Accelerometer-based Activity Research Articles

Predicting Adolescents' Physical Activity Intentions: Testing an Integrated Social Cognition Model.

Few adolescents meet guideline levels of physical activity associated with good health, highlighting the need for intervention. Interventions promoting adolescents' physical activity should be guided by research applying behavioral theory to identify potentially modifiable correlates and associated processes. We applied an integrated social cognition model to identify theory-based constructs and processes that relate to physical activity intentions in a secondary analysis of two samples of Finnish adolescents using a correlational design. Participants in the first sample (n = 455) completed self-report measures of social cognition constructs from theory of planned behavior, habit, self-discipline, and past and current physical activities. Participants in the second sample (n = 3878) completed identical measures plus measures of socio-structural and socio-environmental factors. Participants from the first sample also wore accelerometers for 1week. Hypothesized model effects were tested using variance-based structural equation modeling in data from the first sample and subsequently confirmed in a pre-registered analysis of data from the second sample. Across both samples, habit, attitude, perceived behavioral control, and self-reported past behavior were associated with physical activity intention. Effects of self-reported past physical activity on intention were partially mediated by social cognition constructs. Effects of accelerometer-based physical activity were small by comparison. Effects of socio-structural and socio-environmental factors on intention in the second sample were partially mediated by the social cognition constructs. Results corroborate beliefs and habit as consistent correlates of adolescents' physical activity intentions and provide preliminary evidence that social cognition constructs account for effects of socio-structural and socio-environmental factors on intentions.

Physical activity and physical fitness in children with heritable connective tissue disorders.

Health problems in patients with heritable connective tissue disorders (HCTD) are diverse and complex and might lead to lower physical activity (PA) and physical fitness (PF). This study aimed to investigate the PA and PF of children with heritable connective tissue disorders (HCTD). PA was assessed using an accelerometer-based activity monitor (ActivPAL) and the mobility subscale of the Pediatric Evaluation of Disability Inventory Computer Adaptive Test (PEDI-CAT). PF was measured in terms of cardiovascular endurance using the Fitkids Treadmill Test (FTT); maximal hand grip strength, using hand grip dynamometry (HGD) as an indicator of muscle strength; and motor proficiency, using the Bruininks-Oseretsky Test of Motor Proficiency-2 (BOTMP-2). A total of 56 children, with a median age of 11.6 (interquartile range [IQR], 8.8-15.8) years, diagnosed with Marfan syndrome (MFS), n = 37, Loeys-Dietz syndrome (LDS), n = 6, and genetically confirmed Ehlers-Danlos (EDS) syndromes, n = 13 (including classical EDS n = 10, vascular EDS n = 1, dermatosparaxis EDS n = 1, arthrochalasia EDS n = 1), participated. Regarding PA, children with HCTD were active for 4.5 (IQR 3.5-5.2) hours/day, spent 9.2 (IQR 7.6-10.4) hours/day sedentary, slept 11.2 (IQR 9.5-11.5) hours/day, and performed 8,351.7 (IQR 6,456.9-1,0484.6) steps/day. They scored below average (mean (standard deviation [SD]) z-score -1.4 (1.6)) on the PEDI-CAT mobility subscale. Regarding PF, children with HCTD scored well below average on the FFT (mean (SD) z-score -3.3 (3.2)) and below average on the HGD (mean (SD) z-score -1.1 (1.2)) compared to normative data. Contradictory, the BOTMP-2 score was classified as average (mean (SD) z-score.02 (.98)). Moderate positive correlations were found between PA and PF (r(39) = .378, p < .001). Moderately sized negative correlations were found between pain intensity and fatigue and time spent actively (r(35) = .408, p < .001 and r(24) = .395 p < .001, respectively). This study is the first to demonstrate reduced PA and PF in children with HCTD. PF was moderately positively correlated with PA and negatively correlated with pain intensity and fatigue. Reduced cardiovascular endurance, muscle strength, and deconditioning, combined with disorder-specific cardiovascular and musculoskeletal features, are hypothesized to be causal. Identifying the limitations in PA and PF provides a starting point for tailor-made interventions.

Accelerometer-based physical activity in need satisfaction profiles of schoolchildren: A 3-year follow-up

This study examined moderate-to-vigorous physical activity (MVPA) trends in physical education (PE) classes and beyond school hours in children's need satisfaction profiles over 3 years. Participants were 445 (girls 256, boys 189) Finnish schoolchildren ( Mage = 11.26 ± 0.32 years). Need satisfaction self-reports and accelerometer-based MVPA data were collected in 17 comprehensive schools over four assessment phases. Four latent profiles based on the need satisfaction trends over time were found: Profiles with Large Decrease, Small Decrease, Small Increase, and Large Increase. The children with the most prominent need satisfaction decreases showed a significant decline in out-of-school MVPA. All the children, irrespective of their need satisfaction profile, exhibited similar patterns of MVPA in PE over the 3-year follow-up. Developing need satisfactions and out-of-school MVPA of the children with the greatest need satisfaction decreases may require enhancements in need-supportive PE activities.

Weekly variations of accelerometer variables and workload of professional soccer players from different positions throughout a season

The current study aimed to analyze, using accelerometer-based activity, acute workload, chronic workload, acutechronic workloads ratio, training-monotony and training-strain throughout a competitive soccer-season and to compare these variables between players from different playing positions. Twenty-one professional soccer-players were monitored during the 48 weeks of the season. Players were grouped according to their position. Four lateral-defenders and four winger-players formed LDW group, four central-defenders and four forwards formed CDF group, and six midfielder-players formed MDF group. Accelerometer-based variables were collected during training and match contexts and were used to generate indicators of weekly acute and chronic workload, training monotony, training strain and metabolic power. A one-way ANOVA compared all dependent variables between groups, and effect sizes for pairwise comparisons were calculated. Results revealed variations in the weekly load throughout the season, which demands caution from coaches to avoid injuries. There were no differences in weekly-loads for all dependent variables (P > 0.05, small-to-moderate effects). We conclude that the weekly-load is not constant during a competitive season and players from different positions have similar weekly-loads. Therefore, previously reported in the literature, possible match-related positional differences might be compensated by differences in training-related loads, leading to a similar profile when considering the whole week.

ABIPA: ARIMA-Based Integration of Accelerometer-Based Physical Activity for Adolescent Weight Status Prediction

Obesity is a global health concern associated with various demographic and lifestyle factors including physical activity (PA). Research studies generally used self-reported PA data or, when accelerometer-based activity trackers were used, highly aggregated data (e.g., daily average). This suggests that the rich potential of detailed activity tracker data is largely under-exploited and that deeper analyses may help better understand such relationships. This is particularly true in children and adolescents who are distinct and engage more in bursts of PA. This article presents ABIPA, a machine learning-based methodology that integrates various aspects of accelerometer-based PA data into weight status prediction for adolescents. We propose a method to derive features regarding the structure of different PA time series using Auto-Regressive Integrated Moving Average (ARIMA). The ARIMA-based PA features are combined with other individual attributes to predict weight status and the importance of these features is further unveiled. We apply ABIPA to a dataset about young adolescents (N = 206) containing, for each participant, a 7-day continuous accelerometer dataset (60 Hz, GENEActiv tracker from ActivInsights) and a range of their socio-demographic, anthropometric, and lifestyle information. The results indicate that our method provides a practical approach for integrating accelerometer-based PA patterns into weight status prediction and paves the way for validating their importance in understanding obesity factors.

Effect of Equipment on the Accuracy of Accelerometer-Based Human Activity Recognition in Extreme Environments.

A little explored area of human activity recognition (HAR) is in people operating in relation to extreme environments, e.g., mountaineers. In these contexts, the ability to accurately identify activities, alongside other data streams, has the potential to prevent death and serious negative health events to the operators. This study aimed to address this user group and investigate factors associated with the placement, number, and combination of accelerometer sensors. Eight participants (age = 25.0 ± 7 years) wore 17 accelerometers simultaneously during lab-based simulated mountaineering activities, under a range of equipment and loading conditions. Initially, a selection of machine learning techniques was tested. Secondly, a comprehensive analysis of all possible combinations of the 17 accelerometers was performed to identify the optimum number of sensors, and their respective body locations. Finally, the impact of activity-specific equipment on the classifier accuracy was explored. The results demonstrated that the support vector machine (SVM) provided the most accurate classifications of the five machine learning algorithms tested. It was found that two sensors provided the optimum balance between complexity, performance, and user compliance. Sensors located on the hip and right tibia produced the most accurate classification of the simulated activities (96.29%). A significant effect associated with the use of mountaineering boots and a 12 kg rucksack was established.

A TECHNOLOGY-BASED BODY-MIND INTERVENTION FOR LOW-INCOME AMERICAN OLDER ADULTS

Abstract Research is limited on the use of technology to help individuals who have a mismatch between physiological fall risk (Body) and perceived fall risk (Mind) and are unable to access traditional fall interventions. We examined the feasibility and acceptability of a technology-based body-mind intervention in low-income older adults during the COVID-19 pandemic and explored barriers to access and adopting the technology. Data were collected using a survey, balance test, accelerometer-based physical activity (PA), and semi-structured interviews with twenty participants who engaged in an 8-week intervention at a low-income setting in Florida. We found that: 1) the technology-based intervention is feasible, 2) participants tend to accept technology to alter their perceptions of fall risk and balance capacity, 3) tailored activities to each component are not a one-size-fits-all approach. There were no statistically significant changes in sedentary time, light PA, and moderate to vigorous PA between pre and post-intervention.

FALL RISK, FEAR OF FALLING, PHYSICAL ACTIVITY, AND SELF-PERCEPTIONS IN ETHNICALLY DIVERSE LOW-INCOME OLDER ADULTS

Abstract Falls and fear of falling (FOF) are the leading cause of disability, and hospitalization in ethnically diverse low-income older adults. The present study included an ethnically diverse sample of low-income older adults (N=121) to examine ethnic and income-based group differences in risk factors for falls (high FOF, depression, avoidance of physical activity) and the role of negative self-perceptions of aging in driving these risk factors. Results revealed the highest levels of fall risk among Hispanics and Asian Americans, FOF among African Americans, and depression among Hispanics. Accelerometer-based physical activity measures confirmed that low-income older adults had lower levels of moderate to vigorous physical activity (MVPA) compared with their high-income counterparts (p=0.04). Further, financial difficulty was related to MVPA (p&amp;lt;0.001), depression, anxiety, and fall risk (p=0.01). Critically, we also found a strong relationship between negative self-perceptions of aging and FOF (p = 0.002) across groups.

Physical activity and risk of gallstone disease: A Mendelian randomization study.

Objective: Given the association between physical activity and the reduced risk of gallstone disease as suggested in observational studies, a Mendelian randomization study was conducted to evaluate the causal nature of this association in genetic epidemiology. Study: Including self-reported and accelerometer-based physical activity traits, the independent genetic variants associated with physical activity were selected from the corresponding genome-wide association studies as instrumental variables. The summary-level data for gallstone disease were sourced from the UK Biobank (7,682 cases and 455,251 non-cases) and FinnGen consortium (23,089 cases and 231,644 non-cases). Then, two-sample Mendelian randomization analysis was conducted. Inverse-variance weight (IVW), weighted median, and Mendelian randomization-Egger regression were determined through Mendelian randomization analyses. To ensure the robustness of the results, sensitivity analyses were also carried out in the study. Results: The negative causality between the genetically predicted accelerometer-based "average acceleration" physical activity and the risk of gallstone disease was suggested in the UK Biobank study (p = 0.023, OR = 0.93, 95% CI: 0.87-0.99), and accelerometer-based "overall activity" physical activity and the risk of gallstone disease in the UK Biobank study (p = 0.017, OR = 0.38, 95% CI: 0.17-0.84). With accelerometer-based "average acceleration" physical activity negatively correlated with gallstone disease in the FinnGen consortium data (p = 0.001, OR = 0.94, 95% CI: 0.90-0.97). As for self-reported moderate-to-vigorous physical activity, however, there was no causality observed in both pieces of data. Conclusion: Our studies provide the evidence suggesting a casual association between physical activities and gallstone disease through analysis of genetic data. As indicated by the research results, there is a possibility that a higher level of physical activities could mitigate the risk of gallstone disease.

Accelerometer-Assessed Physical Activity and Cognitive Performance among European Adults Aged 50+: The Mediating Effects of Social Contacts and Depressive Symptoms.

Cognitive decline is a major public health concern worldwide and it is vital to identify and better understand effective population-based means to improve cognitive performance in old age. The current study set out to examine the links between accelerometer-based physical activity with cognitive performance in later life, as well the indirect pathways through one's social network contacts and depression. We used data from 855 participants aged 50 and above who took part in a cross-sectional accelerometer study as part of the Survey of Ageing, Retirement and Health (SHARE). Cognitive function was measured as an average score of fluency, immediate and delayed recall tests, social contacts were the average contact frequency with members of the social support network, and depression was the Euro-D summary score of depressive symptoms. A multiple mediation analysis was conducted to test the direct and indirect associations between total physical activity (intensity gradient) and cognitive function, as well as the mediation of this association by social contacts and depressive symptoms. Intensity of physical activity was directly related to better cognitive performance (B = 0.170, p = 0.007). The association was partially mediated by social contacts (B = 0.022, 95% CI 0.005, 0.046) and depressive symptoms (B = 0.009, 95% CI 0.009, 0.025), such that total physical activity was linked to cognitive health via more frequent contacts with network members and low depressive symptoms. Practitioners might consider encouraging a physically active lifestyle that involves social interactions to support better cognitive aging and mental health.

Responsiveness and trajectory of changes in the rating of everyday arm-use in the community and home (REACH) scale over the first-year post-stroke

Objective To examine the trajectory of the Rating of Everyday Arm-use in the Community and Home (REACH) scores over the first-year post-stroke, determine if REACH scores are modified by baseline impairment level and explore the responsiveness of the REACH scale through hypothesis testing. Design Consecutive sample longitudinal study. Setting Participants were recruited from an acute stroke unit and followed up at three, six, and 12 months post-stroke. Participants Seventy-three participants with upper limb weakness (Shoulder Abduction and Finger Extension score ≤ 8). Main Measures The REACH scale is a six-level self-report classification scale that captures how the affected upper limb is being used in one's own environment. The Fugl-Meyer Upper Limb Assessment (FMA-UL), Stroke Upper Limb Capacity Scale (SULCS), accelerometer-based activity count ratio and Global Rating of Change Scale (GRCS) were used to capture upper limb impairment, capacity, and use. Results The following proportions of participants improved at least one REACH level: 64% from baseline to three months, 37% from three to six months and 13% from six to 12 months post-stroke. The trajectory of REACH scores over time was associated with baseline impairment. Change in REACH had a moderate correlation to change in SULCS and the GRCS but not FMA-UL or the activity count ratio. Conclusions Results of hypothesis testing provide preliminary evidence of the responsiveness of the REACH scale. On average, individuals with severe impairment continued to show improvement in use over the first year, while those with mild/moderate impairment plateaued and a small proportion decreased in the early chronic phase.

Individual and country-level factors associated with self-reported and accelerometer-based physical activity in old age: a cross-national analysis of European countries

This study aimed to investigate associations between individual-level (personality traits, quality of life) and country-level (gross domestic product per capita, number of policies and action plans for physical activity) factors with self-reported and accelerometer-based physical activity and cross-level interactions among European countries. Based on the Survey of Health, Ageing and Retirement in Europe (SHARE) from 2019–2020, self-reported physical activity (N = 46,617 from 27 countries) and accelerometer-based average acceleration and intensity gradient (N = 855 from 10 countries) were analyzed. Mixed-model regressions with two levels (individuals nested within countries) were used for analyses. Between countries differences accounted for relatively small portions of the variability in self-reported physical activity (intraclass correlation, ICC = 7.5%), average acceleration (ICC = 3.5%), and intensity gradient (ICC = 1.9%). There were more associations between individual- and country-level factors and self-reported physical activity than with accelerometer-based physical activity. The association between individual-level variables and accelerometer-based physical activity did not differ between countries. Cross-level interactions suggested that associations between some personality traits and self-reported physical activity were stronger in countries with lower GDP. Both individual- and country-level factors are related to participation in more intensive physical activities. Adults with less resilient personality traits living in countries with lower resources are at the highest risk for physical inactivity.

Life-Space Mobility and Objectively Measured Movement Behavior in Older Adults with Hypertension after Receiving COVID-19 Vaccination.

This study examined the changes in life-space (LS) mobility and objectively measured movement behavior in older adults with hypertension after receiving the COVID-19 vaccine and their associations with housing type. A total of 32 participants were included in this exploratory longitudinal study with a 1-year follow-up. LS mobility and accelerometer-based physical activity (PA) and sedentary behavior (SB) were assessed before and ~2 months after receiving COVID-19 vaccination. Participants residing in apartment/row housing showed an increase in LS mobility composite score (β = 14, p < 0.05). In addition, they showed an increase in light PA on weekdays and the weekend (β = 3.5%; β = 6.5%; p < 0.05) and a decrease in SB on weekdays and the weekend (β = −3.7%; β = −6.6%; p < 0.05). Furthermore, changes in SB pattern were found (less time spent in bouts of ≥10 and 30 min, more breaks/day and breaks/hour). Significant associations were found between changes in LS mobility composite score and PA (positive association) and SB (negative association) in older adults residing in apartment/row housing (p < 0.05). Older adults with hypertension, particularly those who resided in houses with limited outdoor space (apartment/row housing), showed positive changes in LS mobility and objectively measured movement behavior in a period after receiving the COVID-19 vaccine and characterized by social distancing policies without mobility restrictions when compared with the period of social distancing policies with high mobility restrictions and without vaccine.

Sensor-based detection of a Haemonchus contortus (Barber's pole worm) infection in sheep

Haemonchus contortus, or Barber's Pole worm, is considered one of the most pathogenic parasites of sheep due to the production, profitability and animal welfare implications associated with infections. However, detection of H. contortus infections by routine observation of sheep flocks is difficult, and producers are usually unaware of a problem until animals are severely infected. The aim of the current study was to explore the potential for accelerometer-based activity monitoring to detect H. contortus infections in sheep.A three-month clinical study was conducted in Central Queensland, Australia, whereby 45, 12-month-old merino wethers were randomly allocated to one of three treatment groups: control (n = 9), low H. contortus infection (n = 18) or high H. contortus infection (n = 18). Infection occurred on Day 0, and accelerometer sensors were attached to a halter and deployed on all animals from Day 21 to Day 70. Animals were sampled weekly (faecal and blood) and treated with an anthelmintic on Day 56. Following the clinical period, five study animals were observed for a total of five hours to compare direct behavioral observations against accelerometer data. This was then used to develop a machine learning (ML) model to classify the accelerometer data into active or inactive behavior, which was further summarized to determine the proportion of time spent active per day. The most valuable features in the selected ML model were movement variation (MV), maximum X-axis value (MaxX), standard deviation of the X-axis (SDX), maximum Y-axis value (MaxY) and standard deviation of the Z-axis (SDZ).Linear mixed-effects models identified a significant difference in all sheep activity pre- and post-anthelmintic drench on Day 56 (P < 0.001). Conversely, there was no significant difference between activity levels of infected animals compared to controls (P = 0.14). To further explore how the activity of sheep changed with clinical presentations of H. contortus infections, weekly faecal egg count (FEC) and blood packed cell volume (PCV) were compared to sheep activity using a Spearman's rank correlation test. There was a weak but significant negative correlation between FEC and sheep activity (P < 0.001) and a weak but significant positive correlation between PCV and sheep activity (P < 0.001).In conclusion, this study has shown that accelerometer-based activity monitoring may be able to identify changes in sheep activity associated with clinical presentations of H. contortus infections and between periods prior to and following anthelmintic treatment. However, the ability to detect activity differences between infected and control animals was less clear. Further research is needed to determine the impact of individual behavior variability and flock dynamics when using on-animal sensors for the detection of behavioral changes associated with disease.

Accelerometer-Based Physical Activity and Health-Related Quality of Life in Children with ADHD.

Accelerometer-Based Physical Activity and Health-Related Quality of Life in Children with ADHD.

Accelerometer-Based Sedentary Time, Physical Activity, and Serum Metabolome in Young Men.

Physical activity (PA) has been shown to associate with many health benefits but studies with metabolome-wide associations with PA are still lacking. Metabolome studies may deepen the mechanistic understanding of PA on the metabolic pathways related to health outcomes. The aim of the present study was to study the association of accelerometer based sedentary time (SB) and PA with metabolome measures. SB and PA were measured by a hip-worn accelerometer in 314 young adult men (age: mean 28, standard deviation 7 years). Metabolome was analyzed from fasting serum samples consisting of 66 metabolome measures (nuclear magnetic resonance-based metabolomics). The associations were analyzed using a single and compositional approach with regression analysis. The compositional analysis revealed that 4 metabolome variables were significantly (γ: 0.32–0.44, p ≤ 0.002), and 13 variables with a trend towards significance (p < 0.05), associated with SB with varying metabolic pathways. Trends towards significant associations (p < 0.05) were observed with 5 variables with moderate-to-vigorous and 1 variable with light intensity PA with varying metabolic pathways. The present study revealed possible mechanistic pathways relevant for the interaction between especially SB but also PA of moderate-to-vigorous intensity with ketone bodies and amino acid concentration related to exercised-induced energy production and lipid metabolism.

GPS-based activity space exposure to greenness and walkability is associated with increased accelerometer-based physical activity.

Built and natural environments may provide opportunities for physical activity. However, studies are limited by primarily using residential addresses to define exposure and self-report to measure physical activity. We quantified associations between global positioning systems (GPS)-based activity space measures of environmental exposure and accelerometer-based physical activity. Using a nationwide sample of working female adults (N=354), we obtained seven days of GPS and accelerometry data. We created Daily Path Area activity spaces using GPS data and linked these activity spaces to spatial datasets on walkability (EPA Smart Location Database at the Census block group level) and greenness (satellite vegetation at 250m resolution). We utilized generalized additive models to examine nonlinear associations between activity space exposures and accelerometer-derived physical activity outcomes adjusted for demographic characteristics, socioeconomic factors, and self-rated health. Higher activity space walkability was associated with higher levels of moderate-vigorous physical activity, and higher activity space greenness was associated with greater numbers of steps per week. No strong relationships were observed for sedentary behavior or light physical activity. Highest levels of moderate-vigorous physical activity were observed for participants with both high walkability and high greenness in their activity spaces. This study contributes evidence that higher levels of physical activity occur in environments with more dense, diverse, and well-connected built environments, and with higher amounts of vegetation. These data suggest that urban planners, landscape architects, and policy makers should implement and evaluate environmental interventions to encourage higher levels of physical activity.

Secure and Sustainable Framework for Cattle Recognition Using Wireless Multimedia Networks and Machine Learning Techniques

Towards the successful operation of any farm, effective livestock management is necessary. The efficiency, affordability, and scalability of management solutions play a crucial role in modern farming. In this paper, a novel low-cost framework is proposed to recognize for health monitoring of individual cattle based on their sensed behavioral activity data and muzzle (nose) pattern image database using incremental decision tree classification techniques and accelerometer-based activity monitoring method. The proposed system performs image prepossessing on the captured muzzle point images of cattle to mitigate the noise, enhance the contrast, and increase quality. We extract the minutiae features to improve the system’s accuracy for recognizing the cattle for accurate and early classification of behavioral activity for health monitoring. The proposed system uses a support vector machine and incremental decision tree classifiers to classify the extracted feature of cattle’s muzzle images and health database. The server has encrypted databases that consist of captured muzzle images, owner database, health sensor database provided by the owners and systems. We use a similarity score measurement using incremental decision tree classification for matching and classify the muzzle point featutes with the database for cattle identification and health monitoring. We also developed a prototype for evaluating the accuracy of the proposed system with 97.99% accuarcy for unique identification of individual cattle.

Physical Activity during Pregnancy: Comparisons between Objective Measures and Self-Reports in Relation to Blood Glucose Levels.

Objective: to quantify pregnant women’s physical activity during pregnancy using wearable accelerometers and a self-reported scale and to examine the variation in these two physical activity measures in relation to fasting plasma glucose (FPG) levels and presence of gestational diabetes mellitus (GDM). Methods: this prospective observational study included 197 pregnant women from one of the largest regional hospitals in South China. Women with singleton pregnancy, absence of pre-existing comorbidities and pre-specified contraindications, wore an accelerometer on their waist for 7 consecutive days to objectively record their physical activity, followed by completing a past-7-day physical activity questionnaire, three times, respectively, in three trimesters. GDM was determined by 2-h 75 g oral glucose tolerance test (OGTT) in 24–28th week’s gestation and FPG was obtained in both 1st and 2nd trimesters following standard practice. Results: pregnant women engaged highest levels of various physical activity types in 2nd trimester, except accelerometer-based moderate-to-vigorous physical activity which gradually decreased in pregnancy. Pregnant women were more likely to walk in 3rd trimester. The relationship between objective total physical activity and self-reported total physical activity was non-linear. Increased trend of FPG from 1st trimester to 2nd trimester disappeared when adjusting for accelerometer-based light physical activity and attenuated when including walking. Self-reported moderate physical activity was surprisingly positively associated with GDM. Conclusions: different patterns in physical activity between objective measure and self-report in relation to gestational glucose levels were observed. Short-term increase in moderate physical activity prior to OGTT may not be necessary for reducing presence of GDM. Future glucose management for pregnant women may be targeted at lower intensity physical activity.

Validity of trunk acceleration measurement with a chest-worn monitor for assessment of physical activity intensity

BackgroundRecent advancements in wearable technology have enabled easy measurement of daily activities, potentially applicable in rehabilitation practice for various purposes such as maintaining and increasing patients’ activity levels. In this study, we aimed to examine the validity of trunk acceleration measurement using a chest monitor embedded in a smart clothing system (‘hitoe’ system), an emerging wearable system, in assessing the physical activity in an experimental setting with healthy subjects (Study 1) and in a clinical setting with post-stroke patients (Study 2).MethodsStudy 1 involved the participation of 14 healthy individuals. The trunk acceleration, heart rate (HR), and oxygen consumption were simultaneously measured during treadmill testing with a Bruce protocol. Trunk acceleration and HR were measured using the "hitoe" system, a smart clothing system with embedded chest sensors. Expiratory gas analysis was performed to measure oxygen consumption. Three parameters, moving average (MA), moving standard deviation (MSD), and moving root mean square (RMS), were calculated from the norm of the trunk acceleration. The relationships between these accelerometer-based parameters and oxygen consumption-based physical activity intensity measured with the percent VO2 reserve (%VO2R) were examined. In Study 2, 48 h of simultaneous measurement of trunk acceleration and heart rate-based physical activity intensity in terms of percent heart rate reserve (%HRR) was conducted with the "hitoe" system in 136 post-stroke patients.ResultsThe values of MA, MSD, RMS, and %VO2R were significantly different between levels 1, 2, 3, and 4 in the Bruce protocol (P < 0.01). The average coefficients of determination for individual regression for %VO2R versus MA, %VO2R versus MSD, and %VO2R versus RMS were 0.89 ± 0.05, 0.96 ± 0.03, and 0.91 ± 0.05, respectively. Among the parameters examined, MSD showed the best correlation with %VO2R, indicating high validity of the parameter for assessing physical activity intensity. The 48-h measurement of MSD and %HRR in post-stroke patients showed significant within-individual correlation (P < 0.05) in 131 out of 136 patients (correlation coefficient: 0.60 ± 0.16).ConclusionsThe results support the validity of the MSD calculated from the trunk acceleration measured with a smart clothing system in assessing the physical activity intensity.Trial registration: UMIN000034967. Registered 21 November 2018 (retrospectively registered).