Validation of automatic wear-time detection algorithms in a free-living setting of wrist-worn and hip-worn ActiGraph GT3X

A review of the evidence for the utility of physical activity monitor use in patients with idiopathic inflammatory myopathies

Few proven therapies exist for patients with idiopathic inflammatory myopathies (IIMs), partly due to the lack of reliable and valid outcome measures for assessing treatment responses. The current core set measures developed by the International Myositis Assessment and Clinical Studies group were developed to standardize assessments of disease activity and treatment effect. None of the current measures address functional improvement in muscle weakness. Therefore, supplemental measures to more objectively assess physical activity levels and fatiguability in free-living settings are needed to assess disease activity more comprehensively. Validated physical activity monitors (PAMs) have the potential to serve as an objective functional outcome measure in clinical trials and observational studies. This review examines the current evidence for the use of body-worn PAMs in clinical settings with IIM patients. A practical overview of methods for PAM use in clinical patient populations (including measurement details and data processing) that focuses on IIM patients is also presented.

Objectively measured physical activity among people with and without HIV in Uganda: associations with cardiovascular risk and coronary artery disease

Background

Africa has a disproportionate burden of HIV-related cardiovascular disease. We aimed to describe physical activity in people living with HIV (PLHIV) and people without HIV (PWOH) in Uganda and characterize its relationship with the presence of computed tomography angiography-detected (CCTA) coronary artery disease (CAD).

Methods

We performed a cross-sectional analysis of the Ugandan Study of HIV Effects on the Myocardium and Atherosclerosis using Computed Tomography (mUTIMA-CT) cohort. From 2017-2019, physical activity in PLHIV and PWOH was assessed by accelerometry over seven days. Participants additionally underwent CCTA. Univariable and multivariable modified Poisson regression was used to analyze the relationship between physical activity and CAD presence.

Results

168 participants were analyzed. The median (IQR) age was 57 (53-58) years old and 64% were female. Males had more moderate-to-vigorous physical activity per week [68 minutes (12-144) vs 15 minutes (0-50), P<0.001] and less light physical activity [788 minutes (497-1,202) vs [1,059 (730-1490), P=0.001] compared to females, but there was no difference by HIV status. After adjusting for age, which accounted for 10% of the variation in steps taken, and sex, no significant associations were found between physical activity and coronary plaque.

Conclusion

Objectively measured physical activity was low compared to guideline recommendations, with males being somewhat more active than females and without significant differences by HIV status. Physical activity was not associated with the presence of CAD independently of age and sex.

Head Injury Treatment With Healthy and Advanced Dietary Supplements: A Pilot Randomized Controlled Trial of the Tolerability, Safety, and Efficacy of Branched Chain Amino Acids in the Treatment of Concussion in Adolescents and Young Adults

Concussion is a common injury in the adolescent and young adult populations. Although branched chain amino acid (BCAA) supplementation has shown improvements in neurocognitive and sleep function in pre-clinical animal models of mild-to-moderate traumatic brain injury (TBI), to date, no studies have been performed evaluating the efficacy of BCAAs in concussed adolescents and young adults. The goal of this pilot trial was to determine the efficacy, tolerability, and safety of varied doses of oral BCAA supplementation in a group of concussed adolescents and young adults. The study was conducted as a pilot, double-blind, randomized controlled trial of participants ages 11-34 presenting with concussion to outpatient clinics (sports medicine and primary care), urgent care, and emergency departments of a tertiary care pediatric children's hospital and an urban tertiary care adult hospital, between June 24, 2014 and December 5, 2020. Participants were randomized to one of five study arms (placebo and 15 g, 30 g, 45 g, and 54 g BCAA treatment daily) and followed for 21 days after enrollment. Outcome measures included daily computerized neurocognitive tests (processing speed, the a priori primary outcome; and attention, visual learning, and working memory), symptom score, physical and cognitive activity, sleep/wake alterations, treatment compliance, and adverse events. In total, 42 participants were randomized, 38 of whom provided analyzable data. We found no difference in our primary outcome of processing speed between the arms; however, there was a significant reduction in total symptom score (decrease of 4.4 points on a 0-54 scale for every 500 g of study drug consumed, p value for trend = 0.0036, [uncorrected]) and return to physical activity (increase of 0.503 points on a 0-5 scale for every 500 g of study drug consumed, p value for trend = 0.005 [uncorrected]). There were no serious adverse events. Eight of 38 participants reported a mild (not interfering with daily activity) or moderate (limitation of daily activity) adverse event; there were no differences in adverse events by arm, with only two reported mild adverse events (both gastrointestinal) in the highest (45 g and 54 g) BCAA arms. Although limited by slow enrollment, small sample size, and missing data, this study provides the first demonstration of efficacy, as well as safety and tolerability, of BCAAs in concussed adolescents and young adults; specifically, a dose-response effect in reducing concussion symptoms and a return to baseline physical activity in those treated with higher total doses of BCAAs. These findings provide important preliminary data to inform a larger trial of BCAA therapy to expedite concussion recovery.

Beneficial and harmful effects of physical activity on care-seeking for low back pain: the AUTBACK study

PURPOSE

People who seek more care for low back pain (LBP) tend to experience poorer recovery (e.g. higher pain and disability levels). Understanding the factors associated with care-seeking for LBP might improve patient outcomes and potentially alleviate the burden of LBP on global health systems. This study aimed to investigate the relationship between different intensities, volumes, and domains of physical activity and care-seeking behaviours, in people with a history of LBP.

METHODS

Longitudinal data from adult twins were drawn from the AUstralian Twin BACK study. The primary outcome was the total self-reported frequency (counts) of overall utilisation of care for LBP, over 1 year. Secondary outcomes were the utilisation of health services, and the utilisation of self-management strategies, for LBP (assessed as total frequency over 1 year). Explanatory variables were device-based measures of sedentary behaviour and moderate-to-vigorous intensity physical activity, and self-reported physical workload, and work, transport, household, and leisure domain physical activity, at baseline.

RESULTS

Data from 340 individuals were included. Median age was 56.4 years (IQR 44.9-62.3 years) and 73% of participants were female. Medium-to-high baseline volumes of sedentary behaviour were significantly associated with greater counts of overall care utilisation (IRR 1.60, 95%CI 1.04-2.44) and utilisation of self-management strategies (IRR 1.60, 95%CI 1.02-2.50) for LBP, over 1 year. Medium-to-high baseline volumes of household domain physical activity were significantly associated with greater counts of utilising self-management strategies for LBP over 1 year (IRR 1.62, 95%CI 1.04-2.53). No explanatory variables were associated with the utilisation of health services for LBP.

CONCLUSION

People who engage in higher baseline volumes of sedentary behaviour or physical activity in the household setting (e.g. housework, gardening, yard work, general household maintenance) utilise 1.6 times more care for LBP over 1 year. Findings suggest that higher volumes of these behaviours may be harmful for LBP. No intensities, volumes, or domains of physical activity demonstrated clear benefits for LBP. Where feasible, patients and clinicians should collaborate to screen and develop strategies to reduce engagement in sedentary behaviour or physical activity in the household setting. Contextual factors (e.g. patient symptom severity, sociocultural roles, occupational demands) should be considered when devising appropriate behaviour change strategies.

Effects of physical activity levels on characteristic pain in temporomandibular dysfunctions: a cross-sectional study

BACKGROUND

Physical activity is known to influence the symptoms of a variety of pain disorders including fibromyalgia and osteoarthritis although the underlying mechanism is not fully understood. In spite of the high prevalence of temporomandibular disorders (TMD), no previous study has objectively evaluated the relationship between TMD and general physical activity. This study aims to investigate the influence of physical activity on pain and disability from TMD, considering various confounders including sleep, systemic inflammation, psychosocial disturbances, and widespread pain.

METHODS

This observational cross-sectional study is based on consecutive samples of 100 TMD patients (22 with high pain disability and 78 with low pain disability level). Physical activity levels were assessed with actigraph. Level of pain and disability were evaluated using the Graded Chronic Pain Scale. Hematologic examinations including inflammatory biomarkers were assessed and comorbidities were investigated with validated questionnaires. Differences were analyzed according to disability level.

RESULTS

Patients with high disability level spent significantly more time doing both moderate (p = 0.033) and vigorous (p = 0.039) level physical activity. Light physical activity, on the other hand, was associated with low disability but the difference did not reach statistical significance. Time spent in light physical activity was significantly associated with high levels of pain and disability (p = 0.026, β = -0.001) and time spent in vigorous physical activity had significant predictive power (cutoff value 2.5 min per week, AUC 0.643, p = 0.041). Scores of the Jaw Function Limitation Score-20 (p = 0.001), present McGill Pain Score (p = 0.010), and number of people potentially diagnosed with fibromyalgia (p = 0.033) were significantly higher in the high disability group.

CONCLUSIONS

Moderate or vigorous physical activity is associated with worse TMD symptoms while light physical activity may be beneficial. Further research related to the amount and frequency of physical activity is necessary to establish clinical guidelines for TMD.

TRIAL REGISTRATION

clinical trial registration of the Clinical Research Information Service of Republic of Korea (number KCT0007107).

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.

The impact of aggregate positive lifestyle behaviors on low back pain resilience and care seeking

BACKGROUND CONTEXT

Low back pain (LBP) is a global issue, and the high associated costs are mainly attributed to a small proportion of people with LBP who seek care. Importantly, the impact of aggregate positive lifestyle behaviors on LBP resilience and care seeking is not known.

PURPOSE

This study aimed to evaluate the relationship between positive lifestyle behaviors and LBP resilience.

STUDY DESIGN

This study was a prospective longitudinal cohort study.

PATIENT SAMPLE

Data was collected as part of the AUstralian Twin BACK Study (AUTBACK). Participants who reported a lifetime previous history of LBP at baseline were included in this analysis (n = 340).

OUTCOME MEASURES

The outcomes of interest were the number of weeks without activity limiting LBP and total number of days of healthcare usage, health practitioner care, self-management care, and medication intake.

METHODS

A lifestyle behavior score was built using variables of body mass index (BMI), physical activity, smoking status, and sleep quality. Negative binomial regression analyses were used to assess the relationship between the positive lifestyle behavior score and the count outcomes of number of weeks without activity limiting LBP and number of days participants used care.

RESULTS

After adjusting for covariates, no association was found between participants' positive lifestyle behavior score and their number of weeks without activity limiting LBP (IRR: 1.02, 95% CI 1.00-1.05). There was a statistically significant relationship between higher positive lifestyle behavior scores and fewer number of days of participants' total healthcare usage (IRR:0.69, 95% CI 0.56-0.84), healthcare practitioner visits (IRR:0.62, 95% CI 0.45-0.84), use of self-management strategies (IRR:0.74, 95% CI 0.60-0.91), and use of pain medication (IRR:0.55, 95% CI 0.44-0.68).

CONCLUSION

People who adopt optimal lifestyle behaviors, such as engaging in adequate physical activity, achieving optimal quality sleep, maintaining an ideal BMI, and not smoking, may not experience less time suffering from activity limiting LBP, but are less likely to use healthcare and pain medication for their LBP.

Interplay of Race and Neighborhood Deprivation on Ambulatory Blood Pressure in Young Adults

Background

Ambulatory blood pressure (BP) monitoring measures nighttime BP and BP dipping, which are superior to in-clinic BP for predicting cardiovascular disease (CVD), the leading cause of death in America. Compared with other racial/ethnic groups, Black Americans exhibit elevated nighttime BP and attenuated BP dipping, including in young adulthood. Social determinants of health contribute to disparities in CVD risk, but the contribution of neighborhood deprivation on nighttime BP is unclear. Therefore, we examined associations between neighborhood deprivation with nighttime BP and BP dipping in young Black and White adults.

Methods

We recruited 21 Black and 26 White participants (20 M/27 F, mean age: 21 years, body mass index: 25±4 kg/m2) for 24-hour ambulatory BP monitoring. We assessed nighttime BP and BP dipping (nighttime:daytime BP ratio). The area deprivation index (ADI) was used to measure neighborhood deprivation. Associations between ADI and ambulatory BP were examined.

Results

Black participants exhibited higher nighttime diastolic BP compared with White participants (63±8 mmHg vs 58±7 mmHg, p=0.003), and attenuated BP dipping ratios for both systolic (0.92±0.06 vs 0.86±0.05, p=0.001) and diastolic BP (0.86±0.09 vs 0.78±0.08, p=0.007). Black participants experienced greater neighborhood deprivation compared with White participants (ADI scores: 110±8 vs 97±21, p<0.001), and ADI was associated with attenuated systolic BP dipping (ρ=0.342, p=0.019).

Conclusions

Our findings suggest neighborhood deprivation may contribute to higher nighttime BP and attenuated BP dipping, which are prognostic of CVD, and more prevalent in Black adults. Targeted interventions to mitigate the effects of neighborhood deprivation may help to improve nighttime BP.

Clinical Trial Registry

URL: https://www.clinicaltrials.gov; Unique identifier: NCT04576338.

Differences in the gut microbiome across typical ageing and in Parkinson's disease

The microbiota-gut-brain axis' role in Parkinson's disease (PD) pathophysiology, and how this differs from typical ageing, is poorly understood. Presently, gut-bacterial diversity, taxonomic abundance and metabolic bacterial pathways were compared across healthy young (n = 22, 18-35 years), healthy older (n = 33, 50-80 years), and PD groups (n = 18, 50-80 years) using shotgun sequencing and compositional data analysis. Associations between the gut-microbiome and PD symptoms, and between lifestyle factors (fibre intake, physical activity, and sleep) and the gut-microbiome were conducted. Alpha-diversity did not differ between PD participants and older adults, whilst beta-diversity differed between these groups. Lower abundance of Butyricimonas synergistica, a butyrate-producer, was associated with worse PD non-motor symptoms in the PD group. Regarding typical ageing, Bifidobacterium bifidum, was greater in the younger compared to older group, with no difference between the older and PD group. Abundance of metabolic pathways related to butyrate production did not differ among the groups, while 100 other metabolic pathways differed among the three groups. Sleep efficiency was positively associated with Roseburia inulinivorans in the older group. These results highlight the relevance of gut-microbiota to PD and that reduced butyrate-production may be involved with PD pathophysiology. Future studies should account for lifestyle factors when investigating gut-microbiomes across ageing and in PD.

An Algorithm to Classify Real-World Ambulatory Status From a Wearable Device Using Multimodal and Demographically Diverse Data: Validation Study

BACKGROUND

Measuring the amount of physical activity and its patterns using wearable sensor technology in real-world settings can provide critical insights into health status.

OBJECTIVE

This study's aim was to develop and evaluate the analytical validity and transdemographic generalizability of an algorithm that classifies binary ambulatory status (yes or no) on the accelerometer signal from wrist-worn biometric monitoring technology.

METHODS

Biometric monitoring technology algorithm validation traditionally relies on large numbers of self-reported labels or on periods of high-resolution monitoring with reference devices. We used both methods on data collected from 2 distinct studies for algorithm training and testing, one with precise ground-truth labels from a reference device (n=75) and the second with participant-reported ground-truth labels from a more diverse, larger sample (n=1691); in total, we collected data from 16.7 million 10-second epochs. We trained a neural network on a combined data set and measured performance in multiple held-out testing data sets, overall and in demographically stratified subgroups.

RESULTS

The algorithm was accurate at classifying ambulatory status in 10-second epochs (area under the curve 0.938; 95% CI 0.921-0.958) and on daily aggregate metrics (daily mean absolute percentage error 18%; 95% CI 15%-20%) without significant performance differences across subgroups.

CONCLUSIONS

Our algorithm can accurately classify ambulatory status with a wrist-worn device in real-world settings with generalizability across demographic subgroups. The validated algorithm can effectively quantify users' walking activity and help researchers gain insights on users' health status.

Generalizability and performance of methods to detect non-wear with free-living accelerometer recordings

Wearable physical activity sensors are widely used in research and practice as they provide objective measures of human behavior at a low cost. An important challenge for accurate assessment of physical activity behavior in free-living is the detection non-wear. Traditionally, heuristic algorithms that rely on specific interval lengths have been employed to detect non-wear time; however, machine learned models are emerging. We explore the potential of detecting non-wear using decision trees that combine raw acceleration and skin temperature, and we investigate the generalizability of our models, traditional heuristic algorithms, and recently developed machine learned models by external validation. The Decision tree models were trained using one week of data from thigh- and hip-worn accelerometers from 64 children. External validation was performed using data from wrist-worn accelerometers of 42 adolescents. For non-wear episodes longer than 60 min, the heuristic algorithms performed the best with F1-scores above 0.96. However, regarding episodes shorter than 60 min, the best performing method was the decision tree model including the six most important predictors with F1 scores above 0.74 for all sensor locations. We conclude that for classifying non-wear time, researchers should carefully select an appropriate method and we encourage the use of external validation when reporting on machine learned non-wear models.

Gamma frequency sensory stimulation in mild probable Alzheimer's dementia patients: Results of feasibility and pilot studies

Non-invasive Gamma ENtrainment Using Sensory stimulation (GENUS) at 40Hz reduces Alzheimer's disease (AD) pathology such as amyloid and tau levels, prevents cerebral atrophy, and improves behavioral testing performance in mouse models of AD. Here, we report data from (1) a Phase 1 feasibility study (NCT04042922, ClinicalTrials.gov) in cognitively normal volunteers (n = 25), patients with mild AD dementia (n = 16), and patients with epilepsy who underwent intracranial electrode monitoring (n = 2) to assess safety and feasibility of a single brief GENUS session to induce entrainment and (2) a single-blinded, randomized, placebo-controlled Phase 2A pilot study (NCT04055376) in patients with mild probable AD dementia (n = 15) to assess safety, compliance, entrainment, and exploratory clinical outcomes after chronic daily 40Hz sensory stimulation for 3 months. Our Phase 1 study showed that 40Hz GENUS was safe and effectively induced entrainment in both cortical regions and other cortical and subcortical structures such as the hippocampus, amygdala, insula, and gyrus rectus. Our Phase 2A study demonstrated that chronic daily 40Hz light and sound GENUS was well-tolerated and that compliance was equally high in both the control and active groups, with participants equally inaccurate in guessing their group assignments prior to unblinding. Electroencephalography recordings show that our 40Hz GENUS device safely and effectively induced 40Hz entrainment in participants with mild AD dementia. After 3 months of daily stimulation, the group receiving 40Hz stimulation showed (i) lesser ventricular dilation and hippocampal atrophy, (ii) increased functional connectivity in the default mode network as well as with the medial visual network, (iii) better performance on the face-name association delayed recall test, and (iv) improved measures of daily activity rhythmicity compared to the control group. These results support further evaluation of GENUS in a pivotal clinical trial to evaluate its potential as a novel disease-modifying therapeutic for patients with AD.

Self-recorded heart rate variability profiles are associated with health and lifestyle markers in young adults

PURPOSE

To quantify associations between self-recorded heart rate variability (HRV) profiles and various health and lifestyle markers in young adults.

METHODS

Otherwise healthy volunteers (n = 40, 50% male) recorded 60-s, post-waking HRV with a cost-free mobile application in supine and standing positions for 7 days. The 7-day average and coefficient of variation (CV, reflects daily fluctuation) for the mean RR interval and root mean square of successive differences (LnRMSSD) were assessed. 7-day sleep duration and physical activity profiles were characterized via wrist-worn accelerometer. Subsequent laboratory assessments included aerobic fitness ([Formula: see text]O₂peak) and markers of cardiovascular, metabolic, and psychoemotional health. Associations were evaluated before and after [Formula: see text]O₂peak adjustment.

RESULTS

Bivariate correlations (P < 0.05) demonstrated that higher 7-day averages and/or lower CV values were associated with higher activity levels and superior cardiovascular (lower systolic and diastolic blood pressure [BP] and aortic stiffness [cf-PWV]), metabolic (lower body fat percentage, fasting glucose, and low-density lipoprotein cholesterol [LDL-C]), and psychoemotional health (lower perceived stress) markers, with some variation between sexes and recording position. In males, associations between HRV parameters and cf-PWV remained significant following [Formula: see text]O₂peak adjustment (P < 0.05). In females, HRV parameters were associated (P < 0.05) with numerous cardiovascular (systolic and diastolic BP, cf-PWV) and metabolic (fasting glucose and LDL-C) parameters following [Formula: see text]O₂peak adjustment.

CONCLUSIONS

Higher or more stable supine and standing HRV were generally associated with superior health and lifestyle markers in males and females. These findings lay groundwork for future investigation into the usefulness of self-recorded ultra-short HRV as a health-promoting behavior-modification tool in young adults.

Methodological heterogeneity biases physical activity metrics derived from the Actigraph GT3X in multiple sclerosis: A rapid review and comparative study

BACKGROUND

Physical activity (PA) is reduced in persons with multiple sclerosis (MS), though it is known to aid in symptom and fatigue management. Methods for measuring PA are diverse and the impact of this heterogeneity on study outcomes is unclear. We aimed to clarify this impact by comparing common methods for deriving PA metrics in MS populations.

METHODS

First, a rapid review of existing literature identified methods for calculating PA in studies which used the Actigraph GT3X in populations with MS. We then compared methods in a prospective study on 42 persons with MS [EDSS 4.5 (3.5-6)] during a voluntary course of inpatient neurorehabilitation. Mixed-effects linear regression identified methodological factors which influenced PA measurements. Non-parametric hypothesis tests, correlations, and agreement statistics assessed overall and pairwise differences between methods.

RESULTS

In the rapid review, searches identified 421 unique records. Sixty-nine records representing 51 eligible studies exhibited substantial heterogeneity in methodology and reporting practices. In a subsequent comparative study, multiple methods for deriving six PA metrics (step count, activity counts, total time in PA, sedentary time, time in light PA, time in moderate to vigorous PA), were identified and directly compared. All metrics were sensitive to methodological factors such as the selected preprocessing filter, data source (vertical vs. vector magnitude counts), and cutpoint. Additionally, sedentary time was sensitive to wear time definitions. Pairwise correlation and agreement between methods varied from weak (minimum correlation: 0.15, minimum agreement: 0.03) to perfect (maximum correlation: 1.00, maximum agreement: 1.00). Methodological factors biased both point estimates of PA and correlations between PA and clinical assessments.

CONCLUSIONS

Methodological heterogeneity of existing literature is high, and this heterogeneity may confound studies which use the Actigraph GT3X. Step counts were highly sensitive to the filter used to process raw accelerometer data. Sedentary time was particularly sensitive to methodology, and we recommend using total time in PA instead. Several, though not all, methods for deriving light PA and moderate to vigorous PA yielded nearly identical results. PA metrics based on vertical axis counts tended to outperform those based on vector magnitude counts. Additional research is needed to establish the relative validity of existing methods.

A Pilot, Virtual Exercise Intervention Improves Health and Fitness during the COVID-19 Pandemic

Physical activity levels are low in individuals with chronic disease (e.g., obesity) and have worsened during the COVID-19 pandemic.

PURPOSE

Our pilot study tested a virtual exercise intervention for rural-dwelling adults with chronic disease from January-April 2021 for changes in mental health, physical fitness, and physical activity and for intervention fidelity.

METHODS

Participants (n = 8 [7 female]; age = 57.5 ± 13.8 years, body mass index = 38.2 ± 8.0 kg/m²) completed an exercise intervention led virtually by collegiate health science majors. Participants attended two 60-minute sessions/week for 12 weeks, completing individually-tailored and progressed aerobic and muscle-strengthening training. A non-randomized control group matched on gender and age continued normal activity during the 12 weeks. Changes in mental health, physical fitness, and physical activity measures were evaluated using a 2×2 (group × time) analysis of covariance.

RESULTS

Both groups improved mental health, but only intervention participants lost weight (3.1 ± 1.0 kg; no change in controls). Step test, arm curls, and chair stands improved by 16.1-20.6% in the intervention and 7.8-12.1% in the control groups. Intervention participants did not increase overall physical activity during or after the intervention. Intervention fidelity was high; participants attended ~73% of sessions and rated the sessions 4.7 ± 0.6 (out of 5). Researcher observations rated exercise sessions as meeting 12.7 ± 0.6 of 16 goals.

CONCLUSIONS

Our virtual exercise program was associated with positive mental health and physical fitness changes. Such programs may provide a method, even beyond the pandemic, to improve fitness in adults with chronic disease.

Seasonal Variation in Diurnal Rhythms of the Human Eye: Implications for Continuing Ocular Growth in Adolescents and Young Adults

Purpose

To investigate the diurnal rhythms in the human eye in winter and summer in southeast Norway (latitude 60°N).

Methods

Eight measures (epochs) of intraocular pressure, ocular biometry, and optical coherence tomography were obtained from healthy participants (17–24 years of age) on a mid-winter's day (n = 35; 6 hours of daylight at solstice) and on a day the following summer (n = 24; 18 hours of daylight at solstice). Participants wore an activity monitor 7 days before measurements. The epochs were scheduled relative to the individual's habitual wake and sleep time: two in the day (morning and midday) and six in the evening (every hour until and 1 hour after sleep time). Saliva was collected for melatonin. A linear mixed-effects model was used to determine significant diurnal variations, and a sinusoid with a 24-hour period was fitted to the data with a nonlinear mixed-effects model to estimate rhythmic statistics.

Results

All parameters underwent significant diurnal variation in winter and summer (P < 0.002). A 1-hour phase advance was observed for melatonin and ocular axial length in the summer (P < 0.001). The degree of change in axial length was associated with axial length phase advance (R² = 0.81, P < 0.001) and choroidal thickening (R² = 0.54, P < 0.001) in summer.

Conclusions

Diurnal rhythms in ocular biometry appear to be synchronized with melatonin secretion in both winter and summer, revealing seasonal variation of diurnal rhythms in young adult eyes. The association between axial length and seasonal changes in the phase relationships between ocular parameters and melatonin suggests a between-individual variation in adaptation to seasonal changes in ocular diurnal rhythms.

Development and testing of methods for detecting off-wrist in actimetry recordings

Study Objectives

In field studies using wrist-actimetry, not identifying/handling off-wrist intervals may result in their misclassification as immobility/sleep and biased estimations of rhythmic patterns. By comparing different solutions for detecting off-wrist, our goal was to ascertain how accurately they detect nonwear in different contexts and identify variables that are useful in the process.

Methods

We developed algorithms using heuristic (HA) and machine learning (ML) approaches. Both were tested using data from a protocol followed by 10 subjects, which was devised to mimic contexts of actimeter wear/nonwear in real-life. Self-reported data on usage according to the protocol were considered the gold standard. Additionally, the performance of our algorithms was compared to that of visual inspection (by 2 experienced investigators) and Choi algorithm. Data previously collected in field studies were used for proof-of-concept analyses.

Results

All methods showed similarly good performances. Accuracy was marginally higher for one of the raters (visual inspection) than for heuristically developed algorithms (HA, Choi). Short intervals (especially &lt; 2 h) were either not or only poorly identified. Consecutive stretches of zeros in activity were considered important indicators of off-wrist (for both HA and ML). It took hours for raters to complete the task as opposed to the seconds or few minutes taken by the automated methods.

Conclusions

Automated strategies of off-wrist detection are similarly effective to visual inspection, but have the important advantage of being faster, less costly, and independent of raters’ attention/experience. In our study, detecting short intervals was a limitation across methods.

Sleep duration irregularity is associated with elevated blood pressure in young adults

Sleep irregularity (i.e., highly variable sleep patterns) is an emerging risk factor for cardiometabolic disease. Though irregular sleep patterns are common among young adults, the cardiometabolic health (CMH) repercussions of sleep irregularity in this population are unclear. We examined associations between sleep duration and irregularity with measures of CMH in 44 (24 M/20 F, 23 ± 5y, BMI 26 ± 4 kg/m², blood pressure (BP): 125/71 ± 14/9 mmHg) young adults. Participants wore actigraphy monitors for seven-days and sleep duration irregularity was operationalized as the standard deviation of nightly sleep duration (sleep SD). CMH variables of interest included brachial and aortic BP, arterial stiffness (cf-PWV), augmentation index (AIx75), and fasting blood glucose and lipids. Associations between sleep duration and sleep SD with CMH variables were assessed via correlations adjusted for sex and BMI. Sleep duration generally was not associated with CMH indices. However, sleep SD was associated with brachial systolic (r = 0.433, p = .027) and diastolic BP (r = 0.415, p = .035). Similarly, sleep duration SD was associated with aortic systolic BP (r = 0.447, p = .022). Our findings show that sleep irregularity, but not duration, is associated with higher brachial and central BP in young adults.Abbreviations: AIx75: augmentation index at a heart rate of 75 beats per minute; BP: blood pressure; CMH: cardiometabolic health; cf-PWV: carotid-femoral pulse wave velocity; DXA: dual x-ray absorptiometry; mg/dl: milligrams per deciliter; PWA: pulse wave analysis; PWV: pulse wave velocity; sleep duration SD: standard deviation of nightly sleep duration.

Detecting accelerometer non-wear periods using change in acceleration combined with rate-of-change in temperature

Background

Accelerometery is commonly used to estimate physical activity, sleep, and sedentary behavior. In free-living conditions, periods of device removal (non-wear) can lead to misclassification of behavior with consequences for research outcomes and clinical decision making. Common methods for non-wear detection are limited by data transformations (e.g., activity counts) or algorithm parameters such as minimum durations or absolute temperature thresholds that risk over- or under-estimating non-wear time. This study aimed to advance non-wear detection methods by integrating a ‘rate-of-change’ criterion for temperature into a combined temperature-acceleration algorithm.

Methods

Data were from 39 participants with neurodegenerative disease (36% female; age: 45–83 years) who wore a tri-axial accelerometer (GENEActiv) on their wrist 24-h per day for 7-days as part of a multi-sensor protocol. The reference dataset was derived from visual inspection conducted by two expert analysts. Linear regression was used to establish temperature rate-of-change as a criterion for non-wear detection. A classification and regression tree (CART) decision tree classifier determined optimal parameters separately for non-wear start and end detection. Classifiers were trained using data from 15 participants (38.5%). Outputs from the CART analysis were supplemented based on edge cases and published parameters.

Results

The dataset included 186 non-wear periods (85.5% < 60 min). Temperature rate-of-change over the first five minutes of non-wear was − 0.40 ± 0.17 °C/minute and 0.36 ± 0.21 °C/minute for the first five minutes following device donning. Performance of the DETACH (DEvice Temperature and Accelerometer CHange) algorithm was improved compared to existing algorithms with recall of 0.942 (95% CI 0.883 to 1.0), precision of 0.942 (95% CI 0.844 to 1.0), F1-Score of 0.942 (95% CI 0.880 to 1.0) and accuracy of 0.996 (0.994–1.000).

Conclusion

The DETACH algorithm accurately detected non-wear intervals as short as five minutes; improving non-wear classification relative to current interval-based methods. Using temperature rate-of-change combined with acceleration results in a robust algorithm appropriate for use across different temperature ranges and settings. The ability to detect short non-wear periods is particularly relevant to free-living scenarios where brief but frequent removals occur, and for clinical application where misclassification of behavior may have important implications for healthcare decision-making.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01633-6.

Putting Temperature into the Equation: Development and Validation of Algorithms to Distinguish Non-Wearing from Inactivity and Sleep in Wearable Sensors

Long-term monitoring of real-life physical activity (PA) using wearable devices is increasingly used in clinical and epidemiological studies. The quality of the recorded data is an important issue, as unreliable data may negatively affect the outcome measures. A potential source of bias in PA assessment is the non-wearing of a device during the expected monitoring period. Identification of non-wear time is usually performed as a pre-processing step using data recorded by the accelerometer, which is the most common sensor used for PA analysis algorithms. The main issue is the correct differentiation between non-wear time, sleep time, and sedentary wake time, especially in frail older adults or patient groups. Based on the current state of the art, the objectives of this study were to (1) develop robust non-wearing detection algorithms based on data recorded with a wearable device that integrates acceleration and temperature sensors; (2) validate the algorithms using real-world data recorded according to an appropriate measurement protocol. A comparative evaluation of the implemented algorithms indicated better performances (99%, 97%, 99%, and 98% for sensitivity, specificity, accuracy, and negative predictive value, respectively) for an event-based detection algorithm, where the temperature sensor signal was appropriately processed to identify the timing of device removal/non-wear.

Objectively measured preoperative physical activity is associated with time to functional recovery after hepato-pancreato-biliary cancer surgery: a pilot study

BACKGROUND

Surgical resection is currently the cornerstone of hepato-pancreato-biliary (HPB) cancer treatment. A low preoperative aerobic fitness level has been identified as a modifiable risk factor associated with complications after major abdominal surgery. A person's aerobic fitness is influenced by performing moderate to vigorous physical activity (MVPA). This study aims to determine the activity monitor measured levels of MVPA performed among patients on the waiting list for HPB cancer surgery and their association with postoperative outcomes.

METHODS

A prospective, observational multi-center cohort pilot study was conducted. Patients enlisted for resection surgery on suspicion of HPB (pre)malignancy were enrolled. Performed MVPA was measured by an Actigraph wGT3X-BT. Additionally, aerobic fitness was measured via the Incremental Shuttle Walk Test, and (post)operative variables were collected from the electronic patient files. The association between MVPA and the pre- and postoperative variables was determined by univariate and multivariable (logistic) robust regression.

RESULTS

A total of 38 participants, median age 66.0 (IQR 58.25-74.75) years, were enrolled. The median daily MVPA was 10.7 (IQR 6.9-18.0) min; only 8 participants met the Dutch MVPA guidelines. Participant's age and aerobic fitness were associated with MVPA by multivariable statistical analysis. Time to functional recovery was 8 (IQR 5-12) days and was associated with MVPA and type of surgery (major/minor) in multivariable analysis.

CONCLUSION

Seventy-six percent of patients enlisted for resection of HPB (pre)malignancy performed insufficient MVPA. A higher level of MVPA was associated with a shorter time to functional recovery.

Using accelerometers in the assessment of sarcopenia in older adults attending a day hospital service in Ireland

Objectives:

The aim of this study was to describe the associations between sarcopenia and variables derived from wrist accelerometry in community-dwelling older adults attending a day hospital service in Ireland.

Methods:

An observational cross-sectional study was carried out using a consecutive series of older adults attending a day hospital service. Sarcopenia was diagnosed using the latest European Working Group of Sarcopenia in Older People guidelines. Accelerometers were worn by each participant for a 7-day period on their non-dominant wrist.

Results:

Thirty-eight out of forty-one participants (93%) met the accelerometer wear time criterion and were included in statistical analyses. Included participants had a mean age of 81.1 years (standard deviation 6.2). Both sarcopenia (Grip) and sarcopenia (Lower limb) were associated with increased time spent in low physical activity and reduced average of Kcals per hour. Only sarcopenia (Lower limb) was associated with increased time in sedentary behaviour as well as reduced number of steps taken in a week.

Conclusions:

Accelerometer data can be used in an older day hospital population to track physical activity levels and sedentary behaviours. The assessment tool used to assess muscle strength and the cut-off criteria for physical activity behaviour influences the association with sarcopenia.

Comparative assessment of ActiGraph data processing techniques for measuring sedentary behavior in adults with COPD

Objective.The ActiGraph is commonly used for measuring sedentary behavior (SB), but the best data processing technique is not established for sedentary adults with chronic illness. The purpose of this study was to process ActiGraph vertical axis and vector magnitude data with multiple combinations of filters, non-wear algorithm lengths, and cut-points and to compare ActiGraph estimates to activPAL-measured sedentary time in sedentary adults with chronic obstructive pulmonary disease (COPD).Approach.This study was a secondary analysis of adults ≥50 years (N = 59; mean age: 69.4 years;N = 31 males) with COPD. Participants woreActiGraph GT9XandactivPAL3for 7 d. ActiGraph vertical axis and vector magnitude data were processed using combinations of filters (normal, low frequency extension (LFE)), non-wear algorithm lengths (60, 90, 120 min), and cut-points for SB previously validated in older adults (two for vertical axis and three for vector magnitude data). The Bland-Altman method was used to assess concordance between sedentary time measured with 30 ActiGraph techniques and activPAL-measured sedentary time.Main results. Agreement between the two devices was moderate to strong for all techniques; concordance correlations ranged from 0.614 to 0.838. Limits of agreement were wide. The best overall technique was vector magnitude data with LFE filter, 120 min non-wear algorithm, and <40 counts/15 s SB cut-point (concordance correlation 0.838; mean difference -11.7 min d^-1).Significance. This analysis supports the use of ActiGraph vector magnitude data and LFE filter in adults with COPD, but also demonstrates that other techniques may be acceptable with appropriate cut-points. These results can guide ActiGraph data processing decisions.

Relationship between physical activity and dizziness handicap inventory in patients with dizziness -A multivariate analysis

OBJECTIVE

A few studies have analyzed the physical activity in patients with dizziness. Levels of physical activity using 3-axial accelerometer were reported to be lower in patients with chronic dizziness compared to healthy adults. However, the sample size was small and confounding factors were not adjusted in the study. As the age, balance, anxiety, and depression likely contribute to dizziness, the contribution of physical activity to dizziness should be evaluated after adjusting for these potential confounders. We investigated the relationship between physical activity, postural stability, anxiety, and handicap in patients with dizziness using multivariate analysis.

METHODS

This cross-sectional study included 59 patients with dizziness. The physical activity was measured using a 3-axial accelerometer. We also assessed the Dizziness Handicap Inventory (DHI), Hospital and Anxiety and Depression Scale (HADS), and the total center of pressure path length eyes open and eyes closed (COP_EO, COP_EC). To be eligible for analysis, the participants were required to wear the accelerometer for at least four days, with at least 10 h/day of wear time each day.

RESULTS

There were significant differences in the light physical activity (LPA) and moderate to vigorous intensity physical activity (MVPA) between the mild (DHI ≦30) and severe (DHI > 60) groups. Factors that significantly affected the DHI_T score, in order of greater β, were LPA, COP_EC, female, and HADS_A (β = -0.546, 0.459, 0.437, 0.239, respectively).

CONCLUSIONS

The present study demonstrated that the patients in the severe group had shorter LPA and MVPA times than that of the patients in the mild group. Additionally, LPA was associated with DHI_T in patients with dizziness. Therefore, physical activity, especially LPA (e.g., activities of daily living), may need to be assessed in patients with dizziness.

A novel algorithm to detect non-wear time from raw accelerometer data using deep convolutional neural networks

To date, non-wear detection algorithms commonly employ a 30, 60, or even 90 mins interval or window in which acceleration values need to be below a threshold value. A major drawback of such intervals is that they need to be long enough to prevent false positives (type I errors), while short enough to prevent false negatives (type II errors), which limits detecting both short and longer episodes of non-wear time. In this paper, we propose a novel non-wear detection algorithm that eliminates the need for an interval. Rather than inspecting acceleration within intervals, we explore acceleration right before and right after an episode of non-wear time. We trained a deep convolutional neural network that was able to infer non-wear time by detecting when the accelerometer was removed and when it was placed back on again. We evaluate our algorithm against several baseline and existing non-wear algorithms, and our algorithm achieves a perfect precision, a recall of 0.9962, and an F1 score of 0.9981, outperforming all evaluated algorithms. Although our algorithm was developed using patterns learned from a hip-worn accelerometer, we propose algorithmic steps that can easily be applied to a wrist-worn accelerometer and a retrained classification model.

Relationships between College Students' Sedentary Behavior, Sleep Quality, and Body Mass Index

PURPOSE

Sedentary behavior (SB), sleep efficiency (SE), sleep duration (SD), and body mass index (BMI) are crucial determinants of an individual's health. However, empirical evidence regarding associations between these factors in young adults living in China remains unknown. Therefore, the purpose of this study was to examine the relationships between accelerometer-measured SB, SE, SD, and BMI in Chinese college students.

METHODS

Two-hundred and twenty college students (115 females, Meanage = 20.29 years, SD = 2.37) were recruited from a south-central Chinese university. Participants' SB (daily % time spent in SB), SE (number of minutes of sleep duration/number of minutes in bed), and SD were assessed via wrist-worn ActiGraph GT9X Link accelerometers for one week. Body weight was measured using a digital weight scale, height was measured using a stadiometer, and BMI was calculated as weight (kg)/height (m2).

RESULTS

Participants' average time spent in SB was 76.52% (SD = 10.03), SE was 84.12% (SD = 4.79), and BMI was 20.67 kg/m2 (SD = 3.12), respectively. Regression analyses indicated that SB (β = -0.17, p = 0.01) and BMI (β = -0.20, p < 0.01) negatively predicted SE. In addition, BMI negatively predicted SD (β = -0.22, p < 0.01).

CONCLUSION

Prolonged SB (e.g., screen viewing, smartphone use, and computer playing) and higher BMI may link to shorter sleep duration and lower sleep efficiency in Chinese young adults. Future randomized controlled trials are needed to further confirm these findings. Given that increased BMI status and SB may relate to adverse health outcomes, more population-based intervention strategies seeking to lower BMI and reduce SB (e.g., nutrition education and physical activity promotion) are needed in this population.

Replacing school and out-of-school sedentary behaviors with physical activity and its associations with adiposity in children and adolescents: a compositional isotemporal substitution analysis

BACKGROUND

Little is known on how context-specific sedentary behaviors (SB) affect adiposity. This study aimed to investigate compositional associations between context-specific SB and adiposity and estimate the differences in adiposity associated with replacing school and out-of-school SB with physical activity (PA).

METHODS

This study included 336 children and adolescents. Time spent in SB and PA was estimated using multi-day 24-hour raw accelerometer data. SB and PA were specified for school and out-of-school times. Fat mass percentage (FM%) and fat mass index (FMI) were used as adiposity indicators. A compositional isotemporal substitution model was used to estimate differences in adiposity associated with one-to-one reallocations of time from context-specific SB to PA.

RESULTS

Participants spent approximately two thirds of their school and out-of-school time being sedentary. Relative to the remaining 24-h movement behaviors, significant associations between out-of-school SB and adiposity were found in both boys (β_ilr1 = 0.63, 95% confidence interval [CI] = 0.03-1.22 for FM%; β_ilr1 = 0.76, 95% CI = 0.03-1.49 for FMI) and girls (β_ilr1 = 0.62, 95% CI = 0.25-0.98 for FM%; β_ilr1 = 0.80, 95% CI = 0.28-1.32 for FMI). Replacing 30 min/day of out-of-school SB with out-of-school light PA decreased FM% by 10.1% (95% CI = 3.3-17.9) and FMI by 14% (95% CI = 2.7-24) in girls. No significant associations were found for school SB.

CONCLUSIONS

A reduction of out-of-school SB in favor of light PA should be advocated as an appropriate target for interventions and strategies to prevent childhood obesity.

[Influences of Autonomic Function, Salivary Cortisol and Physical Activity on Cognitive Functions in Institutionalized Older Adults with Mild Cognitive Impairment: Based on Neurovisceral Integration Model]

PURPOSE

This study aimed to investigate objectively measured physical activity (PA) in institutionalized older adults with mild cognitive impairment (MCI) and to elucidate the influence of autonomic nervous function, salivary cortisol, and PA on cognitive functions based on neurovisceral integration model.

METHODS

Overall cognitive function was evaluated using the mini-mental state examination (MMSE) and executive function was evaluated using semantic verbal fluency test and clock drawing test. Actigraph for PA, HRV and sAA for autonomous function, and the geriatric depression scale for depression were used. Saliva specimens were collected in the morning for sAA and cortisol.

RESULTS

Ninety-eight older adults from four regional geriatric hospitals participated in the study. They took 4,499 steps per day on average. They spent 753.93 minutes and 23.12 minutes on average in sedentary and moderate-to-vigorous activity, respectively. In the multiple regression analysis, lower salivary cortisol level (β = - .33, p = .041) and greater step counts (β = .37, p = .029) significantly improved MMSE score. Greater step count (β = .27, p = .016) also exerted a significant influence on verbal fluency, and greater sAA (β = .35, p = .026) was significantly associated with a better clock drawing test result.

CONCLUSION

Salivary cortisol, sAA and physical activity were significantly associated with cognitive functions. To prevent older adults from developing dementia, strategies are needed to increase their overall PA amount by decreasing sedentary time and to decrease salivary cortisol for cognitive function, and to maintain their sympathetic nervous activity for executive function.

The Two-Minute Walk Test in Persons with Multiple Sclerosis: Correlations of Cadence with Free-Living Walking Do Not Support Ecological Validity

The two-minute walk test (2MWT) is a frequently used walking capacity test in persons with multiple sclerosis (pwMS). However, less is known about its relevance with regards to walking capacity during free-living walking performance. Therefore, the ecological validity of the 2MWT was tested by 1. computing free-living minutes with the same intensity (cadence) as during the 2MWT and 2. investigating the relationship between 2MWT cadence and minutes with the same cadence during free-living walking. 20 pwMS aged 44.2 ± 12.2 (Expanded Disability Status Scale (EDSS) score of 3.1 ± 1.4) performed a 2MWT and wore an accelerometer for seven days. The number of pwMS reaching 100%, 90%, 80% or 70% of 2MWT cadence for at least one minute a day and minutes/day with at least 100%, 90%, 80% and 70% of 2MWT cadence during free-living walking was calculated. Six participants reached 100% of the 2MWT cadence for at least one minute/day during free-living walking. A total of 80% 2MWT cadence was the first intensity category that was reached by all participants during free-living walking. No significant correlation was found between cadence in the 2MWT and minutes in which this cadence was reached during free-living walking. Ecological validity with regard to walking intensity could not be confirmed in our study sample.

The Use of Inertial Measurement Units for the Study of Free Living Environment Activity Assessment: A Literature Review

This article presents an overview of fifty-eight articles dedicated to the evaluation of physical activity in free-living conditions using wearable motion sensors. This review provides a comprehensive summary of the technical aspects linked to sensors (types, number, body positions, and technical characteristics) as well as a deep discussion on the protocols implemented in free-living conditions (environment, duration, instructions, activities, and annotation). Finally, it presents a description and a comparison of the main algorithms and processing tools used for assessing physical activity from raw signals.

Sedentary Behaviors and Physical Activity Habits Independently Affect Fat Oxidation in Fasting Conditions and Capillary Glucose Levels After Standardized Glucose-Rich Meal in Healthy Females

Purpose

Sedentary behaviors and muscle inactivity are being growingly recognized as important risk factors for health, adjunctively and independently from a scarce physical activity (PA), although the metabolic mechanism underneath is barely clear. To explore the relation between sedentary behaviors (SBs) and metabolism, we measured the metabolic profile in fasting condition and after oral glucose overload in a group of women, along with objective monitoring of their PA/sedentary lifestyle habits.

Subjects and Methods

Thirteen women (age: 32.5 ± 16.1 years; BMI: 24.0 ± 3.3 kg/m²), recruited among university students and research staff, underwent indirect calorimetry to assess fat and carbohydrate contribution to energy metabolism, in fasting conditions and after a glucose-rich standard meal (about 45 g of glucose). Glucose concentration in capillary blood was determined in fasting state and 15 and 30 min after meal. Habitual PA and SBs in the previous week were continuously monitored with Actigraph accelerometers.

Results

After adjustment for age, the contribution of fat oxidation to metabolic energy sources, normalized for fat-free mass, in fasting conditions was significantly correlated with time spent in sitting/lying position during wake hours (p < 0.001), independent from PA habits, whereas capillary blood peak and change of glucose concentration after the meal were significantly and inversely correlated with average daily moderate to vigorous PA (p = 0.025 and p = 0.019, respectively), independent from average daily sitting/lying time.

Conclusions

Here, we report for the first time a direct effect of muscle inactivity on increased fat oxidation in fasting conditions, which can be hypothesized as a preliminary condition for the development of insulin resistance. We also report the direct independent effect of PA on the capacity to respond to a glycemic load, so that SBs and reduced PA appear to concur, although independently, to the increased health risk, as elsewhere observed on an epidemiological ground.

Cohort profile: the AUstralian Twin BACK pain and physical activity study (AUTBACK study)

PURPOSE

Despite the growing evidence that physical activity and familial factors play a role in low back pain (LBP), there is a lack of robust longitudinal studies that (1) investigate the types and dosages of physical activity that are protective or harmful for LBP, (2) employ objective measures of physical activity and (3) conduct appropriate adjustment for confounders. The AUstralian Twin BACK (AUTBACK) study was established to elucidate the longitudinal LBP-physical activity relationship with the benefits of controlling for familial (both genetic/nongenetic) factors that may influence physical activity engagement and LBP.

PARTICIPANTS

Participants are twins registered at Twins Research Australia (TRA), older than 18 years, with access to internet. We collected data on LBP status (weekly) and physical activity levels (monthly) for 12 months as well as a wide range of health, lifestyle and physical activity (objective, self-reported, including different types and dosages) data.

FINDINGS TO DATE

We included 401 twins, 157 being complete twin pairs (n=314). Lifetime prevalence of LBP was 85%. Participants spent 61% of their week in sedentary time and only 4% in moderate/vigorous intensity physical activity (accelerometer). So far, 168 participants (40% of the sample) have completed the 12-month follow-up. A total of 7150 weekly (LBP status) and 1763 monthly questionnaires (physical activity status) have been answered (92% response rate).

FUTURE PLANS

The 12-month follow-up will be completed by June 2020. This cohort represents a novel and comprehensive resource for researchers in the field, and includes high-quality, and frequent data on LBP and physical activity. It allows the investigation of genetic and shared environmental factors on the LBP-physical activity relationship. The AUTBACK group has planned a number of projects, with the main one being the investigation of the influence of physical activity on recurrence of LBP. Data linkage opportunities are available, including with other studies conducted by TRA.

Technology for monitoring everyday prosthesis use: a systematic review

BACKGROUND

Understanding how prostheses are used in everyday life is central to the design, provision and evaluation of prosthetic devices and associated services. This paper reviews the scientific literature on methodologies and technologies that have been used to assess the daily use of both upper- and lower-limb prostheses. It discusses the types of studies that have been undertaken, the technologies used to monitor physical activity, the benefits of monitoring daily living and the barriers to long-term monitoring, with particular focus on low-resource settings.

METHODS

A systematic literature search was conducted in PubMed, Web of Science, Scopus, CINAHL and EMBASE of studies that monitored the activity of prosthesis users during daily-living.

RESULTS

Sixty lower-limb studies and 9 upper-limb studies were identified for inclusion in the review. The first studies in the lower-limb field date from the 1990s and the number has increased steadily since the early 2000s. In contrast, the studies in the upper-limb field have only begun to emerge over the past few years. The early lower-limb studies focused on the development or validation of actimeters, algorithms and/or scores for activity classification. However, most of the recent lower-limb studies used activity monitoring to compare prosthetic components. The lower-limb studies mainly used step-counts as their only measure of activity, focusing on the amount of activity, not the type and quality of movements. In comparison, the small number of upper-limb studies were fairly evenly spread between development of algorithms, comparison of everyday activity to clinical scores, and comparison of different prosthesis user populations. Most upper-limb papers reported the degree of symmetry in activity levels between the arm with the prosthesis and the intact arm.

CONCLUSIONS

Activity monitoring technology used in conjunction with clinical scores and user feedback, offers significant insights into how prostheses are used and whether they meet the user's requirements. However, the cost, limited battery-life and lack of availability in many countries mean that using sensors to understand the daily use of prostheses and the types of activity being performed has not yet become a feasible standard clinical practice. This review provides recommendations for the research and clinical communities to advance this area for the benefit of prosthesis users.

Associations of participation in organized sports and physical activity in preschool children: a cross-sectional study

Background

Participation in organized sports is associated with higher physical activity (PA) levels in school-aged-children. Yet, little is known about PA determinants in preschool-aged-children. We examined associations between organized sports participation and preschoolers’ daily PA.

Methods

The study comprised 290 3–5 years old children and PA was measured for 1 week via accelerometers. Organized sports participation was parent-reported and preschool arrival and departure time was teacher-recorded. The preschool duration reported by teachers was matched with time-stamped accelerometer data to distinguish PA during preschool time and PA outside preschool time. Linear mixed models, nested on preschool level, were used to examine associations between organized sports participation and children’s PA outside preschool time, during preschool time and throughout the day.

Results

In total, 146 children (50.3%) participated in organized sports at least 1 h/week. Participation in organized sports was associated with 6.0 more minutes of moderate-to-vigorous PA (MVPA) (95% CI: 0.6, 11.3) throughout the day and 5.7 more minutes of MVPA (95% CI: 1.6, 9.7) outside preschool time after adjustment. There was no association between organized sports participation and PA during preschool time.

Conclusions

This is the first study to show positive associations between organized sports participation and preschoolers’ PA levels outside preschool time and throughout the day. In addition, findings from this study do not support PA compensation. Therefore, targeting organized sports may be successful in improving PA, even among preschoolers.

Evaluating the performance of raw and epoch non-wear algorithms using multiple accelerometers and electrocardiogram recordings

Accurate detection of accelerometer non-wear time is crucial for calculating physical activity summary statistics. In this study, we evaluated three epoch-based non-wear algorithms (Hecht, Troiano, and Choi) and one raw-based algorithm (Hees). In addition, we performed a sensitivity analysis to provide insight into the relationship between the algorithms’ hyperparameters and classification performance, as well as to generate tuned hyperparameter values to better detect episodes of wear and non-wear time. We used machine learning to construct a gold-standard dataset by combining two accelerometers and electrocardiogram recordings. The Hecht and Troiano algorithms achieved poor classification performance, while Choi exhibited moderate performance. Meanwhile, Hees outperformed all epoch-based algorithms. The sensitivity analysis and hyperparameter tuning revealed that all algorithms were able to achieve increased classification performance by employing larger intervals and windows, while more stringently defining artificial movement. These classification gains were associated with the ability to lower the false positives (type I error) and do not necessarily indicate a more accurate detection of the total non-wear time. Moreover, our results indicate that with tuned hyperparameters, epoch-based non-wear algorithms are able to perform just as well as raw-based non-wear algorithms with respect to their ability to correctly detect true wear and non-wear episodes.

Automatic Posture and Movement Tracking of Infants with Wearable Movement Sensors

Infants’ spontaneous and voluntary movements mirror developmental integrity of brain networks since they require coordinated activation of multiple sites in the central nervous system. Accordingly, early detection of infants with atypical motor development holds promise for recognizing those infants who are at risk for a wide range of neurodevelopmental disorders (e.g., cerebral palsy, autism spectrum disorders). Previously, novel wearable technology has shown promise for offering efficient, scalable and automated methods for movement assessment in adults. Here, we describe the development of an infant wearable, a multi-sensor smart jumpsuit that allows mobile accelerometer and gyroscope data collection during movements. Using this suit, we first recorded play sessions of 22 typically developing infants of approximately 7 months of age. These data were manually annotated for infant posture and movement based on video recordings of the sessions, and using a novel annotation scheme specifically designed to assess the overall movement pattern of infants in the given age group. A machine learning algorithm, based on deep convolutional neural networks (CNNs) was then trained for automatic detection of posture and movement classes using the data and annotations. Our experiments show that the setup can be used for quantitative tracking of infant movement activities with a human equivalent accuracy, i.e., it meets the human inter-rater agreement levels in infant posture and movement classification. We also quantify the ambiguity of human observers in analyzing infant movements, and propose a method for utilizing this uncertainty for performance improvements in training of the automated classifier. Comparison of different sensor configurations also shows that four-limb recording leads to the best performance in posture and movement classification.