, as well as when sample set was separated by sex. This study suggests that the triaxial GENEA accelerometers (worn on the non-dominant wrist) can be used to predict energy expenditure for running activities.

Intensity level and on-court role of wheelchair rugby players during competition

BACKGROUND

This study aims at quantifying the level of physical activity of wheelchair rugby players during matches in order to compare defensives players (DP) and offensives players (OP) profiles. Our hypothesis is that OP would present a higher energy expenditure and intensity level values during matches than DP, due to specific actions according to the on-court role.

METHODS

Fifty-two players, including 24 DP and 28 OP (mean age of 34±9 years), from eight French teams involved in the national elite championship and in the French national cup, participated. The seven wheelchair rugby players' classes were differentiated from 0.5 points (most severe deficiencies) to 3.5 points (less severe deficiencies). DP and OP were regrouped from 0.5 to 1.5 points and from 2 to 3.5 points, respectively. Energy expenditure (in kcal), intensity level (in metabolic equivalent of task) and physical activity time (in minutes) of wheelchair rugby players during competition were evaluated.

RESULTS

Statistical analysis between DP and OP showed a significant difference in vigorous activity time with a higher vigorous activity time for OP than DP; P<0.007), associated with higher mean intensity level for OP vs. DP (4.3±1.0 METs vs. 3.8±0.9 METs respectively; P=0.049). No significant differences between DP and OP were found for active energy expenditure (385±158 kcal vs. 446±199 kcal, for DP and OP respectively) during matches.

CONCLUSIONS

This study highlighted significantly different wheelchair rugby player profiles between competing DP and OP for the time spent in high intensity and intensity level. Offensive players were more explosive during a match than DP; therefore, training should be adapted accordingly to their roles.

Validity of activity monitors in wheelchair users: A systematic review

Assessing physical activity (PA) in manual wheelchair users (MWUs) is challenging because of their different movement patterns in comparison to the ambulatory population. The aim of this review was to investigate the validity of portable monitors in quantifying PA in MWUs. A systematic literature search was performed. The data source was full reports of validation and evaluation studies in peer-reviewed journals and conference proceedings. Eligible articles between January 1, 1999, and September 18, 2015, were identified in three databases: PubMed, Institute of Electrical and Electronics Engineers, and Scopus. A total of 164 articles (158 from the databases and 6 from the citation/reference tracking) were identified, and 29 met the eligibility criteria. Two investigators independently extracted the characteristics from each selected article following a predetermined protocol and completed seven summary tables describing the study characteristics and key outcomes. In the identified studies, the monitors were used to assess three types of PA measures: energy cost, user movement, and wheelchair movement. The customized algorithms/monitors did not estimate energy cost in MWUs as well as the commercial monitors did in the ambulatory population; however, they showed fair accuracy in measuring both wheelchair and user movements.

Measurement of Physical Activity and Energy Expenditure in Wheelchair Users: Methods, Considerations and Future Directions

Accurately measuring physical activity and energy expenditure in persons with chronic physical disabilities who use wheelchairs is a considerable and ongoing challenge. Quantifying various free-living lifestyle behaviours in this group is at present restricted by our understanding of appropriate measurement tools and analytical techniques. This review provides a detailed evaluation of the currently available measurement tools used to predict physical activity and energy expenditure in persons who use wheelchairs. It also outlines numerous considerations specific to this population and suggests suitable future directions for the field. Of the existing three self-report methods utilised in this population, the 3-day Physical Activity Recall Assessment for People with Spinal Cord Injury (PARA-SCI) telephone interview demonstrates the best reliability and validity. However, the complexity of interview administration and potential for recall bias are notable limitations. Objective measurement tools, which overcome such considerations, have been validated using controlled laboratory protocols. These have consistently demonstrated the arm or wrist as the most suitable anatomical location to wear accelerometers. Yet, more complex data analysis methodologies may be necessary to further improve energy expenditure prediction for more intricate movements or behaviours. Multi-sensor devices that incorporate physiological signals and acceleration have recently been adapted for persons who use wheelchairs. Population specific algorithms offer considerable improvements in energy expenditure prediction accuracy. This review highlights the progress in the field and aims to encourage the wider scientific community to develop innovative solutions to accurately quantify physical activity in this population.

Impact of anatomical placement of an accelerometer on prediction of physical activity energy expenditure in lower-limb amputees

Purpose

To assess the influence of the anatomical placement of a tri-axial accelerometer on the prediction of physical activity energy expenditure (PAEE) in traumatic lower-limb amputees during walking and to develop valid population-specific prediction algorithms.

Methods

Thirty participants, consisting of unilateral (n = 10), and bilateral (n = 10) amputees, and non-injured controls (n = 10) volunteered to complete eight activities; resting in a supine position, walking on a flat (0.48, 0.67, 0.89, 1.12, 1.34 m.s^-1) and an inclined (3 and 5% gradient at 0.89 m.s^-1) treadmill. During each task, expired gases were collected and an Actigraph GT3X+ accelerometer was worn on the right hip, left hip and lumbar spine. Linear regression analyses were conducted between outputs from each accelerometer site and criterion PAEE (indirect calorimetry). Mean bias ± 95% limits of agreement were calculated. Additional covariates were incorporated to assess whether they improved the prediction accuracy of regression models. Subsequent mean absolute error statistics were calculated for the derived models at all sites using a leave-one out cross-validation analysis.

Results

Predicted PAEE at each anatomical location was significantly (P< 0.01) correlated with criterion PAEE (P<0.01). Wearing the GT3X+ on the shortest residual limb demonstrates the strongest correlation (unilateral; r = 0.86, bilateral; r = 0.94), smallest ±95% limits of agreement (unilateral; ±2.15, bilateral ±1.99 kcal·min^-1) and least absolute percentage error (unilateral; 22±17%, bilateral 17±14%) to criterion PAEE.

Conclusions

We have developed accurate PAEE population specific prediction models in lower-limb amputees using an ActiGraph GT3X+ accelerometer. Of the 3 anatomical locations considered, wearing the accelerometer on the side of the shortest residual limb provides the most accurate prediction of PAEE with the least error in unilateral and bilateral traumatic lower-limb amputees.

Physical Activity Monitoring in Patients with Neurological Disorders: A Review of Novel Body-Worn Devices

Aim

The aim was to conduct a systematic review to examine the literature reporting the validity and reliability of wearable physical activity monitoring in individuals with neurological disorders.

Method

A systematic search of the literature was performed using a specific search strategy in PubMed and CINAHL. A search constraint of articles published in English, including human participants, published between January 2008 and March 2017 was applied. Peer-reviewed studies which enrolled adult participants with any neurological disorder were included. For the studies which sought to explore the validity of activity monitors, the outcomes measured using the monitor were compared to a criterion measure of physical activity. The studies' methodological quality was assessed using an adapted version of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) framework. Data extracted from each study included the following: characteristics of the study participants, study setting, devices used, study protocol/methods, outcomes measured, and the validity/reliability of measurement produced.

Results

Twenty-three studies examining the validity and reliability of 16 different monitors were included. The identified studies comprised participants with a range of different disorders of neurological origin. The available evidence suggests that biaxial or triaxial accelerometer devices positioned around the ankle produce the most accurate step count measurements in patients with neurological disorders. The findings regarding the reliability and validity of activity counts and energy expenditure are largely inconclusive in this population.

Discussion

Ankle-worn biaxial or triaxial accelerometer-type devices provide the most accurate measurement of physical activity. However, further work is required in this field before wearable activity monitoring can be more widely implemented clinically. Standardised activity monitoring protocols are required for implementing these devices in clinical trials and clinical practice, and consensus is required as to the reporting and interpretation of derived variables.

Assessment of laboratory and daily energy expenditure estimates from consumer multi-sensor physical activity monitors

Wearable physical activity monitors are growing in popularity and provide the opportunity for large numbers of the public to self-monitor physical activity behaviours. The latest generation of these devices feature multiple sensors, ostensibly similar or even superior to advanced research instruments. However, little is known about the accuracy of their energy expenditure estimates. Here, we assessed their performance against criterion measurements in both controlled laboratory conditions (simulated activities of daily living and structured exercise) and over a 24 hour period in free-living conditions. Thirty men (n = 15) and women (n = 15) wore three multi-sensor consumer monitors (Microsoft Band, Apple Watch and Fitbit Charge HR), an accelerometry-only device as a comparison (Jawbone UP24) and validated research-grade multi-sensor devices (BodyMedia Core and individually calibrated Actiheart™). During discrete laboratory activities when compared against indirect calorimetry, the Apple Watch performed similarly to criterion measures. The Fitbit Charge HR was less consistent at measurement of discrete activities, but produced similar free-living estimates to the Apple Watch. Both these devices underestimated free-living energy expenditure (-394 kcal/d and -405 kcal/d, respectively; P<0.01). The multi-sensor Microsoft Band and accelerometry-only Jawbone UP24 devices underestimated most laboratory activities and substantially underestimated free-living expenditure (-1128 kcal/d and -998 kcal/d, respectively; P<0.01). None of the consumer devices were deemed equivalent to the reference method for daily energy expenditure. For all devices, there was a tendency for negative bias with greater daily energy expenditure. No consumer monitors performed as well as the research-grade devices although in some (but not all) cases, estimates were close to criterion measurements. Thus, whilst industry-led innovation has improved the accuracy of consumer monitors, these devices are not yet equivalent to the best research-grade devices or indeed equivalent to each other. We propose independent quality standards and/or accuracy ratings for consumer devices are required.

Data logger technologies for manual wheelchairs: A scoping review

In recent years, studies have increasingly employed data logger technologies to record objective driving and physiological characteristics of manual wheelchair users. However, the technologies used offer significant differences in characteristics, such as measured outcomes, ease of use, and level of burden. In order to identify and describe the extent of published research activity that relies on data logger technologies for manual wheelchair users, we performed a scoping review of the scientific and gray literature. Five databases were searched: Medline, Compendex, CINAHL, EMBASE, and Google Scholar. The 119 retained papers document a wide variety of logging devices and sensing technologies measuring a range of outcomes. The most commonly used technologies were accelerometers installed on the user (18.8%), odometers installed on the wheelchair (12.4%), accelerometers installed on the wheelchair (9.7%), and heart monitors (9.7%). Not surprisingly, the most reported outcomes were distance, mobility events, heart rate, speed/velocity, acceleration, and driving time. With decreasing costs and technological improvements, data loggers are likely to have future widespread clinical (and even personal) use. Future research may be needed to assess the usefulness of different outcomes and to develop methods more appropriate to wheelchair users in order to optimize the practicality of wheelchair data loggers.

The Evaluation of Physical Stillness with Wearable Chest and Arm Accelerometer during Chan Ding Practice

Chan Ding training is beneficial to health and emotional wellbeing. More and more people have taken up this practice over the past few years. A major training method of Chan Ding is to focus on the ten Mailuns, i.e., energy points, and to maintain physical stillness. In this article, wireless wearable accelerometers were used to detect physical stillness, and the created physical stillness index (PSI) was also shown. Ninety college students participated in this study. Primarily, accelerometers used on the arms and chest were examined. The results showed that the PSI values on the arms were higher than that of the chest, when participants moved their bodies in three different ways, left-right, anterior-posterior, and hand, movements with natural breathing. Then, they were divided into three groups to practice Chan Ding for approximately thirty minutes. Participants without any Chan Ding experience were in Group I. Participants with one year of Chan Ding experience were in Group II, and participants with over three year of experience were in Group III. The Chinese Happiness Inventory (CHI) was also conducted. Results showed that the PSI of the three groups measured during 20-30 min were 0.123 ± 0.155, 0.012 ± 0.013, and 0.001 ± 0.0003, respectively (p < 0.001 ***). The averaged CHI scores of the three groups were 10.13, 17.17, and 25.53, respectively (p < 0.001 ***). Correlation coefficients between PSI and CHI of the three groups were -0.440, -0.369, and -0.537, respectively (p < 0.01 **). PSI value and the wearable accelerometer that are presently available on the market could be used to evaluate the quality of the physical stillness of the participants during Chan Ding practice.

The influence of a home-based exercise intervention on human health indices in individuals with chronic spinal cord injury (HOMEX-SCI): study protocol for a randomised controlled trial

BACKGROUND

Spinal cord injury (SCI) creates a complex pathology that can lead to an increase in sedentary behaviours and deleterious changes in body composition. Consequently, individuals with SCI are at increased risk of developing cardiovascular disease and type-2 diabetes mellitus. While the role of physical activity on the reduction of chronic disease risk is well documented in non-disabled individuals the evidence is less conclusive for persons with SCI. The aim of this methodological paper is to outline the design of a study that will assess the role of a home-based exercise intervention on biomarkers of metabolic and cardiovascular health in persons with SCI: the HOMEX-SCI study.

METHODS/DESIGN

Eligible participants will be inactive (physical activity level ≤1.60) individuals, with a chronic (more than 1 year) spinal cord lesion between the second thoracic and the fifth lumbar vertebrae, and aged between 18 and 65 years. Following baseline laboratory testing and lifestyle monitoring, participants will be randomly allocated to a control (CON) group or a 6-week home-based exercise intervention (INT) group. The INT consists of 45 minutes of moderate-intensity (60-65 % peak oxygen uptake) arm-crank exercise four times per week. Participants assigned to the CON group will be asked to maintain their normal lifestyle. The main outcomes of this study (biomarkers of metabolic and cardiovascular health) are obtained from venous blood samples, collected in the fasted and postprandial state. Eight other measurement categories will be assessed: (1) body composition, (2) physical activity, (3) energy intake, (4) measures of health and wellbeing, (5) resting metabolic rate, heart rate and blood pressure, (6) aerobic capacity, (7) immune function, and (8) adipose tissue gene expression.

DISCUSSION

This study will explore the feasibility of home-based moderate-intensity exercise and ascertain its impact on metabolic and cardiovascular health in comparison to a lifestyle maintenance CON group. Findings from this study may help to inform new evidence-based physical activity guidelines and also help to elucidate the physiological mechanisms whereby exercise might exert beneficial effects in persons with chronic SCI. The results will also act as a scientific platform for further intervention studies in other diverse and at-risk populations.

TRIAL REGISTRATION

International Standard Randomised Controlled Trial Number: ISRCTN57096451 . Registered on 11 July 2014.

Predicting physical activity energy expenditure in wheelchair users with a multisensor device

Aim

To assess the error in predicting physical activity energy expenditure (PAEE), using a multisensor device in wheelchair users, and to examine the efficacy of using an individual heart rate calibration (IC) method.

Methods

15 manual wheelchair users (36±10 years, 72±11 kg) completed 10 activities: resting, folding clothes, wheelchair propulsion on a 1% gradient (3456 and 7 km/h) and propulsion at 4 km/h (with an additional 8% of body mass, 2% and 3% gradient) on a motorised wheelchair treadmill. Criterion PAEE was measured using a computerised indirect calorimetry system. Participants wore a combined accelerometer and heart rate monitor (Actiheart). They also performed an incremental arm crank ergometry test to exhaustion which permitted retrospective individual calibration of the Actiheart for the activity protocol. Linear regression analysis was conducted between criterion (indirect calorimetry) and estimated PAEE from the Actiheart using the manufacturer's proprietary algorithms (group calibration, GC) or IC. Bland-Altman plots were used and mean absolute error was calculated to assess the agreement between criterion values and estimated PAEE.

Results

Predicted PAEE was significantly (p<0.01) correlated with criterion PAEE (GC, r=0.76 and IC, r=0.95). The absolute bias ±95% limits of agreement were 0.51±3.75 and −0.22±0.96 kcal/min for GC and IC, respectively. Mean absolute errors across the activity protocol were 51.4±38.9% using GC and 16.8±15.8% using IC.

Summary

PAEE can be accurately and precisely estimated using a combined accelerometer and heart rate monitor device, with integration of an IC. Interindividual variance in cardiovascular function and response to exercise is high in this population. Therefore, in manual wheelchair users, we advocate the use of an IC when using the Actiheart to predict PAEE.