Validation of the use of Actigraph GT3X accelerometers to estimate energy expenditure in full time manual wheelchair users with spinal cord injury

Validity of Actigraph for Measuring Energy Expenditure in Healthy Adults: A Systematic Review and Meta-Analysis

PURPOSE

The objective of this systematic review and meta-analysis was to assess the validity of the Actigraph triaxial accelerometer device in measuring physical activity energy expenditure (PAEE) in healthy adults, with indirect calorimetry (IC) serving as the validity criterion.

METHODS

A comprehensive search was conducted using the PubMed, Web of Science, and sportdiscuss databases, in addition to manual searches for supplementary sources. Search strategies were employed that involved conducting single keyword searches using the terms "gt3x" and "Actigraph gt3x". The literature search encompassed the timeframe spanning from 1 January 2010 to 1 March 2023. The methodological quality of the studies included in the analysis was evaluated using both the Downs and Black checklist and the Consensus-Based Criteria for Selection of Measurement Instruments (COSMIN) checklist. The meta-analysis was conducted using the Review Manager 5.4 software. The standardized mean difference (SMD) was calculated and expressed as a 95% confidence interval (CI). The significance level was set at α = 0.05. A systematic assessment of the Actigraph's performance was conducted through the descriptive analysis of computed effect sizes.

RESULTS

A total of 4738 articles were retrieved from the initial search. After eliminating duplicate articles and excluding those deemed irrelevant, a comprehensive analysis was conducted on a total of 20 studies, encompassing a combined sample size of 1247 participants. The scores on the Downs and Black checklist ranged from 10 to 14, with a mean score of 11.35. The scores on the COSMIN checklist varied from 50% to 100%, with an average score of 65.83%. The meta-analysis findings revealed a small effect size (SMD = 0.01, 95% CI = 0.50-0.52, p = 0.97), indicating no statistically significant difference (p > 0.05).

CONCLUSIONS

The meta-analysis revealed a small effect size when comparing the Actigraph and IC, suggesting that the Actigraph can be utilized for assessing total PAEE. Descriptive analyses have indicated that the Actigraph device has limited validity in accurately measuring energy expenditure during specific physical activities, such as high-intensity and low-intensity activities. Therefore, caution should be exercised when utilizing this device for such purposes. Furthermore, there was a significant correlation between the activity counts measured by the Actigraph and the PAEE, indicating that activity counts can be utilized as a predictive variable for PAEE.

Limb accelerations during sleep are related to measures of strength, sensation, and spasticity among individuals with spinal cord injury

BACKGROUND

To evaluate the relationship between measures of neuromuscular impairment and limb accelerations (LA) collected during sleep among individuals with chronic spinal cord injury (SCI) to provide evidence of construct and concurrent validity for LA as a clinically meaningful measure.

METHODS

The strength (lower extremity motor score), sensation (summed lower limb light touch scores), and spasticity (categorized lower limb Modified Ashworth Scale) were measured from 40 adults with chronic (≥ 1 year) SCI. Demographics, pain, sleep quality, and other covariate or confounding factors were measured using self-report questionnaires. Each participant then wore ActiGraph GT9X Link accelerometers on their ankles and wrist continuously for 1-5 days to measure LA from movements during sleep. Regression models with built-in feature selection were used to determine the most relevant LA features and the association to each measure of impairment.

RESULTS

LA features were related to measures of impairment with models explaining 69% and 73% of the variance (R²) in strength and sensation, respectively, and correctly classifying 81.6% (F1-score = 0.814) of the participants into spasticity categories. The most commonly selected LA features included measures of power and frequency (frequency domain), movement direction (correlation between axes), consistency between movements (relation to recent movements), and wavelet energy (signal characteristics). Rolling speed (change in angle of inclination) and movement smoothness (median crossings) were uniquely associated with strength. When LA features were included, an increase of 72% and 222% of the variance was explained for strength and sensation scores, respectively, and there was a 34% increase in spasticity classification accuracy compared to models containing only covariate features such as demographics, sleep quality, and pain.

CONCLUSION

LA features have shown evidence of having construct and concurrent validity, thus demonstrating that LA are a clinically-relevant measure related to lower limb strength, sensation, and spasticity after SCI. LA may be useful as a more detailed measure of impairment for applications such as clinical prediction models for ambulation.

Toward Improving the Prediction of Functional Ambulation After Spinal Cord Injury Though the Inclusion of Limb Accelerations During Sleep and Personal Factors

OBJECTIVE

To determine if functional measures of ambulation can be accurately classified using clinical measures; demographics; personal, psychosocial, and environmental factors; and limb accelerations (LAs) obtained during sleep among individuals with chronic, motor incomplete spinal cord injury (SCI) in an effort to guide future, longitudinal predictions models.

DESIGN

Cross-sectional, 1-5 days of data collection.

SETTING

Community-based data collection.

PARTICIPANTS

Adults with chronic (>1 year), motor incomplete SCI (N=27).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Ambulatory ability based on the 10-m walk test (10MWT) or 6-minute walk test (6MWT) categorized as nonambulatory, household ambulator (0.01-0.44 m/s, 1-204 m), or community ambulator (>0.44 m/s, >204 m). A random forest model classified ambulatory ability using input features including clinical measures of strength, sensation, and spasticity; demographics; personal, psychosocial, and environmental factors including pain, environmental factors, health, social support, self-efficacy, resilience, and sleep quality; and LAs measured during sleep. Machine learning methods were used explicitly to avoid overfitting and minimize the possibility of biased results.

RESULTS

The combination of LA, clinical, and demographic features resulted in the highest classification accuracies for both functional ambulation outcomes (10MWT=70.4%, 6MWT=81.5%). Adding LAs, personal, psychosocial, and environmental factors, or both increased the accuracy of classification compared with the clinical/demographic features alone. Clinical measures of strength and sensation (especially knee flexion strength), LA measures of movement smoothness, and presence of pain and comorbidities were among the most important features selected for the models.

CONCLUSIONS

The addition of LA and personal, psychosocial, and environmental features increased functional ambulation classification accuracy in a population with incomplete SCI for whom improved prognosis for mobility outcomes is needed. These findings provide support for future longitudinal studies that use LA; personal, psychosocial, and environmental factors; and advanced analyses to improve clinical prediction rules for functional mobility outcomes.

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.

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.

Step and Distance Measurement From a Low-Cost Consumer-Based Hip and Wrist Activity Monitor: Protocol for a Validity and Reliability Assessment

Background

Self-tracking via wearable and mobile technologies is becoming an essential part of personal health management. At this point, however, little information is available to substantiate the validity and reliability of low-cost consumer-based hip and wrist activity monitors, with regard more specifically to the measurements of step counts and distance traveled while walking.

Objective

The aim of our study is to assess the validity and reliability of step and distance measurement from a low-cost consumer-based hip and wrist activity monitor specific in various walking conditions that are commonly encountered in daily life. Specifically, this study is designed to evaluate whether and to what extent validity and reliability could depend on the sensor placement on the human body and the walking task being performed.

Methods

Thirty healthy participants will be instructed to wear four PBN 2433 (Nakosite) activity monitors simultaneously, with one placed on each hip and each wrist. Participants will attend two experimental sessions separated by 1 week. During each experimental session, two separate studies will be performed. In study 1, participants will be instructed to complete a 2-minute walk test along a 30-meter indoor corridor under 3 walking speeds: very slow, slow, and usual speed. In study 2, participants will be required to complete the following 3 conditions performed at usual walking speed: walking on flat ground, upstairs, and downstairs. Activity monitor measured step count and distance values will be computed along with the actual step count (determined from video recordings) and distance (measured using a measuring tape) to determine validity and reliability for each activity monitor placement and each walking condition.

Results

Participant recruitment and data collection began in January 2020. As of June 2020, we enrolled 8 participants. Dissemination of study results in peer-reviewed journals is expected in spring 2021.

Conclusions

To the best of our knowledge, this is the first study that examines the validity and reliability of step and distance measurement during walking using the PBN 2433 (Nakosite) activity monitor. Results of this study will provide beneficial information on the effects of activity monitor placement, walking speed, and walking tasks on the validity and reliability of step and distance measurement. We believe such information is of utmost importance to general consumers, clinicians, and researchers.

International Registered Report Identifier (IRRID)

DERR1-10.2196/21262

Different neighborhood walkability indexes for active commuting to school are necessary for urban and rural children and adolescents

BACKGROUND

Literature focusing on youth has reported limited evidence and non-conclusive associations between neighborhood walkability measures and active commuting to and from school (ACS). Moreover, there is a lack of studies evaluating both macro- and micro-scale environmental factors of the neighborhood when ACS is analyzed. Likewise, most studies on built environment attributes and ACS focus on urban areas, whereas there is a lack of studies analyzing rural residential locations. Moreover, the relationship between built environment attributes and ACS may differ in children and adolescents. Hence, this study aimed to develop walkability indexes in relation to ACS for urban and rural children and adolescents, including both macro- and micro-scale school-neighborhood factors.

METHODS

A cross-sectional study of 4593 participants from Spain with a mean age of 12.2 (SD 3.6) years was carried out. Macro-scale environmental factors were evaluated using geographic information system data, and micro-scale factors were measured using observational procedures. Socio-demographic characteristics and ACS were assessed with a questionnaire. Several linear regression models were conducted, including all the possible combinations of six or less built environment factors in order to find the best walkability index.

RESULTS

Analyses showed that intersection density, number of four-way intersections, and residential density were positively related to ACS in urban participants, but negatively in rural participants. In rural children, positive streetscape characteristics, number of regulated crossings, traffic calming features, traffic lanes, and parking street buffers were also negatively related to ACS. In urban participants, other different factors were positively related to ACS: number of regulated crossings, positive streetscape characteristics, or crossing quality. Land use mix acted as a positive predictor only in urban adolescents. Distance to the school was a negative predictor on all the walkability indexes. However, aesthetic and social characteristics were not included in any of the indexes.

CONCLUSIONS

Interventions focusing on improving built environments to increase ACS behavior need to have a better understanding of the walkability components that are specifically relevant to urban or rural samples.

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.

Accuracy of Apple Watch fitness tracker for wheelchair use varies according to movement frequency and task

OBJECTIVES

Individuals with disabilities have high prevalence of sedentary lifestyle, obesity, and cardiometabolic disease. Physical activity monitors (i.e., step counters) are ill-suited for tracking wheelchair pushes. The study purpose was to investigate the validity of a consumer-level fitness tracker (Apple Watch) designed for wheelchair users.

METHODS

Validation study. A total of 15 wheelchair users with disabilities and 15 able-bodied individuals completed 3-min bouts of wheelchair propulsion on a treadmill and arm ergometry at pre-determined cadences as well as overground obstacle and Figure 8 courses. Tracker stroke counts were compared against direct observation.

RESULTS

We found no interaction of tracker counts and ability status across all tasks (P≥0.550), so results are presented for the combined sample. For treadmill tasks, Bland-Altman analysis (bias±limits of agreement) showed good agreement for only higher-rate fixed-frequency tasks (-15±48, -1±14, 0±5, and 0±27 for low, moderate, high, and variable cadence, respectively). Mean absolute percentage error (MAPE) was 22%, 3%, 1%, and 6%, respectively. Intraclass correlation coefficients (ICCs) (95% confidence intervals) were -0.18 (-0.51-0.20), 0.47 (0.13-0.71), 0.98 (0.96-0.99), and 0.22 (-0.16-0.54). We found significant overestimation by the tracker at low frequency (P<0.01). Arm ergometry showed good agreement across all cadences (0±5, -1±3, 0±8, 6±6). MAPE was 1%, 1%, 1%, and 4%. ICCs were 0.88 (0.77-0.94), 0.95 (0.89-0.97), 0.88 (0.76-0.94), and 0.97 (0.87-0.97). We found minimal (2rpm) but significant differences at variable cadence (P<0.01). Overground tasks showed poor agreement for casual-pace and fast-pace obstacle course and Figure 8 task (-5±18, 0±23, and -18±32, respectively). MAPE was 15%, 18%, 21% and ICCs were 0.90 (0.79-0.95), 0.79 (0.59-0.90), and 0.82 (0.64-0.91). Significant differences were found for propulsion at casual pace (P<0.01) and the Figure 8 task (P<0.01).

CONCLUSIONS

Apple Watch is suitable for tracking high-frequency standardized (i.e., treadmill) pushing and arm ergometry but not low-frequency pushing or overground tasks.

Use of actigraphy to measure real-world physical activities in manual wheelchair users

Introduction

The benefits of physical activity for manual wheelchair users are well-known. The purpose of this study was to validate actigraphy to objectively measure physical activity intensity among manual wheelchair users.

Method

An experimental design was used. Adult manual wheelchair users wore a GT3X actigraph on their non-dominant arm while completing eight physical activities of low (reading), moderate (propelling -- flat) and high (propelling -- steep ramp) intensity. Heart rate and rating of perceived exertion were collected at the end of each physical activity. Distribution of data were examined and used to determine the type of repeated measures (parametric vs. non-parametric). A categorical principal component analysis was performed to determine the amount of variability explained by actigraphy, heart rate and rating of perceived exertion. Activity count cut-points were estimated using bootstrapping methods.

Results

Twenty-eight manual wheelchair users completed the study. Actigraphy, heart rate and rating of perceived exertion co-varied as physical activity intensity changed. Activity counts for low-intensity and medium-intensity physical activities were estimated to be 0 to 45 and 45 to 100 activity counts per second, respectively. Activity counts' ranges for high-intensity physical activities were not clear.

Conclusion

Combining actigraphy and rating of perceived exertion could be an easy and reliable method to measure the intensity of real-world activities. Further research is needed confirm cut-points for physical activity intensity.

Accelerometer assessment of physical activity in individuals with paraplegia who do and do not participate in physical exercise

OBJECTIVE

Our main goal was to measure physical activity (PA) in people with paraplegia. Secondarily, we aimed to establish the relationship between being engaged in physical exercise (PE) and reaching the recommended moderate-to-vigorous physical activity (MVPA) level. We further analyzed the effect of being engaged in PE on the PA levels.

DESIGN

Descriptive cross-sectional.

SETTING

Spanish associations for individuals with spinal cord injury.

PARTICIPANTS

Ninety-six manual wheelchair users with chronic paraplegia.

INTERVENTIONS

Participants wore a wrist accelerometer for one week.

OUTCOME MEASURES

Levels of PA and sedentary behavior. In addition, participants were classified into two groups, exercisers (EG) and non-exercisers (NEG) to analyze the effect of PE enrollment on the variables.

RESULTS

For all participants, a mean (SD) of 5,341.70 (966.4) minutes per week were spent engaged in sedentary behaviors, 2,188.99 (723.9) minutes were spent engaged in light activity, and 206.24 (180.0) minutes were spent engaged in MVPA. There was a significant relationship between PE and reaching the minimum levels of MVPA recommended [x2 (1) = 25.03, P < 0.01]. NEG showed a greater number of minutes per week for sedentary behavior [t (94) = 2.50, P < 0.05, r = 0.25]. The EG spent more than twice as much time doing MVPA than the NEG (263.8 min vs 114.3 min, respectively).

CONCLUSIONS

MVPA levels are low in manual wheelchair users who are not regular exercisers, but most of those who self-reported being regular exercisers reach the minimum levels recommended for health benefits. Sedentary behavior is a concern in this population.

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.

Mobile health-based physical activity intervention for individuals with spinal cord injury in the community: A pilot study

Low levels of physical activity (PA) and high levels of sedentary behavior in individuals with spinal cord injury (SCI) have been associated with secondary conditions such as pain, fatigue, weight gain, and deconditioning. One strategy for promoting regular PA is to provide people with an accurate estimate of everyday PA level. The objective of this research was to use a mobile health-based PA measurement system to track PA levels of individuals with SCI in the community and provide them with a behavior-sensitive, just-in-time-adaptive intervention (JITAI) to improve their PA levels. The first, second, and third phases of the study, each with a duration of one month, involved collecting baseline PA levels, providing near-real-time feedback on PA level (PA Feedback), and providing PA Feedback with JITAI, respectively. PA levels in terms of energy expenditure in kilocalories, and minutes of light- and moderate- or vigorous-intensity PA were assessed by an activity monitor during the study. Twenty participants with SCI took part in this research study with a mean (SD) age of 39.4 (12.8) years and 12.4 (12.5) years since injury. Sixteen participants completed the study. Sixteen were male, 16 had paraplegia, and 12 had complete injury. Within-participant comparisons indicated that only two participants had higher energy expenditure (>10%) or lower energy expenditure (<-10%) during PA Feedback with JITAI compared to the baseline. However, eleven participants (69.0%) had higher light- and/or moderate-intensity PA during PA Feedback with JITAI compared to the baseline. To our knowledge, this is the first study to test a PA JITAI for individuals with SCI that responds automatically to monitored PA levels. The results of this pilot study suggest that a sensor-enabled mobile JITAI has potential to improve PA levels of individuals with SCI. Future research should investigate the efficacy of JITAI through a clinical trial.

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.

Defining accelerometer cut-points for different intensity levels in motor-complete spinal cord injury

STUDY DESIGN

Descriptive.

OBJECTIVE

The present aim was to define accelerometer cut-point values for wrist-worn accelerometers to identify absolute- and relative-intensity physical activity (PA) levels in people with motor-complete paraplegics (PP) and tetraplegics (TP).

SETTINGS

Rehabilitation facility in Sweden.

METHODS

The participants were 26 (19 men, 7 women) with C5-C8, AIS A and B (TP) and 37 (27 men, 10 women) with T7-T12 (PP), AIS A and B. Wrist-worn accelerometer recordings (Actigraph GT3X+) were taken during seven standardized activities. Oxygen consumption was measured, as well as at-rest and peak effort, with indirect calorimetry. Accelerometer cut-points for absolute and relative intensities were defined using ROC-curve analyses.

RESULTS

The ROC-curve analyses for accelerometer cut-points revealed good-to-excellent accuracy (AUC >0.8), defining cut-points for absolute intensity (2, 3, 4, 5, 6, 7 METs for PP and 2 to 6 METs for TP) and relative intensity (30, 40, 50, 60, 70, and 80% for PP and 40-80% for TP). The cut-points for moderate-to-vigorous physical activity was defined as ≥9515 vector magnitude counts per minute (VMC) for PP and ≥4887 VMC/min for TP.

CONCLUSION

This study presents cut-points for wrist-worn accelerometers in both PP and TP, which could be used in clinical practice to describe physical activity patterns and time spent at different intensity levels.

Smartphone-Delivered Peer Physical Activity Counseling Program for Individuals With Spinal Cord Injury: Protocol for Development and Pilot Evaluation

Background

Leisure-time physical activity (LTPA) is a critical component of a healthy lifestyle for individuals with spinal cord injury (SCI). However, most individuals are not sufficiently active to accrue health benefits. The Active Living Lifestyles program for individuals with SCI who use manual wheelchairs (ALLWheel) targets important psychological factors that are associated with LTPA uptake and adherence while overcoming some barriers associated with participation restrictions.

Objective

The goal of the paper is to describe the protocol for the development and evaluation of the ALLWheel program for individuals with SCI who use manual wheelchairs.

Methods

The first three stages of the Medical Research Council framework for developing and evaluating complex interventions (ie, preclinical, modeling, exploratory) are described. The preclinical phase will consist of scoping and systematic reviews and review of theory. The intervention will be modeled by expert opinions and consensus through focus groups and Delphi surveys with individuals with SCI, clinicians, and community partners. Finally, the feasibility and potential influence of the ALLWheel program on LTPA and psychological outcomes will be evaluated.

Results

This project is funded by the Craig H Neilsen Foundation, the Fonds de Recherche du Québec–Santé, and the Canadian Disability Participation Project and is currently underway.

Conclusions

Using peer trainers and mobile phone technology may help to cultivate autonomy-supportive environments that also enhance self-efficacy. Following a framework for developing and evaluating a novel intervention that includes input from stakeholders at all stages will ensure the final product (ie, a replicable intervention) is desirable to knowledge users and ready for evaluation in a randomized controlled trial. If effective, the ALLWheel program has the potential to reach a large number of individuals with SCI to promote LTPA uptake and adherence.

International Registered Report Identifier (IRRID)

DERR1-10.2196/10798

Use of a Low-Cost, Chest-Mounted Accelerometer to Evaluate Transfer Skills of Wheelchair Users During Everyday Activities: Observational Study

Background

Transfers are an important skill for many wheelchair users (WU). However, they have also been related to the risk of falling or developing upper limb injuries. Transfer abilities are usually evaluated in clinical settings or biomechanics laboratories, and these methods of assessment are poorly suited to evaluation in real and unconstrained world settings where transfers take place.

Objective

The objective of this paper is to test the feasibility of a system based on a wearable low-cost sensor to monitor transfer skills in real-world settings.

Methods

We collected data from 9 WU wearing triaxial accelerometer on their chest while performing transfers to and from car seats and home furniture. We then extracted significant features from accelerometer data based on biomechanical considerations and previous relevant literature and used machine learning algorithms to evaluate the performance of wheelchair transfers and detect their occurrence from a continuous time series of data.

Results

Results show a good predictive accuracy of support vector machine classifiers when determining the use of head-hip relationship (75.9%) and smoothness of landing (79.6%) when the starting and ending of the transfer are known. Automatic transfer detection reaches performances that are similar to state of the art in this context (multinomial logistic regression accuracy 87.8%). However, we achieve these results using only a single sensor and collecting data in a more ecological manner.

Conclusions

The use of a single chest-placed accelerometer shows good predictive accuracy for algorithms applied independently to both transfer evaluation and monitoring. This points to the opportunity for designing ubiquitous-technology based personalized skill development interventions for WU. However, monitoring transfers still require the use of external inputs or extra sensors to identify the start and end of the transfer, which is needed to perform an accurate evaluation.

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.

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.

Validity of Fitbit's active minutes as compared with a research-grade accelerometer and self-reported measures

Objectives

The main purpose of the study was to assess the validity between the Fitbit and ActiGraph GT3X+ accelerometer. The specific aims were to determine the: (1) concurrent validity between the various models of the Fitbit and the GTX3+ accelerometer as the criterion measure for: number of steps and active minutes averaged over a single-day and 7-day period; (2) validity of the two devices with the International Physical Activity Questionnaire (IPAQ) for the number of daily active minutes performed.

Methods

Fifty-three subjects wore a Fitbit and ActiGraph concurrently for 7 days. Data were analysed using correlation coefficients, t-tests to assess mean comparisons and Bland-Altman plots to determine agreement between the Fitbit and the ActiGraph.

Results

The correlations between the Fitbit and ActiGraph for steps per day and per 7 days were r=0.862 and 0.820, respectively with significant mean differences between both devices. Bland-Altman analyses revealed agreement between the Fitbit and the ActiGraph for 7-day active minutes only. The correlations between the Fitbit and ActiGraph for active minutes per day and per 7 days were r=0.695 and r=0.658, respectively, with no significant mean differences between both devices. No significant correlations were found between the IPAQ and the other two devices.

Conclusions

The data produced by the Fitbit were consistent with the ActiGraph when the means of each device were compared over the 1-day and 7-day time periods. However, Bland-Altman analyses revealed that the Fitbit agreed with the ActiGraph when used to measure physical activity levels over a 7-day span only.

Comorbidity and physical activity in people with paraplegia: a descriptive cross-sectional study

STUDY DESIGN

Descriptive cross-sectional study.

SETTING

The study was conducted in the Spinal Cord Injury Unit of the University Vall d'Hebron Hospital and in the Physical Education and Sports Department of the University of Valencia.

OBJECTIVES

The aim of this study was to quantify the presence of comorbidities in spinal cord injury (SCI) subjects who did or did not perform regular physical activity (PA) and to identify the relationship between PA and the level of comorbidity.

METHODS

The sample consisted of patients with complete motor SCI (T2-T12), who were fitted with an accelerometer attached to the non-dominant wrist for a period of 1 week. The clinical and blood analytic variables were selected by an expert panel.

RESULTS

In the exploratory analysis, we have found differences in the total number of pathologies between active and inactive patients, with fewer total pathologies in the active patient group. An association was found between the PA level and diabetes mellitus (; P=0.047; φ=0.25). We also observed an association between the cardioprotector level of high-density lipoprotein (HDL)-cholesterol and PA level (; P=0.057; Φ0.24).

CONCLUSIONS

Our results suggest that patients considered active showed lower total comorbidity than inactive patients and higher protection levels against developing cardiovascular comorbidity.

The Smartphone Peer Physical Activity Counseling (SPPAC) Program for Manual Wheelchair Users: Protocol of a Pilot Randomized Controlled Trial

Background

Physical activity (PA) must be performed regularly to accrue health benefits. However, the majority of manual wheelchair users do not meet PA recommendations. Existing community-based PA programs for manual wheelchair users appear to work, but effect sizes are small and retention is low. Existing PA programs may not fully implement some psychosocial factors that are strongly linked with PA (eg, autonomy). The use of peers and mobile phone technology in the Smartphone Peer PA Counseling (SPPAC) program represents a novel approach to cultivating a PA-supportive environment for manual wheelchair users.

Objective

The primary objective is to compare change in objective PA between the experimental (SPPAC) and control groups from baseline to postintervention (10 weeks) and follow-up (3 months). Changes in and relationships between subjective PA, wheelchair skills, motivation, self-efficacy (for overcoming barriers to PA for manual wheelchair use), satisfaction of psychological needs for PA, and satisfaction with PA participation will be explored (secondary outcome). Program implementation will be explored (tertiary objective).

Methods

A total of 38 community-living manual wheelchair users (≥18 years) will be recruited in a randomized controlled trial (RCT). Participants in both the control and experimental groups will receive existing PA guidelines. Participants in the experimental group will also receive the SPPAC program: 14 sessions (~30 min) over a 10-week period delivered by a peer trainer using a mobile phone. PA activities will be based on individuals’ preferences and goals. Implementation of important theoretical variables will be enforced through a peer-trainer checklist. Outcomes for objective PA (primary) and subjective PA, wheelchair skills, motivation, self-efficacy, satisfaction of psychological needs, and satisfaction with participation will be collected at three time points (baseline, postintervention, follow-up). Multiple imputations will be used to treat missing data. A mixed-model ANCOVA will be conducted, controlling for covariates (primary and secondary objectives). The strength and direction of the relationships between the primary and secondary outcomes will be explored (secondary objective). Descriptive and content analysis will be used to appraise program implementation (tertiary objective).

Results

Funding has been obtained from the Craig Neilsen Foundation and the Canadian Disability Participation Project, with additional funds being sought from the Canadian Institute for Health Research and Fonds de Recherche du Québec-Santé. Pilot evaluation of intervention implementation is currently underway, with enrollment anticipated to begin early 2018.

Conclusions

There may be substantial benefits for the SPPAC program including limited burden on health care professionals, decreased barriers (eg. accessibility, transportation), development of peer social supports, and potential cost savings related to physical inactivity. Before conducting a large and expensive multisite RCT within a small heterogeneous population of manual wheelchair users, a pilot study affords a prudent step to establishing an adequate study protocol and implementation strategies.

Trial Registration

ClinicalTrials.gov NCT02826707; https://clinicaltrials.gov/ct2/show/NCT02826707 (Archived by WebCite at http://www.webcitation.org/6pqIc14dU)

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.

Estimation of Energy Expenditure for Wheelchair Users Using a Physical Activity Monitoring System

OBJECTIVE

To develop and evaluate energy expenditure (EE) estimation models for a physical activity monitoring system (PAMS) in manual wheelchair users with spinal cord injury (SCI).

DESIGN

Cross-sectional study.

SETTING

University-based laboratory environment, a semistructured environment at the National Veterans Wheelchair Games, and the participants' home environments.

PARTICIPANTS

Volunteer sample of manual wheelchair users with SCI (N=45).

INTERVENTION

Participants were asked to perform 10 physical activities (PAs) of various intensities from a list. The PAMS consists of a gyroscope-based wheel rotation monitor (G-WRM) and an accelerometer device worn on the upper arm or on the wrist. Criterion EE using a portable metabolic cart and raw sensor data from PAMS were collected during each of these activities.

MAIN OUTCOME MEASURES

Estimated EE using custom models for manual wheelchair users based on either the G-WRM and arm accelerometer (PAMS-Arm) or the G-WRM and wrist accelerometer (PAMS-Wrist).

RESULTS

EE estimation performance for the PAMS-Arm (average error ± SD: -9.82%±37.03%) and PAMS-Wrist (-5.65%±32.61%) on the validation dataset indicated that both PAMS-Arm and PAMS-Wrist were able to estimate EE for a range of PAs with <10% error. Moderate to high intraclass correlation coefficients (ICCs) indicated that the EE estimated by PAMS-Arm (ICC3,1=.82, P<.05) and PAMS-Wrist (ICC3,1=.89, P<.05) are consistent with the criterion EE.

CONCLUSIONS

Availability of PA monitors can assist wheelchair users to track PA levels, leading toward a healthier lifestyle. The new models we developed can estimate PA levels in manual wheelchair users with SCI in laboratory and community settings.

Active paraplegics are protected against exercise-induced oxidative damage through the induction of antioxidant enzymes

STUDY DESIGN

Experimental study.

OBJECTIVES

Exercise improves functional capacity in spinal cord injury (SCI). However, exhaustive exercise, especially when sporadic, is linked to the production of reactive oxygen species that may have a detrimental effect on SCI. We aimed to study the effect of a single bout of exhaustive exercise on systemic oxidative stress parameters and on the expression of antioxidant enzymes in individuals with paraplegia.

SETTING

The study was conducted in the Physical Therapy department and the Physical Education and Sports department of the University of Valencia.

METHODS

Sixteen paraplegic subjects were submitted to a graded exercise test (GET) until volitional exhaustion. They were divided into active or non-active groups. Blood samples were drawn immediately, 1 and 2 h after the GET. We determined plasma malondialdehyde (MDA) and protein carbonylation as markers of oxidative damage. Antioxidant gene expression (catalase and glutathione peroxidase-GPx) was determined in peripheral blood mononuclear cells.

RESULTS

We found a significant increase in plasma MDA and protein carbonyls immediately after the GET (P<0.05). This increment correlated significantly with the lactate levels. Active paraplegics showed lower levels of exercise-induced oxidative damage (P<0.05) and higher exercise-induced catalase (P<0.01) and GPx (P<0.05) gene expression after the GET.

CONCLUSIONS

These results suggest that exercise training may be useful in SCI patients to develop systemic antioxidant defenses that may protect them against exercise-induced oxidative damage.

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.

Identifying physical activity type in manual wheelchair users with spinal cord injury by means of accelerometers

STUDY DESIGN

This was a cross-sectional study.

OBJECTIVES

The main objective of this study was to develop and test classification algorithms based on machine learning using accelerometers to identify the activity type performed by manual wheelchair users with spinal cord injury (SCI).

SETTING

The study was conducted in the Physical Therapy department and the Physical Education and Sports department of the University of Valencia.

METHODS

A total of 20 volunteers were asked to perform 10 physical activities, lying down, body transfers, moving items, mopping, working on a computer, watching TV, arm-ergometer exercises, passive propulsion, slow propulsion and fast propulsion, while fitted with four accelerometers placed on both wrists, chest and waist. The activities were grouped into five categories: sedentary, locomotion, housework, body transfers and moderate physical activity. Different machine learning algorithms were used to develop individual and group activity classifiers from the acceleration data for different combinations of number and position of the accelerometers.

RESULTS

We found that although the accuracy of the classifiers for individual activities was moderate (55-72%), with higher values for a greater number of accelerometers, grouped activities were correctly classified in a high percentage of cases (83.2-93.6%).

CONCLUSIONS

With only two accelerometers and the quadratic discriminant analysis algorithm we achieved a reasonably accurate group activity recognition system (>90%). Such a system with the minimum of intervention would be a valuable tool for studying physical activity in individuals with SCI.

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

PURPOSE

To assess the validity of two accelerometer devices, at two different anatomical locations, for the prediction of physical activity energy expenditure (PAEE) in manual wheelchair users (MWUs).

METHODS

Seventeen MWUs (36 ± 10 yrs, 72 ± 11 kg) completed ten activities; resting, folding clothes, propulsion on a 1% gradient (3,4,5,6 and 7 km·hr-1) and propulsion at 4km·hr-1 (with an additional 8% body mass, 2% and 3% gradient) on a motorised wheelchair treadmill. GT3X+ and GENEActiv accelerometers were worn on the right wrist (W) and upper arm (UA). Linear regression analysis was conducted between outputs from each accelerometer and criterion PAEE, measured using indirect calorimetry. Subsequent error statistics were calculated for the derived regression equations for all four device/location combinations, using a leave-one-out cross-validation analysis.

RESULTS

Accelerometer outputs at each anatomical location were significantly (p < .01) associated with PAEE (GT3X+-UA; r = 0.68 and GT3X+-W; r = 0.82. GENEActiv-UA; r = 0.87 and GENEActiv-W; r = 0.88). Mean ± SD PAEE estimation errors for all activities combined were 15 ± 45%, 14 ± 50%, 3 ± 25% and 4 ± 26% for GT3X+-UA, GT3X+-W, GENEActiv-UA and GENEActiv-W, respectively. Absolute PAEE estimation errors for devices varied, 19 to 66% for GT3X+-UA, 17 to 122% for GT3X+-W, 15 to 26% for GENEActiv-UA and from 17.0 to 32% for the GENEActiv-W.

CONCLUSION

The results indicate that the GENEActiv device worn on either the upper arm or wrist provides the most valid prediction of PAEE in MWUs. Variation in error statistics between the two devices is a result of inherent differences in internal components, on-board filtering processes and outputs of each device.

Lifestyles of Adult Omani Women: Cross-sectional study on physical activity and sedentary behaviour

OBJECTIVES

This study aimed to investigate the lifestyles of adult Omani women with regards to physical activity (PA) levels and sedentary behaviour (SB).

METHODS

The study was carried out between May and June 2013 and included a total of 277 healthy women aged 18-48 years from five governorates in Oman. Total, moderate and vigorous PA levels and walking were self-reported by participants using the short form of the International Physical Activity Questionnaire. SB (total sitting time and different types of sitting time) was self-reported using the Domain-Specific Sitting Time Questionnaire on both working and non-working days. PA levels and SB were also objectively measured among 86 of the participants using an accelerometer.

RESULTS

The self-reported median ± interquartile range (IQR) total PA was 1,516 ± 3,392 metabolic equivalent of task minutes/week. The self-reported median ± IQR total sitting time was 433 ± 323 minutes/day and 470 ± 423 minutes/day for working and non-working days, respectively. Sitting at work on working days and sitting during leisure activities on non-working days formed the greatest proportion of total sitting time. Overall, accelerometer results indicated that participants spent 62% of their time involved in SB, 35% in light PA and only 3% in moderate to vigorous PA.

CONCLUSION

Sedentary lifestyles were common among the adult Omani women studied. Lack of PA and increased SB is known to increase the risk of metabolic syndrome and obesity. The use of accelerometers to monitor PA and SB among different groups in Oman is highly recommended in order to accurately assess the lifestyle risks of this population.

Accelerometer output and its association with energy expenditure during manual wheelchair propulsion

STUDY DESIGN

This is an experimental design.

OBJECTIVES

This study examined the association between rates of energy expenditure (that is, oxygen consumption (VO2)) and accelerometer counts (that is, vector magnitude (VM)) across a range of speeds during manual wheelchair propulsion on a motor-driven treadmill. Such an association allows for the generation of cutoff points for quantifying the time spent in moderate-to-vigorous physical activity (MVPA) during manual wheelchair propulsion.

SETTING

The study was conducted in the University Laboratory.

METHODS

Twenty-four manual wheelchair users completed a 6-min period of seated rest and three 6-min periods of manual wheelchair propulsion on a motor-driven wheelchair treadmill. The 6-min periods of wheelchair propulsion corresponded with three treadmill speeds (1.5, 3.0 and 4.5 mph) that elicited a range of physical activity intensities. Participants wore a portable metabolic unit and accelerometers on both wrists. Primary outcome measures included steady-state VO2 and VM, and the strength of association between VO2 and VM was based on the multiple correlation and squared multiple correlation coefficients from linear regression analyses.

RESULTS

Strong linear associations were established between VO2 and VM for the left (R=0.93±0.44; R2=0.87±0.19), right (R=0.95±0.37; R2=0.90±0.14) and combined (R=0.94±0.38; R2=0.88±0.15) accelerometers. The linear relationship between VO2 and VM for the left, right and combined wrists yielded cutoff points for MVPA of 3659 ±1302, 3630±1403 and 3644±1339 counts min(-1), respectively.

CONCLUSION

We provide cutoff points based on the linear association between energy expenditure and accelerometer counts for estimating time spent in MVPA during manual wheelchair propulsion using wrist-worn accelerometry. The similarity across wrist location permits flexibility in selecting a location for wrist accelerometry placement.