"What Is a Step?" Differences in How a Step Is Detected among Three Popular Activity Monitors That Have Impacted Physical Activity Research

Objective Assessment of Physical Activity at Home Using a Novel Floor-Vibration Monitoring System: Validation and Comparison With Wearable Activity Trackers and Indirect Calorimetry Measurements

BACKGROUND

The self-monitoring of physical activity is an effective strategy for promoting active lifestyles. However, accurately assessing physical activity remains challenging in certain situations. This study evaluates a novel floor-vibration monitoring system to quantify housework-related physical activity.

OBJECTIVE

This study aims to assess the validity of step-count and physical behavior intensity predictions of a novel floor-vibration monitoring system in comparison with the actual number of steps and indirect calorimetry measurements. The accuracy of the predictions is also compared with that of research-grade devices (ActiGraph GT9X).

METHODS

The Ocha-House, located in Tokyo, serves as an independent experimental facility equipped with high-sensitivity accelerometers installed on the floor to monitor vibrations. Dedicated data processing software was developed to analyze floor-vibration signals and calculate 3 quantitative indices: floor-vibration quantity, step count, and moving distance. In total, 10 participants performed 4 different housework-related activities, wearing ActiGraph GT9X monitors on both the waist and wrist for 6 minutes each. Concurrently, floor-vibration data were collected, and the energy expenditure was measured using the Douglas bag method to determine the actual intensity of activities.

RESULTS

Significant correlations (P<.001) were found between the quantity of floor vibrations, the estimated step count, the estimated moving distance, and the actual activity intensities. The step-count parameter extracted from the floor-vibration signal emerged as the most robust predictor (r2=0.82; P<.001). Multiple regression models incorporating several floor-vibration-extracted parameters showed a strong association with actual activity intensities (r2=0.88; P<.001). Both the step-count and intensity predictions made by the floor-vibration monitoring system exhibited greater accuracy than those of the ActiGraph monitor.

CONCLUSIONS

Floor-vibration monitoring systems seem able to produce valid quantitative assessments of physical activity for selected housework-related activities. In the future, connected smart home systems that integrate this type of technology could be used to perform continuous and accurate evaluations of physical behaviors throughout the day.

Current Knowledge about ActiGraph GT9X Link Activity Monitor Accuracy and Validity in Measuring Steps and Energy Expenditure: A Systematic Review

Over recent decades, wearable inertial sensors have become popular means to quantify physical activity and mobility. However, research assessing measurement accuracy and precision is required, especially before using device-based measures as outcomes in trials. The GT9X Link is a recent activity monitor available from ActiGraph, recognized as a "gold standard" and previously used as a criterion measure to assess the validity of various consumer-based activity monitors. However, the validity of the ActiGraph GT9X Link is not fully elucidated. A systematic review was undertaken to synthesize the current evidence for the criterion validity of the ActiGraph GT9X Link in measuring steps and energy expenditure. This review followed the PRISMA guidelines and eight studies were included with a combined sample size of 558 participants. We found that (1) the ActiGraph GT9X Link generally underestimates steps; (2) the validity and accuracy of the device in measuring steps seem to be influenced by gait speed, device placement, filtering process, and monitoring conditions; and (3) there is a lack of evidence regarding the accuracy of step counting in free-living conditions and regarding energy expenditure estimation. Given the limited number of included studies and their heterogeneity, the present review emphasizes the need for further validation studies of the ActiGraph GT9X Link in various populations and in both controlled and free-living settings.

Effects of ActiGraph's filter, epoch length and non-wearing time algorithm on step counts in people with COPD

The influence of the ActiGraph® processing criteria on estimating step counts in chronic obstructive pulmonary disease (COPD) remains uncertain. This study aimed to assess the influence of filters, epoch lengths and non-wearing time (NWT) algorithms on steps/day in people with COPD. ActiGraph GT3X+ was worn on the waist for seven days. Steps were detected using different filters (normal and low-frequency extension [LFE]), epoch lengths (15s and 60s), and NWT algorithms (Choi and Troiano). Linear mixed-effects model was applied to assess the effects of filter, epoch length, NWT algorithm on steps/day. Lin's concordance correlation and Bland-Altman were used to measure agreement. A total of 136 people with COPD (107 male; 69 ± 8 years; FEV1 51 ± 17% predicted) were included. Significant differences were found between filters (p < 0.001), but not between epoch lengths or NWT algorithms. The LFE increased, on average, approximately 7500 steps/day compared to the normal filter (p < 0.001). Agreement was poor (<0.3) and proportional bias was significant when comparing steps/day computed with different filters, regardless of the epoch length and NWT algorithm. Filter choice but not epoch lengths or NWT algorithms seem to impact measurement of steps/day. Future studies are needed to recommend the most accurate technique for measuring steps/day in people with COPD.

Comparative Analysis of ActiGraph Step Counting Methods in Adults: A Systematic Literature Review and Meta-Analysis

PURPOSE

The primary aim of this study was to compare steps per day across ActiGraph models, wear locations, and filtering methods. A secondary aim was to compare ActiGraph steps per day to those estimated by the ankle-worn StepWatch.

METHODS

We conducted a systematic literature review to identify studies of adults published before May 12, 2022, that compared free-living steps per day of ActiGraph step counting methods and studies that compared ActiGraph to StepWatch. Random-effects meta-analysis compared ActiGraph models, wear locations, filter mechanisms, and ActiGraph to StepWatch steps per day. A sensitivity analysis of wear location by younger and older age was included.

RESULTS

Twelve studies, with 46 comparisons, were identified. When worn on the hip, the AM-7164 recorded 123% of the GT series steps (no low-frequency extension (no LFE) or default filter). However, the AM-7164 recorded 72% of the GT series steps when the LFE was enabled. Independent of the filter used (i.e., LFE, no LFE), ActiGraph GT series monitors captured more steps on the wrist than on the hip, especially among older adults. Enabling the LFE on the GT series monitors consistently recorded more steps, regardless of wear location. When using the default filter (no LFE), ActiGraph recorded fewer steps than StepWatch (ActiGraph on hip 73% and ActiGraph on wrist 97% of StepWatch steps). When LFE was enabled, ActiGraph recorded more steps than StepWatch (ActiGraph on the hip, 132%; ActiGraph on the wrist, 178% of StepWatch steps).

CONCLUSIONS

The choice of ActiGraph model, wear location, and filter all impacted steps per day in adults. These can markedly alter the steps recorded compared with a criterion method (StepWatch). This review provides critical insights for comparing studies using different ActiGraph step counting methods.

Physical activity measurements in individuals with interstitial lung disease: a systematic review and meta-analysis

BACKGROUND

Physical activity (PA) measurements are becoming common in interstitial lung disease (ILD); however, standardisation has not been achieved. We aimed to systematically review PA measurement methods, present PA levels and provide practical recommendations on PA measurement in ILD.

METHODS

We searched four databases up to November 2022 for studies assessing PA in ILD. We collected information about the studies and participants, the methods used to measure PA, and the PA metrics. Studies were scored using 12 items regarding PA measurements to evaluate the reporting quality of activity monitor use.

RESULTS

In 40 of the included studies, PA was measured using various devices or questionnaires with numerous metrics. Of the 33 studies that utilised activity monitors, a median of five out of 12 items were not reported, with the definition of nonwear time being the most frequently omitted. The meta-analyses showed that the pooled means (95% CI) of steps, time spent in moderate to vigorous PA, total energy expenditure and sedentary time were 5215 (4640-5791) steps·day^-1, 82 (58-106) min·day^-1, 2130 (1847-2412) kcal·day^-1 and 605 (323-887) min·day^-1, respectively, with considerable heterogeneity.

CONCLUSION

The use of activity monitors and questionnaires in ILD lacks consistency. Improvement is required in the reporting quality of PA measurement methods using activity monitors.

Continuous Monitoring of Health and Mobility Indicators in Patients with Cardiovascular Disease: A Review of Recent Technologies

Cardiovascular diseases kill 18 million people each year. Currently, a patient's health is assessed only during clinical visits, which are often infrequent and provide little information on the person's health during daily life. Advances in mobile health technologies have allowed for the continuous monitoring of indicators of health and mobility during daily life by wearable and other devices. The ability to obtain such longitudinal, clinically relevant measurements could enhance the prevention, detection and treatment of cardiovascular diseases. This review discusses the advantages and disadvantages of various methods for monitoring patients with cardiovascular disease during daily life using wearable devices. We specifically discuss three distinct monitoring domains: physical activity monitoring, indoor home monitoring and physiological parameter monitoring.

The Analytical and Clinical Validity of the pfSTEP Digital Biomarker of the Susceptibility/Risk of Declining Physical Function in Community-Dwelling Older Adults

Measures of stepping volume and rate are common outputs from wearable devices, such as accelerometers. It has been proposed that biomedical technologies, including accelerometers and their algorithms, should undergo rigorous verification as well as analytical and clinical validation to demonstrate that they are fit for purpose. The aim of this study was to use the V3 framework to assess the analytical and clinical validity of a wrist-worn measurement system of stepping volume and rate, formed by the GENEActiv accelerometer and GENEAcount step counting algorithm. The analytical validity was assessed by measuring the level of agreement between the wrist-worn system and a thigh-worn system (activPAL), the reference measure. The clinical validity was assessed by establishing the prospective association between the changes in stepping volume and rate with changes in physical function (SPPB score). The agreement of the thigh-worn reference system and the wrist-worn system was excellent for total daily steps (CCC = 0.88, 95% CI 0.83-0.91) and moderate for walking steps and faster-paced walking steps (CCC = 0.61, 95% CI 0.53-0.68 and 0.55, 95% CI 0.46-0.64, respectively). A higher number of total steps and faster paced-walking steps was consistently associated with better physical function. After 24 months, an increase of 1000 daily faster-paced walking steps was associated with a clinically meaningful increase in physical function (0.53 SPPB score, 95% CI 0.32-0.74). We have validated a digital susceptibility/risk biomarker-pfSTEP-that identifies an associated risk of low physical function in community-dwelling older adults using a wrist-worn accelerometer and its accompanying open-source step counting algorithm.

Opal Actigraphy (Activity and Sleep) Measures Compared to ActiGraph: A Validation Study

Physical activity and sleep monitoring in daily life provide vital information to track health status and physical fitness. The aim of this study was to establish concurrent validity for the new Opal Actigraphy solution in relation to the widely used ActiGraph GT9X for measuring physical activity from accelerometry epic counts (sedentary to vigorous levels) and sleep periods in daily life. Twenty participants (age 56 + 22 years) wore two wearable devices on each wrist for 7 days and nights, recording 3-D accelerations at 30 Hz. Bland-Altman plots and intraclass correlation coefficients (ICCs) assessed validity (agreement) and test-retest reliability between ActiGraph and Opal Actigraphy sleep durations and activity levels, as well as between the two different versions of the ActiGraph. ICCs showed excellent reliability for physical activity measures and moderate-to-excellent reliability for sleep measures between Opal versus Actigraph GT9X and between GT3X versus GT9X. Bland-Altman plots and mean absolute percentage error (MAPE) also show a comparable performance (within 10%) between Opal and ActiGraph and between the two ActiGraph monitors across activity and sleep measures. In conclusion, physical activity and sleep measures using Opal Actigraphy demonstrate performance comparable to that of ActiGraph, supporting concurrent validation. Opal Actigraphy can be used to quantify activity and monitor sleep patterns in research and clinical studies.

Agreement of Step-Based Metrics From ActiGraph and ActivPAL Accelerometers Worn Concurrently Among Older Adults

Purpose

Our study evaluated the agreement of mean daily step counts, peak 1-min cadence, and peak 30-min cadence between the hip-worn ActiGraph GT3X+ accelerometer, using the normal filter (AG_N) and the low frequency extension (AG_LFE), and the thigh-worn activPAL3 micro (AP) accelerometer among older adults.

Methods

Nine-hundred and fifty-three older adults (≥65 years) were recruited to wear the ActiGraph device concurrently with the AP for 4-7 days beginning in 2016. Using the AP as the reference measure, device agreement for each step-based metric was assessed using mean differences (AG_N - AP and AG_LFE - AP), mean absolute percentage error (MAPE), and Pearson and concordance correlation coefficients.

Results

For AG_N - AP, the mean differences and MAPE were: daily steps -1,851 steps/day and 27.2%, peak 1-min cadence -16.2 steps/min and 16.3%, and peak 30-min cadence -17.7 steps/min and 24.0%. Pearson coefficients were .94, .85, and .91 and concordance coefficients were .81, .65, and .73, respectively. For AG_LFE - AP, the mean differences and MAPE were: daily steps 4,968 steps/day and 72.7%, peak 1-min cadence -1.4 steps/min and 4.7%, and peak 30-min cadence 1.4 steps/min and 7.0%. Pearson coefficients were .91, .91, and .95 and concordance coefficients were .49, .91, and .94, respectively.

Conclusions

Compared with estimates from the AP, the AG_N underestimated daily step counts by approximately 1,800 steps/day, while the AG_LFE overestimated by approximately 5,000 steps/day. However, peak step cadence estimates generated from the AG_LFE and AP had high agreement (MAPE ≤ 7.0%). Additional convergent validation studies of step-based metrics from concurrently worn accelerometers are needed for improved understanding of between-device agreement.

Functional and Symptomatic Clinical Trial Endpoints: The HFC-ARC Scientific Expert Panel

The Heart Failure Academic Research Consortium is a partnership between the Heart Failure Collaboratory (HFC) and the Academic Research Consortium (ARC) composed of patients, academic investigators from the United States and Europe, the U.S. Food and Drug Administration, the National Institutes of Health, payers, and industry. Members discussed the measure, remote capture, and clinical utility of functional and quality-of-life endpoints for use in clinical trials of heart failure and cardiovascular therapeutics, with the goal of improving the efficiency of heart failure and cardiovascular clinical research, evidence generation, and thereby patient quality of life, functional status, and survival. Assessments of patient-reported outcomes and maximal and submaximal exercise tolerance are standardized and validated, but actigraphy remains inconsistent as a potential endpoint. This paper details those discussions and consensus recommendations.

Optimal Number of Steps per Day to Prevent All-Cause Mortality in People With Prediabetes and Diabetes

OBJECTIVE

We aimed to examine the dose-response associations between the number of steps per day and all-cause mortality among adults with prediabetes and diabetes.

RESEARCH DESIGN AND METHODS

This prospective study used data from 1,194 U.S. adults with prediabetes and 493 with diabetes for whom accelerometer-derived steps per day could be retrieved. Mortality was ascertained through the National Death Index (February 25, 2019). Splines were used to assess the dose-response associations between steps per day and all-cause mortality.

RESULTS

Over ∼9 years of follow-up, 200 adults with prediabetes and 138 with diabetes died. Nonlinear associations akin to an L shape were observed. We estimated an optimal dose of ∼10,000 steps per day to reduce the risk of all-cause mortality for both individuals with prediabetes and those with diabetes.

CONCLUSIONS

Accumulating more steps per day up to ∼10,000 steps per day may lower the risk of all-cause mortality of adults with prediabetes and diabetes.

Step Count in Patients With Lumbar Spinal Stenosis: Accuracy During Walking and Nonwalking Activities

STUDY DESIGN

This is a method development and validation study.

OBJECTIVES

The purpose of this study was to develop and test a method for step detection using accelerometer data in patients with lumbar spinal stenosis (LSS). There are 2 objectives: (1) to describe a method for step detection from accelerations measured at the wrist, hip, lower back, thigh and ankle; (2) to assess the accuracy of the method during walking with and without walking aids and during nonwalking activities.

SUMMARY OF BACKGROUND DATA

Loss of walking ability is one of the main symptoms of LSS, and there is no validated measure to assess walking activity in daily living in patients with LSS.

MATERIALS AND METHODS

Thirty patients with LSS performed a standardized movement protocol that included walking with and without walking aids and performing nonwalking activities while wearing accelerometers on five different wear-sites. After the walking tests, a method was designed for optimal step detection and compared with a gold standard of observed step count.

RESULTS

The method for step detection applied to accelerations from the lower back, hip, thigh, and ankle provided an accurate step counts during continuous walking without walking aids. Accuracy diminished at all wear-sites when walking with walking aids, except the ankle. The wrist provided the most inaccurate step count, and the accelerometers on the thigh and ankle were prone to falsely detecting steps during bicycling.

CONCLUSION

The ankle-worn accelerometer provided the most accurate step count, but wrongly registered steps during nonwalking activities. The developed step detection method shows potential as a measure of walking activity why further development and testing under free-living conditions should be performed.

Linking Gait Biomechanics and Daily Steps After ACL Reconstruction

PURPOSE

Aberrant biomechanics and altered loading frequency are associated with poor knee joint health in osteoarthritis development. After anterior cruciate ligament reconstruction (ACLR), individuals demonstrate underloading (lesser vertical ground reaction force (vGRF)) with stiffened knee gait biomechanics (lesser knee extension moment (KEM) and knee flexion angle) and take fewer daily steps as early as 6 months after surgery. The purpose of this cross-sectional laboratory study is to compare gait biomechanics throughout stance between individuals 6-12 months after ACLR who take the lowest, moderate, and highest daily steps.

METHODS

Individuals with primary, unilateral history of ACLR between the ages of 16 and 35 yr were included (n = 36, 47% females; age, 21 ± 5 yr; months since ACLR, 8 ± 2). Barefoot gait biomechanics of vGRF (body weight), KEM (body weight × height), and knee flexion angle during stance were collected and time normalized. Average daily steps were collected via a waist-mounted accelerometer in free-living settings over 7 d. Participants were separated into tertiles based on lowest daily steps (3326-6042 daily steps), moderate (6043-8198 daily steps), and highest (8199-12,680 daily steps). Biomechanical outcomes of the ACLR limb during stance were compared between daily step groups using functional waveform gait analyses.

RESULTS

There were no significant differences in sex, body mass index, age, or gait speed between daily step groups. Individuals with the lowest daily steps walk with lesser vGRF and lesser KEM during weight acceptance, and lesser knee flexion angle throughout stance in the ACLR limb compared with individuals with highest and moderate daily steps.

CONCLUSIONS

After ACLR, individuals who take the fewest daily steps also walk with lesser vGRF during weight acceptance and a stiffened knee strategy throughout stance. These results highlight complex interactions between joint loading parameters after ACLR.

Stop motion: using high resolution spatiotemporal data to estimate and locate stationary and movement behaviour in an office workplace

Prolonged periods of stationary behaviour, a common occurrence in many office workplaces, are linked with a range of physical disorders. Investigating the physical context of this behaviour may be a key to developing effective interventions. This study aimed to estimate and locate the stationary and movement behaviours of office workers (n = 10) by segmenting spatiotemporal data collected over 5 days in an office work-based setting. The segmentation method achieved a balanced accuracy ≥85.5% for observation classification and ≥90% for bout classification when compared to reference data. The results show the workers spent the majority of their time stationary (Mean = 86.4%) and had on average, 28.4 stationary and 25.9 moving bouts per hour. While these findings accord with other studies, the segmented data was also visualised, revealing that the workers were stationary for periods ≥5 min at multiple locations and these locations changed across time. Practitioner Summary: This study applied a data segmentation method to classify stationary and moving behaviours from spatiotemporal data collected in an office workplace. The segmented data revealed not only what behaviours occurred but also their location, duration, and time. Segmenting spatiotemporal data may add valuable physical context to aid workplace research.

Adaptation and virtual feasibility pilot of a mindfulness-based lifestyle program targeting modifiable dementia risk factors in older adults

OBJECTIVES

We developed a group-based program (My Healthy Brain, MHB) to engage older adults at-risk for dementia in healthy lifestyles. We report on a two-part study to adapt MHB by incorporating mindfulness skills, using mobile health technology to monitor and reinforce behaviors, and delivering it via live video.

METHODS

Participants were older adults (age ≥ 60) with subjective cognitive decline (SCD) and at least one lifestyle risk factor. In Aim 1 (n = 11, 2 groups), we conducted focus groups to obtain qualitative feedback on proposed adaptations. In Aim 2 (n = 10), we conducted a virtual open pilot with exit interviews to explore the feasibility and outcomes of the adapted MHB.

RESULTS

Thematic analysis revealed: (1) barriers and facilitators to healthy lifestyles, (2) positive impressions of MHB, (3) interest in mindfulness skills, and (4) openness to study technologies. MHB met a-priori feasibility benchmarks and was associated with improvements in cognition, lifestyle (e.g. physical function), and proposed mechanisms (e.g. mindfulness). Exit interviews confirmed high feasibility and satisfaction.

CONCLUSION

The integration of mindfulness, live video, and mobile health technologies was feasible and promising for improving healthier lifestyles. The results inform the next feasibility RCT of MHB to prepare for efficacy testing.

Supplemental data for this article is available online at http://dx.doi.org/10.1080/13607863.2022.2032600.

Validation of the Trackhealth physical activity monitor

ABSTRACT This is a quantitative methodological study for the validation of a research instrument. It aimed to validate the data from the TrackHealth accelerometry device. The sample consisted of 30 adult individuals of both sexes selected by convenience who met the inclusion and exclusion criteria. The physical activity monitors used for the research protocol were the ActiGraph® wGT3X-BT triaxial accelerometer and the TrackHealth accelerometer (TH). The activity protocol consisted of 4 (four) activities (walking at 4.8 and 6.4 km h1 and running at 9.7 and 12 km h1) performed in the laboratory, on an Ibramed treadmill, lasting 5 (five) minutes at each stage. A difference was found between the raw acceleration data of the two devices, however the TrackHealth device showed higher sensitivity at speeds of 4.8 and 6.4 km/h, and a high level of agreement (2.7-2.8%) at the initial speeds of the magnitude vectors. However, there is still a need for improvement in the functioning of the device, so that TrackHealth can be commercialized.

Detailed analysis and comparison of different activity metrics

Actigraphic measurements are an important part of research in different disciplines, yet the procedure of determining activity values is unexpectedly not standardized in the literature. Although the measured raw acceleration signal can be diversely processed, and then the activity values can be calculated by different activity calculation methods, the documentations of them are generally incomplete or vary by manufacturer. These numerous activity metrics may require different types of preprocessing of the acceleration signal. For example, digital filtering of the acceleration signals can have various parameters; moreover, both the filter and the activity metrics can also be applied per axis or on the magnitudes of the acceleration vector. Level crossing-based activity metrics also depend on threshold level values, yet the determination of their exact values is unclear as well. Due to the serious inconsistency of determining activity values, we created a detailed and comprehensive comparison of the different available activity calculation procedures because, up to the present, it was lacking in the literature. We assessed the different methods by analysing the triaxial acceleration signals measured during a 10-day movement of 42 subjects. We calculated 148 different activity signals for each subject’s movement using the combinations of various types of preprocessing and 7 different activity metrics applied on both axial and magnitude data. We determined the strength of the linear relationship between the metrics by correlation analysis, while we also examined the effects of the preprocessing steps. Moreover, we established that the standard deviation of the data series can be used as an appropriate, adaptive and generalized threshold level for the level intersection-based metrics. On the basis of these results, our work also serves as a general guide on how to proceed if one wants to determine activity from the raw acceleration data. All of the analysed raw acceleration signals are also publicly available.

The effect of bariatric surgery on gravitational loading and its impact on bone mass

INTRODUCTION

Mechanical unloading associated with weight loss might be one of the main causes for bariatric surgery (BS) induced bone loss. However, no study has tested this hypothesis through objectively measured accelerometry-derived gravitational loading. We aimed to assess how gravitational loading changes following BS and how this correlates with bone mass losses.

METHODS

Twenty-one patients submitted to gastric bypass were assessed before, 1, 6 and 12 months after BS for areal bone mineral density (BMD), calciotropic hormones, sclerostin, body composition and daily physical activity. Gravitational loading was determined as the sum of ground reaction forces assessed by accelerometer which considered the interaction between weight and daily ambulation.

RESULTS

Mechanical stimuli promoted through the significant increase in steps number counterbalanced the gravitational loading decreases derived from the significant weight loss after BS. Gravitational loading volume decreased between pre-BS and 1 month post-BS (-2215 kN·d^-1; p = .023), but remained stable between 6 and 12 months post-BS, despite decreases on hip (-7.0%; p < .001), femoral neck (-8.8%; p < .001) and lumbar spine (-5.2%; p < .001) BMD. Serum sclerostin increased from pre-BS to 1 month post-BS (+0.118 ng·mL^-1; p = .021), returning to pre-BS levels 6 months after surgery. Neither vitamin D nor parathyroid hormone were affected by BS. Weight variation was a predictor of BMD decreases at total hip (R² = 0.06; p = .026) and femoral neck (R² = 0.12; p = .022), whereas daily gravitational loading volume was not. Fat and lean mass changes were also predictors of BMD decrease at total hip (R² = 0.05; p = .031) and femoral neck (R² = 0.14; p = .010), respectively.

CONCLUSION

Our findings suggest that gravitational loading only decreased during the first month after surgery remaining stable thereafter, and these changes do not seem to explain BS-induced bone loss. The association between weight and bone loss seems to result from other physiological aspects, fat and lean mass loss, rather than from gravitational loading decrease.

Step detection and energy expenditure at different speeds by three accelerometers in a controlled environment

Physical activity (PA) is one of the most efficient ways to prevent obesity and its associated diseases worldwide. In the USA, less than 10% of the adult population were able to meet the PA recommendations when accelerometers were used to assess PA habituation. Accelerometers significantly differ from each other in step recognition and do not reveal raw data. The aim of our study was to compare a novel accelerometer, Sartorio Xelometer, which enables to gather raw data, with existing accelerometers ActiGraph GT3X+ and activPAL in terms of step detection and energy expenditure estimation accuracy. 53 healthy subjects were divided into 2 cohorts (cohort 1 optimization; cohort 2 validation) and wore 3 accelerometers and performed an exercise routine consisting of the following speeds: 1.5, 3, 4.5, 9 and 10.5 km/h (6 km/h for 2nd cohort included). Data from optimization cohort was used to optimize Sartorio step detection algorithm. Actual taken steps were recorded with a video camera and energy expenditure (EE) was measured. To observe the similarity between video and accelerometer step counts, paired samples t test and intraclass correlation were used separately for step counts in different speeds and for total counts as well as EE estimations. In speeds of 1.5, 3, 4.5, 6, 9 and 10.5 km/h mean absolute percentage error (MAPE) % were 8.1, 3.5, 4.3, 4.2, 3.1 and 7.8 for the Xelometer, respectively (after optimization). For ActiGraph GT3X+ the MAPE-% were 96.93 (87.4), 34.69 (23.1), 2.13 (2.3), 1.96 (2.6) and 2.99 (3.8), respectively and for activPAL 6.55 (5.6), 1.59 (0.6), 0.81 (1.1), 10.60 (10.3) and 15.76 (13.8), respectively. Significant intraclass correlations were observed with Xelometer estimates and actual steps in all speeds. Xelometer estimated the EE with a MAPE-% of 30.3, activPAL and ActiGraph GT3X+ with MAPE percentages of 20.5 and 24.3, respectively. The Xelometer is a valid device for assessing step counts at different gait speeds. MAPE is different at different speeds, which is of importance when assessing the PA in obese subjects and elderly. EE estimates of all three devices were found to be inaccurate when compared with indirect calorimetry.

Physical Activity and Its Association with Traditional Outcome Measures in Pulmonary Arterial Hypertension

Rationale Limitation of physical activity is a common presenting complaint for patients with pulmonary arterial hypertension (PAH). Physical activity is thought to be determined by cardiopulmonary function, yet there are limited data that investigate this relationship. Objective We aimed to study the relationship between right ventricular function and daily activity and its impact on health-related quality of life (HRQoL) in PAH. Methods Baseline data for 55 patients enrolled in PHANTOM, an ongoing multicenter randomized controlled trial of anastrozole in PAH were used. Post-menopausal women and men were eligible and underwent six-minute walk testing, echocardiography and completed HRQoL questionnaires. Each patient wore an accelerometer for 7-days. Multivariable linear regression models were used to study the association between tricuspid annular plane systolic excursion (TAPSE) and vector magnitude counts, and between daily activity and HRQoL. Principal component analysis and K-means clustering were used to identify activity-based phenotypes. K-nearest neighbors' classification was applied to an independent cross-sectional cohort from the University of Pennsylvania. Results The mean age of patients in PHANTOM was 61 years. 67% were women with idiopathic PAH as the most common etiology. A 0.4 cm increase in TAPSE was associated with an increase in daily vector magnitude counts (ß:34000, 95%CI:900-67000, p=0.004) after adjustment for age, sex, body mass index, etiology of PAH and wear time. A 1-standard deviation increase in vector magnitude counts was associated with higher six-minute walk distance (ß: 56.1 meters, 95%CI:28.6-83.7, p<0.001) and lower emPHasis-10 scores (ß:-3.3, 95%CI:0.3-6.4, p=0.03). Three activity phenotypes, low, medium, and high, were identified. The most active phenotype had greater six-minute walk distances (p=0.001) and lower emPHasis-10 scores (p=0.009) after adjustment for age, sex, body mass index, WHO functional class and parenteral prostacyclin use. Phenotypes of physical activity were reproduced in the second cohort and were independently associated with six-minute walk distance. Conclusion Better right ventricular systolic function was associated with increased levels of activity in PAH. Increased daily activity was associated with greater six-minute walk distance and better HRQoL. Distinct activity-based phenotypes may be helpful in risk stratification of PAH patients or provide novel endpoints for clinical trials.

Agreement Between StepWatch3 and ActiGraph wGT3X+ for Measuring Step-Based Metrics in People With Peripheral Artery Disease

The authors investigated the agreement between StepWatch3™ (SW3) and ActiGraph™ wGT3X+ monitors for measuring step-based metrics in patients with peripheral artery disease and older adults. In 23 patients with peripheral artery disease and 38 older participants, the authors compared the metrics obtained during an outdoor (400-m track) walking session (step count) and a 7-day free-living period (step count and 60/30/5/1-min maximal or peak step accumulation) using the SW3 (ankle) and the wGT3X+ (hip) with the low-frequency extension filter enabled (wGT3X+/LFE) or not (wGT3X+/N). During outdoor walking session, agreement was high, particularly for wGT3X+/LFE: correlations ≥.98, median absolute percentage errors <1%, and significant equivalence using a ± 15% equivalence zone or narrower. In free living, no wGT3X+ method was equivalent to SW3 for step count. The wGT3X+/LFE was equivalent to SW3 regarding all step accumulation metrics using a ± 20% equivalence zone or narrower, with median absolute percentage errors <11%. The wGT3X+/LFE method is the best option for comparisons with SW3 in peripheral artery disease and older adults.

Tracking and Changes in Daily Step Counts among Finnish Adults

PURPOSE

This study aimed to investigate the tracking and changes of steps per day in adults and their determinants over 13 yr.

METHODS

A total of 2195 subjects (1236 women) 30-45 yr of age were randomly recruited from the ongoing Cardiovascular Risk in Young Finns Study in 2007 and were followed up in 2020. Steps per day, including both total and aerobic steps per day, were monitored for seven consecutive days with a pedometer in 2007-2008 and 2011-2012 and with an accelerometer in 2018-2020. Tracking was analyzed using Spearman's correlation. Stability and changes of steps per day over time in both low-active and high-active groups (based on median values) were described by percentage agreements, kappa statistics, and logistic regression. Associations of sex, age, and body mass index with the initial number and changes in steps per day were analyzed using linear growth curve modeling.

RESULTS

Tracking correlations of total steps per day at 4-, 9-, and 13-yr intervals were 0.45-0.66, 0.33-0.70, and 0.29-0.60, while corresponding correlations for aerobic steps per day were 0.28-0.55, 0.23-0.52, and 0.08-0.55, respectively. Percentage agreements were higher than 54%, and kappa statistics ranged from slight to fair over time. Compared with the low-active group, the high-active group at baseline had a higher probability of being active later in adulthood. Female sex and higher age were associated directly with the initial number of steps per day and inversely with changes in the number of steps per day. Body mass index was inversely associated with the initial number of steps per day and changes in the number of total steps per day.

CONCLUSION

The 13-yr tracking of steps per day in adulthood was found to be low to moderately high. Daily ambulatory activity is essential to maintaining an active lifestyle throughout adulthood. Changes in the amount of adult steps per day vary by sex, age, and BMI.

Criterion Validity of iOS and Android Applications to Measure Steps and Distance in Adults

The growing popularity of physical activity (PA) applications (apps) in recent years and the vast amounts of data that they generate present attractive possibilities for surveillance. However, measurement accuracy is indispensable when tracking PA variables to provide meaningful measures of PA. The purpose of this study was to examine the steps and distance criterion validity of freeware accelerometer-based PA smartphone apps, during incremental-intensity treadmill walking and jogging. Thirty healthy adults (25.9 ± 5.7 years) participated in this cross-sectional study. They were fitted with two smartphones (one with Android and one with iOS operating systems), each one simultaneously running four different apps (i.e., Runtastic Pedometer, Accupedo, Pacer, and Argus). They walked and jogged for 5 min at each of the predefined speeds of 4.8, 6.0, and 8.4 km/h on a treadmill, and two researchers counted every step taken during trials with a digital tally counter. Validity was evaluated by comparing each app with the criterion measure using repeated-measures analysis of variance (ANOVA), mean absolute percentage errors (MAPEs), and Bland–Altman plots. For step count, Android apps performed slightly more accurately that iOS apps; nevertheless, MAPEs were generally low for all apps (<5%) and accuracy increased at higher speeds. On the other hand, errors were significantly higher for distance estimation (>10%). The findings suggest that accelerometer-based apps are accurate tools for counting steps during treadmill walking and jogging and could be considered suitable for use as an outcome measure within a clinical trial. However, none of the examined apps was suitable for measuring distance.

Combining Accelerometer and GPS Features to Evaluate Community Mobility in Knee Ankle Foot Orthoses (KAFO) Users

Orthotic and assistive devices such as knee ankle foot orthoses (KAFO), come in a variety of forms and fits, with several levels of available features that could help users perform daily activities more naturally. However, objective data on the actual use of these devices outside of the research lab is usually not obtained. Such data could enhance traditional lab-based outcome measures and inform clinical decision-making when prescribing new orthotic and assistive technology. Here, we link data from a GPS unit and an accelerometer mounted on the orthotic device to quantify its usage in the community and examine the correlations with clinical metrics. We collected data from 14 individuals over a period of 2 months as they used their personal KAFO first, and then a novel research KAFO; for each device we quantified number of steps, cadence, time spent at community locations and time wearing the KAFO at those locations. Sensor-derived metrics showed that mobility patterns differed widely between participants (mean steps: 591.3, SD =704.2). The novel KAFO generally enabled participants to walk faster during clinical tests ( ∆6 Minute-Walk-Test=71.5m, p=0.006). However, some participants wore the novel device less often despite improved performance on these clinical measures, leading to poor correlation between changes in clinical outcome measures and changes in community mobility ( ∆6 Minute-Walk-Test - ∆ Community Steps: r=0.09, p=0.76). Our results suggest that some traditional clinical outcome measures may not be associated with the actual wear time of an assistive device in the community, and obtaining personalized data from real-world use through wearable technology is valuable.

Assessment of Physical Activity in Adults using Wrist Accelerometers

The health benefits of physical activity have been widely recognized, yet traditional measures of physical activity including questionnaires and category-based assessments of volume and intensity provide only broad estimates of daily activities. Accelerometers have advanced epidemiologic research on physical activity by providing objective and continuous measurement of physical activity in free-living conditions. Wrist-worn accelerometers have become especially popular due to low participant burden. However, the validity and reliability of wrist-worn devices for adults have yet to be summarized. Moreover, accelerometer data provide rich information on how physical activity is accumulated throughout the day, but only a small portion of these rich data have been utilized by researchers. Lastly, new methodological developments that aim to overcome some of the limitations of accelerometers are emerging. The purpose of this review is to provide an overview of accelerometry research, with a special focus on wrist-worn accelerometers. We describe briefly how accelerometers work, summarize the validity and reliability of wrist-worn accelerometers, discuss the benefits of accelerometers including measuring light-intensity physical activity, and discuss pattern metrics of daily physical activity recently introduced in the literature. A summary of large-scale cohort studies and randomized trials that implemented wrist-worn accelerometry is provided. We conclude the review by discussing new developments and future directions of research using accelerometers, with a focus on wrist-worn accelerometers.

Accuracy and precision of wrist-worn actigraphy for measuring steps taken during over-ground and treadmill walking in adults with Parkinson's disease

INTRODUCTION

Step counts represent a straight-forward method of measuring physical activity in adults with Parkinson's disease (PD). The present study examined the absolute and relative accuracy and precision of a wrist-worn research-grade accelerometer (i.e., ActiGraph GT3X+) for measuring step counts during over-ground and treadmill walking in adults with PD and controls without PD.

METHODS

Participants (PD: n = 29; controls: n = 31) wore two ActiGraph GT3X + accelerometers, one on each wrist, and completed an over-ground walking bout followed by a treadmill walking bout at the same speed. Step counts were measured manually using a hand-held tally counter. Accuracy and precision were based on absolute and relative metrics.

RESULTS

The ActiGraph GT3X + underestimated step counts in both participants with PD (4.7-11% error) and controls without PD (8.8-17% error), with a greater discrepancy in controls. The ActiGraph GT3X + provided more accurate and precise estimates of step counts when placed on the more affected wrist and non-dominant wrist for participants with PD and controls, respectively, and was more accurate and precise during over-ground walking compared with treadmill walking for both groups.

CONCLUSIONS

Our results suggest that placement of the device (i.e., dominant vs. non-dominant), type of activity (i.e., over-ground vs. treadmill walking), and presence of clinical conditions may impact the accuracy and precision of data when using the research-grade ActiGraph GT3X + accelerometer for measuring step counts.

Influence of Self-managed Rehabilitation on Work Efficiency in Active Duty Military With a Knee Injury

INTRODUCTION

Knee injuries associated with intense physical training are one of the most frequent injuries associated with medical encounters for military members. The purpose of this study was to evaluate four approaches to physiotherapy rehabilitation and their effects on work efficiency in active duty military with a knee injury. The four groups included neuromuscular electrical stimulation (NMES), walking with a weighted vest (WALK), combined NMES/Walk, and standard physiotherapy rehabilitation. All groups received standard physiotherapy rehabilitation.We have previously reported that quadriceps muscle strength improved over 18 weeks in the study for the three interventions relative to standard rehabilitation alone. This report presents results from an examination of work efficiency as evaluated during a step test while measuring oxygen utilization.

METHODS

A randomized controlled trial was conducted, with repeated outcome measures of work efficiency assessed at baseline, 3, 6, 12, and 18 weeks. The sample consisted of 67 active duty service members between the ages of 18 and 50 years with a knee injury. Participants were randomized to one of the four approaches to physiotherapy rehabilitation: (1) NMES was applied to the quadriceps muscle four times per week, for 30 minutes (15 minutes to each leg), consisting of 15 quadriceps muscle contractions per leg; (2) graduated strength walking using a weighted vest (WALK) was for 30 minutes, 3 to 4 days a week; (3) combined NMES with strength walking received both the NMES therapy and the weighted vest walking; and (4) standard physiotherapy consisted of progressive exercise with the number and type of sessions not controlled by the study. All four groups received the standard physiotherapy for a knee injury. The primary outcome was work efficiency, as measured by oxygen utilization during a 2-minute self-paced step test over 18 weeks. The primary analysis used repeated measures, linear mixed-effects models with a random effect for subject.

RESULTS

Both the number of steps performed and gross work efficiency improved during the study for all three intervention groups. For gross work efficiency, standard rehabilitation improved 12%, WALK showed a 19% improvement, NMES increased by 24%, and the NMES/Walk group improved by 40%.

CONCLUSIONS

All groups showed improved submaximal exercise efficiency based on oxygen utilization, with the intervention groups showing a greater improvement in work efficiency as compared to standard rehabilitation. Knee injuries can be problematic for active duty members because of reduced mobility leading to deconditioning and associated declines in work efficiency. Rehabilitative programs, including those described in this study, may minimize loss of work efficiency and fitness and promote a quicker recovery.

Validity of Hip and Ankle Worn Actigraph Accelerometers for Measuring Steps as a Function of Gait Speed during Steady State Walking and Continuous Turning

This study aimed to investigate the accuracy and reliability of hip and ankle worn Actigraph GT3X+ (AG) accelerometers to measure steps as a function of gait speed. Additionally, the effect of the low frequency extension filter (LFEF) on the step accuracy was determined. Thirty healthy individuals walked straight and walked with continuous turns in different gait speeds. Number of steps were recorded with a hip and ankle worn AG, and with a Stepwatch (SW) activity monitor positioned around the right ankle, which was used as a reference for step count. The percentage agreement, interclass correlation coefficients and Bland–Altmann plots were determined between the AG and the reference SW across gait speeds for the two walking conditions. The ankle worn AG with the default filter was the most sensitive for step detection at >0.6 m/s, whilst accurate step detection for gait speeds < 0.6 m/s were only observed when applying the LFEF. The hip worn AG with the default filter showed poor accuracy (12–78%) at gait speeds < 1.0 m/s whereas the accuracy increased to >87% for gait speeds < 1.0 m/s when applying the LFEF. Ankle worn AG was the most sensitive to measure steps at a vast range of gait speeds. Our results suggest that sensor placement and filter settings need to be taken into account to provide accurate estimates of step counts.

Movement at work: A comparison of real time location system, accelerometer and observational data from an office work environment

Office workers can spend significant periods of time being stationary whilst at work, with potentially serious health consequences. The development of effective health interventions could be aided by a greater understanding of the location and environmental context in which this stationary behaviour occurs. Real time location systems (RTLS) potentially offer the opportunity to gather this much needed information, but they have not been extensively trialled in office workplaces, nor rigorously compared against more familiar devices such as accelerometers. The aim of this paper was to determine whether an RTLS can measure and spatially locate the non-stationary and stationary behaviours of adults working in an office work environment. Data collected from a series of comparison studies undertaken in a commercial office building suggests that RTLS can measure the velocity at which people are moving and locate them, when stationary, with an accuracy of 0.668 m (SD 0.389). This opens up significant opportunities to further understand how people move within buildings, the indoor physical environmental influences on that movement, and the development of effective interventions to help people to move more whilst at work.

Reduction in ambulatory distance from childhood through adolescence: The impact of the number and length of steps

Background

The aim of this study was to explore the relationship between ambulatory distance with steps/day and increased step length as children age.

Methods

This is a prospective cohort study. Forty-five children from the QUALITY cohort were assessed at childhood (baseline) and seven years later during adolescence (follow-up). Daily step count was evaluated by accelerometry, step length by a standardized test, and daily ambulatory distance was calculated based on step count and length.

Results

Children grew by an average of 0.33 m from childhood to adolescence (p < 0.001). The daily ambulatory distance decreased by an average 3008 m from childhood to adolescence (p < 0.001). Step length increased an average of 0.10 m (p < 0.001) from childhood to adolescence, while the number of steps taken decreased by an average of 5549 steps (childhood to adolescence) (p < 0.001). The change in the number of steps between childhood and adolescence represents 84.6% of the change in the ambulatory distance while the change in step length explained an additional 13.0%

Conclusions

The decrease in the ambulatory distance from childhood to adolescence was strongly explained by the decrease in step count; however the increase in step length should not to be neglected.

Does Multiple Sclerosis Differently Impact Physical Activity in Women and Man? A Quantitative Study Based on Wearable Accelerometers

In people with multiple sclerosis (pwMS), fatigue, weakness and spasticity may reduce mobility and promote sedentary behavior. However, little is known about the existence of possible differences in the way MS modifies the propensity to perform physical activity (PA) in men and women. The present study aimed to partly close this gap by means of quantitative analysis carried out using wearable sensors. Forty-five pwMS (23 F, 22 M, mean age 50.3) and 41 unaffected age- and sex-matched individuals wore a tri-axial accelerometer 24 h/day for 7 consecutive days. Raw data were processed to calculate average number of daily steps, vector magnitude (VM) counts, and percentage of time spent in sedentary behavior and in PA of different intensities (i.e., light and moderate-to-vigorous, MVPA). Women with MS spent more time in sedentary behavior and exhibited a reduced amount of light intensity activity with respect to men, while MVPA was similar across sexes. However, in comparison with unaffected individuals, the overall PA patterns appear significantly modified mostly in women who, in presence of the disease, present increased sedentary behavior, reduced MVPA, number of daily steps and VM counts. The findings of the present study highlight the urgency of including sex as variable in all studies on PA in pwMS.

Conduct of Clinical Trials in the Era of COVID-19: JACC Scientific Expert Panel

The coronavirus disease-2019 (COVID-19) pandemic has profoundly changed clinical care and research, including the conduct of clinical trials, and the clinical research ecosystem will need to adapt to this transformed environment. The Heart Failure Academic Research Consortium is a partnership between the Heart Failure Collaboratory and the Academic Research Consortium, composed of academic investigators from the United States and Europe, patients, the U.S. Food and Drug Administration, the National Institutes of Health, and industry members. A series of meetings were convened to address the challenges caused by the COVID-19 pandemic, review options for maintaining or altering best practices, and establish key recommendations for the conduct and analysis of clinical trials for cardiovascular disease and heart failure. This paper summarizes the discussions and expert consensus recommendations.

Temporal association between objectively measured smartphone usage, sleep quality and physical activity among Chinese adolescents and young adults

We studied the association between objectively measured smartphone usage and objectively measured sleep quality and physical activity for seven consecutive days among Hong Kong adolescents and young adults aged 11-25 years (n = 357, 67% female). We installed an app that tracked the subjects' smartphone usage and had them wear an ActiGraph GT3X accelerometer on their wrist to measure their sleep quality and physical activity level. Smartphone usage data were successfully obtained from 187 participants (52.4%). The participants on average spent 2 h 46 min per day on their smartphone. Multilevel regression showed that 1 min of daytime smartphone usage was associated with 0.07 min decrease in total sleeping time that night (p = .043, 95% confidence interval [CI]: -0.14, -0.003). Broken down for different usage purposes, 1 min of daytime social network usage and games and comics was associated with a 0.28 (p = .02, 95% CI: -0.52, -0.04) min and 0.18 min (p = .01, 95% CI: -0.32, -0.04) decrease in total sleeping time that night, respectively. One minute of daytime smartphone usage was associated with an increase of 4.55 steps in the number of steps (p = .001, 95% CI: 1.77, 7.34) on the next day. To conclude, time spent on a smartphone in the daytime was associated with total sleeping time that night and number of steps the next day, but was not associated with sleep efficiency, wake after sleep onset and moderate-to-vigorous-intensity activity (MVPA) among Hong Kong adolescents and young adults.

Development and Evaluation of an Accelerometer-Based Protocol for Measuring Physical Activity Levels in Cancer Survivors: Development and Usability Study

Background

The collection of self-reported physical activity using validated questionnaires has known bias and measurement error.

Objective

Accelerometry, an objective measure of daily activity, increases the rigor and accuracy of physical activity measurements. Here, we describe the methodology and related protocols for accelerometry data collection and quality assurance using the Actigraph GT9X accelerometer data collection in a convenience sample of ovarian cancer survivors enrolled in GOG/NRG 0225, a 24-month randomized controlled trial of diet and physical activity intervention versus attention control.

Methods

From July 2015 to December 2019, accelerometers were mailed on 1337 separate occasions to 580 study participants to wear at 4 time points (baseline, 6, 12, and 24 months) for 7 consecutive days. Study staff contacted participants via telephone to confirm their availability to wear the accelerometers and reviewed instructions and procedures regarding the return of the accelerometers and assisted with any technology concerns.

Results

We evaluated factors associated with wear compliance, including activity tracking, use of a mobile app, and demographic characteristics with chi-square tests and logistic regression. Compliant data, defined as ≥4 consecutive days with ≥10 hours daily wear time, exceeded 90% at all study time points. Activity tracking, but no other characteristics, was significantly associated with compliant data at all time points (P<.001). This implementation of data collection through accelerometry provided highly compliant and usable activity data in women who recently completed treatment for ovarian cancer.

Conclusions

The high compliance and data quality associated with this protocol suggest that it could be disseminated to support researchers who seek to collect robust objective activity data in cancer survivors residing in a wide geographic area.

Advances in accelerometry for cardiovascular patients: a systematic review with practical recommendations

Aims

Accelerometers are becoming increasingly commonplace for assessing physical activity; however, their use in patients with cardiovascular diseases is relatively substandard. We aimed to systematically review the methods used for collecting and processing accelerometer data in cardiology, using the example of heart failure, and to provide practical recommendations on how to improve objective physical activity assessment in patients with cardiovascular diseases by using accelerometers.

Methods and results

Four electronic databases were searched up to September 2019 for observational, interventional, and validation studies using accelerometers to assess physical activity in patients with heart failure. Study and population characteristics, details of accelerometry data collection and processing, and description of physical activity metrics were extracted from the eligible studies and synthesized. To assess the quality and completeness of accelerometer reporting, the studies were scored using 12 items on data collection and processing, such as the placement of accelerometer, days of data collected, and criteria for non‐wear of the accelerometer. In 60 eligible studies with 3500 patients (of those, 536 were heart failure with preserved ejection fraction patients), a wide variety of accelerometer brands (n = 27) and models (n = 46) were used, with Actigraph being the most frequent (n = 12), followed by Fitbit (n = 5). The accelerometer was usually worn on the hip (n = 32), and the most prevalent wear period was 7 days (n = 22). The median wear time required for a valid day was 600 min, and between two and five valid days was required for a patient to be included in the analysis. The most common measures of physical activity were steps (n = 20), activity counts (n = 15), and time spent in moderate‐to‐vigorous physical activity (n = 14). Only three studies validated accelerometers in a heart failure population, showing that their accuracy deteriorates at slower speeds. Studies failed to report between one and six (median 4) of the 12 scored items, with non‐wear time criteria and valid day definition being the most underreported items.

Conclusions

The use of accelerometers in cardiology lacks consistency and reporting on data collection, and processing methods need to be improved. Furthermore, calculating metrics based on raw acceleration and machine learning techniques is lacking, opening the opportunity for future exploration. Therefore, we encourage researchers and clinicians to improve the quality and transparency of data collection and processing by following our proposed practical recommendations for using accelerometers in patients with cardiovascular diseases, which are outlined in the article.

Step by step: Association of device-measured daily steps with all-cause mortality-A prospective cohort Study

Introduction

Walking is free, does not require special training, and can be done almost everywhere. Therefore, walking is a feasible behavior on which to tailor public health messages. This study assesses the prospective association and dose‐response relationship between daily steps and all‐cause mortality.

Materials and Methods

Daily steps were measured by waist‐mounted accelerometers in 2183 individuals (53% women) for seven consecutive days at baseline (2008‐09). Participants were followed for a median period of 9.1 years and associations between steps and all‐cause mortality determined by registry linkage were assessed using Cox proportional hazard regression with adjustment for relevant covariates.

Results

Mean age was 57.0 (SD 10.9) years at baseline. Median (IQR) daily steps across ascending quartiles were 4651 (3495‐5325), 6862 (6388‐7350), 8670 (8215‐9186), and 11 467 (10 556‐13 110), respectively. During follow‐up, 119 individuals died (68% men). Higher number of daily steps was associated with a lower risk of all‐cause mortality with hazard ratios of 1.00 (referent), 0.52 (0.29‐0.93), 0.50 (0.27‐0.94), and 0.43 (0.21‐0.88) across ascending quartiles of daily steps in the multivariable‐adjusted model with follow‐up commencing 2 years after baseline. Risk differences per 1000 individuals for ascending quartiles were 6.8 (2.9‐9.3), 7.1 (0.8‐11.1), and 8.0 (1.7‐12.1), respectively.

Conclusions

Daily steps were associated with lower mortality risk in a non‐linear dose‐response pattern. The risk is almost halved when comparing the least active referent against the second quartile equivalent to a difference of about 2200 daily steps. Encouraging those least active to increase their daily steps may have substantial public health implications.

Concurrent validity of Nokia Go activity tracker in walking and free-living conditions

RATIONALE, AIMS, AND OBJECTIVES

Consumer-based activity trackers aim at quantifying physical activity in a wide range of contexts. Nevertheless, they need to be validated before they are confidently used. This study assessed the concurrent validity of the Nokia Go against reference devices, according to different sensor locations, in two measurement conditions: during a walking task and during a 24-hour free-living condition.

METHODS

We examined the agreement between devices and between locations in the number of steps and total sleep time by using intraclass correlation coefficient and Bland-Altman method.

RESULTS

In the walking task, the agreement is good to excellent for steps between the Nokia Go and the reference device. In the free-living condition, there is a systematic underestimation of steps in comparison with the ActiGraph. Excellent agreement was found between locations. The device worn at the hip indicated the lowest number of steps, and the device located at the dominant wrist indicated the greatest number of steps.

CONCLUSIONS

There are high discrepancies in step count between devices because of the different types of activities in daily life. The Nokia Go may be confidently used for step counting during pure walking tasks, at different locations. However, the lack of concurrent validity with ActiGraph call for caution regarding their use in daily living conditions.

An Open-Source Monitor-Independent Movement Summary for Accelerometer Data Processing

Background

Physical behavior researchers using motion sensors often use acceleration summaries to visualize, clean, and interpret data. Such output is dependent on device specifications (e.g., dynamic range, sampling rate) and/or are proprietary, which invalidate cross-study comparison of findings when using different devices. This limits flexibility in selecting devices to measure physical activity, sedentary behavior, and sleep.

Purpose

Develop an open-source, universal acceleration summary metric that accounts for discrepancies in raw data among research and consumer devices.

Methods

We used signal processing techniques to generate a Monitor-Independent Movement Summary unit (MIMS-unit) optimized to capture normal human motion. Methodological steps included raw signal harmonization to eliminate inter-device variability (e.g., dynamic g-range, sampling rate), bandpass filtering (0.2-5.0 Hz) to eliminate non-human movement, and signal aggregation to reduce data to simplify visualization and summarization. We examined the consistency of MIMS-units using orbital shaker testing on eight accelerometers with varying dynamic range (±2 to ±8 g) and sampling rates (20-100 Hz), and human data (N = 60) from an ActiGraph GT9X.

Results

During shaker testing, MIMS-units yielded lower between-device coefficient of variations than proprietary ActiGraph and ENMO acceleration summaries. Unlike the widely used ActiGraph activity counts, MIMS-units were sensitive in detecting subtle wrist movements during sedentary behaviors.

Conclusions

Open-source MIMS-units may provide a means to summarize high-resolution raw data in a device-independent manner, thereby increasing standardization of data cleaning and analytical procedures to estimate selected attributes of physical behavior across studies.

Validity of six consumer-level activity monitors for measuring steps in patients with chronic heart failure

INTRODUCTION

Although numerous activity trackers have been validated in healthy populations, validation is lacking in chronic heart failure patients who normally walk at a slower pace, making it difficult for researchers and clinicians to implement activity monitors during physical activity interventions.

METHODS

Six consumer-level activity monitors were validated in a 3-day field study in patients with chronic heart failure and healthy individuals under free living conditions. Furthermore, the same devices were evaluated in a lab-based study during treadmill walking at speeds of 2.4, 3.0, 3.6, and 4.2 km·h-1. Concordance correlation coefficients (CCC) were used to evaluate the agreement between the activity monitors and the criterion, and mean absolute percentage errors (MAPE) were calculated to assess differences between each device and the criterion (MAPE <10% was considered as a threshold for validity).

RESULTS

In the field study of healthy individuals, all but one of the activity monitors showed a substantial correlation (CCC ≥0.95) with the criterion device and MAPE <10%. In patients with heart failure, the correlation of only two activity monitors (Garmin vívofit 3 and Withings Go) was classified as at least moderate (CCC ≥0.90) and none of the devices had MAPE <10%. In the lab-based study at speeds 4.2 and 3.6 km·h-1, all activity monitors showed substantial to almost perfect correlations (CCC ≥0.95) with the criterion and MAPE in the range 1%-3%. However, at slower speeds of 3.0 and 2.4 km·h-1, the accuracy of all devices substantially deteriorated: their correlation with the criterion decreased below 90% and their MAPE increased to 4-8% and 10-45%, respectively.

CONCLUSIONS

Even though none of the tested activity monitors fall within arbitrary thresholds for validity, most of them perform reasonably well enough to be useful tools that clinicians can use to simply motivate chronic heart failure patients to walk more.

Self-Managed Strength Training for Active Duty Military With a Knee Injury: A Randomized Controlled Pilot Trial

INTRODUCTION

Knee injuries among active duty military are one of the most frequent musculoskeletal injuries and are often caused by exercise or intense physical activity or combat training. These injuries pose a threat to force readiness. Our objective was to assess feasibility (including recruitment and retention rates) of three self-managed strengthening strategies for knee injuries and determine if they resulted in improvements in lower extremity strength, function, pain, and activity compared to usual physical therapy (PT) in military members.

METHODS

A pilot study using a randomized controlled trial was conducted at three outpatient military medical treatment facilities. After baseline testing, 78 active duty military members with a knee injury were randomized to 1-4 trial arms: (1) neuromuscular electrical stimulation (NMES) applied to the quadriceps muscle; (2) graduated strength walking using a weighted vest (WALK); (3) combined NMES with strength walking (COMBO); (4) usual PT alone. All groups received usual PT. The primary outcome was the rates of change in knee extensor and flexor strength over 18 weeks. Secondary outcomes explored the rates of change in functional performance, pain, and activities of daily living scale (ADLS). The primary analysis for the endpoints used repeated measures, linear mixed-effects models. This study was approved by Institutional Review Boards at all facilities.

RESULTS

The randomized sample (N = 78) included 19 participants in the PT-only, 20 in the WALK, 19 in the NMES and 20 in the COMBO groups. At baseline, there were no group differences. Fifty of the participants completed the 18-week study. The completers and non-completers differed at baseline on injury mechanism, with more completers injured during sports (45% vs 29%), and more non-completers during military training (36% vs 18%). Also, they differed in uninjured knee extension (completers 28% weaker), and uninjured knee flexion (completers 22% weaker). Adherence for self-reported daily step logs showed that the WALK group was 15% below goal and COMBO group 6% below goal. The 300 PV muscle stimulator showed the NMES group completed 34% of recommended stimulation sessions and the COMBO group 30%.Knee extension strength in the injured knee found only the COMBO group having a statistically higher improvement compared to PT-only (Change over 18 weeks: 10.6 kg in COMBO; 2.1 kg in PT-only). For the injured knee flexion changes, only the COMBO showed significant difference from PT-only (Change over 18 weeks: 7.5 kg in COMBO; -0.2 kg in PT-only). Similarly, for the uninjured knee, only the COMBO showed significant difference from PT-only in knee extension (Change over 18 weeks: 14.7 Kg in COMBO; 2.7 kg in PT-only) and knee flexion (Change over 18 weeks: 6.5 kg in COMBO; -0.2 kg in PT-only). Overall pain improved during the study for all groups with no significant group differences. Similarly, function and ADLS significantly improved over 18 weeks, with no significant group differences.

CONCLUSIONS

Knee extensor strength improvements in the COMBO group were significantly higher compared to usual PT. Pain, functional measures, and ADLS all improved during the study with no group differences. Further research is required to confirm these findings.

Application and Validation of Activity Monitors' Epoch Lengths and Placement Sites for Physical Activity Assessment in Exergaming

We assessed the agreement of two ActiGraph activity monitors (wGT3X vs. GT9X) placed at the hip and the wrist and determined an appropriate epoch length for physical activity levels in an exergaming setting. Forty-seven young adults played a 30-min exergame while wearing wGT3X and GT9X on both hip and wrist placement sites and a heart rate sensor below the chest. Intraclass correlation coefficient indicated that intermonitor agreement in steps and activity counts was excellent on the hip and good on the wrist. Bland-Altman plots indicated good intermonitor agreement in the steps and activity counts on both placement sites but a significant intermonitor difference was detected in steps on the wrist. Time spent in sedentary and physical activity intensity levels varied across six epoch lengths and depended on the placement sites, whereas time spent from a 1-s epoch of the hip-worn monitors most accurately matched the relative exercise intensity by heart rate. Hip placement site was associated with better step-counting accuracy for both activity monitors and more valid estimation of physical activity levels. A 1-s epoch was the most appropriate epoch length to detect short bursts of intense physical activity and may be the best choice for data processing and analysis in exergaming studies examining intermittent physical activities.