Accuracy of 12 Wearable Devices for Estimating Physical Activity Energy Expenditure Using a Metabolic Chamber and the Doubly Labeled Water Method: Validation Study

Measurement of Physical Activity Divided Into Inside and Outside the Home in People With Parkinson's Disease: A Feasibility Study

RATIONALE

In people with Parkinson's disease (PD), quantitative assessment of activities inside and outside the home is crucial for planning effective rehabilitation tailored to a person's living conditions and characteristics.

AIMS AND OBJECTIVES

We examined the feasibility of combining a physical activity metre and a daily activity diary for people with PD.

METHODS

Physical activity was evaluated using a triaxial accelerometer and recorded in a daily activity diary by the participant. The feasibility outcome was the data adoption rate, which was the physical activity rate calculated from the activity metre wearing time and the missing times from the daily activity diary.

RESULTS AND CONCLUSION

Of the 10 participants, nine had a complete data set (adoption rate 90%). The mean physical activity metre wearing time was 14.12 ± 2.26 h/day, with a mean missing time of 25.7 ± 18.1 min/day in the daily activity diary. Combining a physical activity metre and a daily activity diary is feasible in people with PD, particularly when planning rehabilitation protocols to enhance daily physical activity.

Wristwatch pulse wave monitoring: assessing daily activity post-catheter ablation for atrial fibrillation

Aims

Atrial fibrillation (AF) leads to impaired exercise capacity, and catheter ablation (CA) for AF improves exercise capacity. However, the precise changes in daily activities after CA for AF remain unclear. The authors aimed to evaluate the changes in daily activities following CA for AF using a wristwatch-type pulse wave monitor (PWM), which tracks steps and exercise time, estimates burnt daily calories, and records sleep duration, in addition to establishing the rhythm diagnosis of AF or non-AF.

Methods and results

One hundred and twenty-three patients with AF (97 paroxysmal, 26 persistent) wore a wristwatch-type PWM for 1 week duration at three time points: before, 1 month after, and 3 months after ablation. Daily activity data were compared. Steps did not change in both groups, and the number of burnt daily calories and total exercise time increased after CA in patients with paroxysmal AF (burnt daily calories: before, 1591 kcal/day; 1 month, 1688 kcal/day; and 3 months, 1624 kcal/day; P < 0.001 and exercise time: before, 45.8 min; 1 month, 51.2 min; and 3 months, 56.3 min; P = 0.023). Sleep hours significantly increased (paroxysmal AF: before, 6.8 h; 1 month, 7.1 h; and 3 months, 7.1 h; P = 0.039 and persistent AF: before, 6.0 h; 1 month, 7.0 h; and 3 months, 7.0 h; P = 0.007).

Conclusion

Using a wristwatch-type PWM, we demonstrated changes in daily activities after CA in patients with AF.

Trial registration number

jRCT1030210022.

Validity and Reliability of Wearable Technology Devices during Simulated Pickleball Game Play

Pickleball is a popular sport. Also popular is wearable technology usage. Because the validity and reliability of wearable technology during pickleball is unknown, the purpose of this research was to evaluate the ability of common devices to return heart rate and estimated energy expenditure during pickleball activity. Twenty adult participants were outfitted with a portable metabolic unit and heart rate monitor (criterion measures). Experimental devices were a Garmin Instinct, Polar Vantage M2, Polar OH1, and Polar Verity Sense. Participants played simulated pickleball for 10 min. Validity measures included mean absolute percent error (MAPE) and Lin's Concordance Correlation Coefficient (CCC), whereas reliability measures included coefficient of variation (CV) and intraclass correlation coefficient (ICC). The heart rate returned lower than 10% MAPE across all devices (Instinct = 5.73-6.32%, Verity Sense = 2.92-2.97%, OH1 = 3.39-3.45%) and greater than 0.85 CCC (Instinct = 0.85-0.88, Verity Sense = 0.96-0.96, OH1 = 0.93-0.94). The CV was below 10% (Instinct = 9.30%, Verity Sense = 2.68%, OH1 = 5.01%), and ICC was above 0.7 (Instinct = 0.77, Verity Sense = 0.98, OH1 = 0.91). The energy expenditure MAPE was greater than 10% (Instinct = 27.67-28.08%, Vantage M2 = 18.87-23.38%) with CCC lower than 0.7 (Instinct = 0.47-0.49, Vantage M2 = 0.62-0.63). Reliability thresholds were met in the Vantage M2 (CV = 6%, ICC = 0.98) but not in the Instinct (CV = 15%, ICC = 0.86). The Instinct was neither valid nor reliable for estimated energy expenditure, while the Polar Vantage M2 was reliable but not valid. All devices returned valid and reliable heart rates during pickleball.

Association between muscle quality and nutritional status among community-dwelling older adults: A cross-sectional study

Background: Decline in muscle quality is associated with poorer health in community-dwelling older adults. Although there is evidence that malnutrition is associated with the decline of muscle quality in older adults, few analyses have considered important factors related to muscle quality. Aim: The purpose of this study was to determine the relationship between muscle quality and nutritional status in community-dwelling older adults, taking into account muscle mass, muscle strength, and amount of physical activity. Methods: This was a cross-sectional study. Data were obtained from a health checkup program in Japan. Participants were older adults aged ≥65 years living in the community who participated in the health checkup program. The data collected were echo intensity, scores on the Global Leadership Initiative on Malnutrition criteria, skeletal muscle mass, grip strength, physical activity level, and demographic data. Multiple regression analysis was used to examine the association between muscle quality and nutritional status. Results: Data were analyzed for 50 participants (mean age 77.62 years, standard deviation 6.16 years, 78.0% women). Multiple regression analysis showed that nutritional status affected muscle quality even when various factors were taken into account (B = 6.95, β = 0.31, p = 0.04, 95% confidence interval: 0.01-0.62). Conclusion: The observed association suggests that providing nutritional support for older adults living in the community may be a useful strategy to maintain muscle quality.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Associations Between Cognitive Function and Muscle Quality Among Community-Dwelling Older Adults: A Cross-Sectional Study

OBJECTIVE

To investigate whether muscle quality is related to cognitive function in older adults living in the community.

METHODS

The participants were 40 community-dwelling older adults without a diagnosis of dementia (mean age, 78.85 ± 6.40 years; 31 women). The dependent variable was the score on the mild cognitive impairment (MCI) index of the Japanese version of the Neurobehavioral Cognitive Status Examination Five (range: 0-6; higher scores indicate MCI or possible dementia).

RESULTS

Multiple regression with Bayesian statistics was performed for analysis of muscle quality, as indicated by echo intensity (EI), with skeletal muscle mass index, gait speed, physical activity level, age, and sex as covariates. EI was significantly associated with the MCI index (expected a posterior = 0.04 [95% Bayesian confidence interval: 0.01, 0.07], t = 2.47, β = 0.41, p = 0.019).

CONCLUSIONS

The results suggest that EI may be related to the cognitive function of older adults living in the community. Future studies should examine whether focusing on EI can help prevent cognitive decline among older adults..

Accuracy of the SenseWear Armband during Short Bouts of Exercise

A goal of mobile monitoring is to approximate metabolic energy expenditure (EE) during activities of daily living and exercise. Many physical activity monitors are inaccurate with respect to estimated EE and differentiating between activities that occur over short intervals. The objective of our study was to assess the validity of the SenseWear Armband (SWA) compared to indirect calorimetry (IC) during short intervals of walking and running. Twenty young, fit participants walked (preferred speed) and ran (75%, 85%, and 95% of predicted VO2max run speeds) on a treadmill. EE estimates from IC, SWA, and prediction equations that used the SWA, speed, and heart rate were examined during each 4 min interval and across the whole protocol (Total). The level of significance was p < 0.05. The SWA overestimated EE relative to IC by 1.62 kcal·min-1 while walking and 1.05 kcal·min-1 while running at 75%. However, it underestimated EE at the 85% (0.05 kcal·min-1) and 95% (0.92 kcal·min-1) speeds, but not significantly, and overestimated total EE by 28.29 kcal. Except for walking, our results suggest that the SWA displayed a good level of agreement (ICC = 0.76 to 0.84) with IC measures. Activity-specific algorithms using SWA, speed, and heart rate improved EE estimates, based on the standard error of the estimates, but perhaps not enough to justify extra sensors. The SWA may enable EE estimation of locomotion outside the laboratory, including those with short bouts of high intensity activity, but continued development of the SWA, or devices like it, is needed to enable accurate monitoring.

Physical Activity Components that Determine Daily Life Satisfaction Among Older Adults: An Intensive Longitudinal Diary Study

BACKGROUND

Although previous studies have shown that engaging in physical activity can elevate daily life satisfaction, few studies have identified the specific aspects that can result in this. This study examined whether enjoying moderate-to-vigorous intensity exercises with others for a longer time, but not any aspects of non-exercise physical activity, was associated with higher daily life satisfaction among older adults.

METHOD

We conducted an intensive longitudinal diary survey of 182 individuals for 1 week and obtained valid data for 853 person-days. The time spent engaging in light and moderate-to-vigorous physical activity at 8:00-11:59, 12:00-15:59, and 16:00-19:59 h was measured using an accelerometer. Duration, intensity, timing, social context, and enjoyment of the exercises were assessed based on diary entries. Stratified by non-exercise and exercise days, we conducted multilevel models.

RESULTS

On non-exercise days, longer duration of light physical activity from 12:00 to 15:59 at the within-person level was associated with higher daily life satisfaction. On exercise days, longer duration of moderate-to-vigorous physical activity from 12:00 to 15:59 at the within-person level, longer exercise duration at the within-person level, exercising with moderate-to-vigorous intensity, and enjoyment of exercise at both the within- and between-person levels were associated with higher daily life satisfaction.

CONCLUSION

These findings indicate that enjoying moderate-to-vigorous intensity exercise for a longer duration than usual and engaging in non-exercise physical activity in the afternoon are important for elevating older adults' daily life satisfaction.

Individually optimized estimation of energy expenditure in rescue workers using a tri-axial accelerometer and heart rate monitor

Objectives: This study aimed to provide an improved energy expenditure estimation for heavy-load physical labor using accelerometer data and heart rate (HR) measured by wearables and to support food preparation and supply management for disaster relief and rescue operations as an expedition team. Methods: To achieve an individually optimized estimation for energy expenditure, a model equation parameter was determined based on the measurements of physical activity and HR during simulated rescue operations. The metabolic equivalent of task (MET), which was measured by using a tri-axial accelerometer and individual HR, was used, where two (minimum and maximum) or three (minimum, intermediate, and maximum) representative reference points were selected for each individual model fitting. In demonstrating the applicability of our approach in a realistic situation, accelerometer-based METs and HR of 30 males were measured using the tri-axial accelerometer and wearable HR during simulated rescue operations over 2 days. Results: Data sets of 27 rescue operations (age:34.2 ± 7.5 years; body mass index (BMI):22.9 ± 1.5 kg/m2) were used for the energy expenditure estimation after excluding three rescue workers due to their activity type and insufficient HR measurement. Using the combined approach with a tri-axial accelerometer and HR, the total energy expenditure increased by 143% for two points and 133% for three points, compared with the estimated total energy expenditure using only the accelerometer-based method. Conclusion: The use of wearables provided a reasonable estimation of energy expenditure for physical workers with heavy equipment. The application of our approach to disaster relief and rescue operations can provide important insights into nutrition and healthcare management.

Relationship between Phase Angle and Physical Activity Intensity among Community-Dwelling Older Adults in Japan: A Cross-Sectional Study

This cross-sectional study aimed to determine the association between phase angle (PhA) and physical activity intensity in community-dwelling older Japanese adults. The intensity and time of physical activity for predicting high PhA were also examined. This study involved 67 community-dwelling older adults (mean age: 78.3 ± 5.5; female: 83.6%). We measured the physical activity and body composition of the participants. Physical activity was measured using a triaxial accelerometer, and light-intensity physical activity (LPA) and moderate-to-vigorous intensity physical activity (MVPA) hours per day were calculated from the results. Body composition was measured using Inbody S10, and the PhA was calculated from the measurements of the right side of the body. Bayesian statistical modeling revealed an association between PhA and MVPA (β = 0.256; p = 0.022; 95% Bayesian confidence interval [CI] = 0.001, 0.012), but not LPA (β = -0.113; p = 0.341; 95% Bayesian CI = -0.002, 0.001), even after adjustment for confounders. The cutoff value of MVPA predicting high PhA, calculated by the receiver operator characteristic curve, was 19.7 min/d (sensitivity = 0.906; specificity = 0.429). These results can be used to develop strategies to increase PhA in older adults and suggest that MVPA is important in this population.

Questionnaire-based scoring system for screening moderate-to-vigorous physical activity in middle-aged Japanese workers

OBJECTIVES

Currently available questionnaires have limited ability to measure physical activity (PA) using accelerometers as a gold standard. This study aimed to develop a PA questionnaire for middle-aged Japanese workers and propose a PA scoring system for predicting low moderate-to-vigorous PA (MVPA).

METHODS

A total of 428 participants (median age 49 years; 75.8% men) participated in a 7-day PA measurement using an accelerometer and a questionnaire. The association between questionnaire responses and low MVPA (<150 min/wk) was assessed by logistic regression analysis. A score was assigned to each response based on the correlation coefficients of the multivariate model. The ability of the sum score to predict low MVPA was assessed using the area under the receiver operating characteristic curve (AUC).

RESULTS

Five questionnaire items were used for measuring PA scores (range: 0-50; higher scores indicated a higher probability of low MVPA). The AUC was 0.741 (95% CI, 0.689-0.792), and the sensitivity and specificity at the optimal cut-off value were 66.7% and 68.2%, respectively. This predictive ability was slightly increased by body mass index (AUC 0.745 [95% CI, 0.693-0.796]; sensitivity 69.9%; specificity 66.9%). These predictive values were greater than those of conventional questionnaires used in health checkups in Japan (P < .05).

CONCLUSIONS

This questionnaire-based PA scoring system showed moderate accuracy in predicting low MVPA. It is useful for screening physically inactive workers and promoting PA.

Evaluation of protein requirements using the indicator amino acid oxidation method: a scoping review

BACKGROUND

The indicator amino acid oxidation (IAAO) method has been accepted as an approach to evaluate habitual protein requirements under free-living conditions.

OBJECTIVES

This scoping review reports on literature that evaluated protein requirements in humans using the IAAO methods.

METHODS

Three databases (PubMed/Medline, Web of Science, and ProQuest) were systematically searched to identify studies that evaluated protein requirements using the IAAO method published in English until 5 June, 2023. We evaluated the study quality using previously developed criteria. We extracted the characteristics of the study design and the results of protein requirements. Two reviewers conducted both reviews and quality assessments independently; any differences among them were resolved by consensus or agreement of all team members.

RESULTS

We extracted 16 articles targeting children, young adults (including pregnant women, resistance training athletes, endurance-training athletes, and team sports), and older adults. In quality assessment, 14 studies were evaluated "strong," but the remaining 2 were "moderate." These studies were conducted in only 3 countries and did not include all sexes or life stages. The range of the estimated average protein requirements of each life stage was 1.30 g/kg body weight/d for children, 0.87 to 2.10 (0.87-0.93 for general young adults, 1.22-1.52 for pregnant women, 1.49-2.00 for resistance-trained athletes, 1.65-2.10 for endurance athletes, and 1.20-1.41 for team sports athletes) g/kg body weight/d for young adults, and 0.85 to 0.96 g/kg body weight/d for older adults.

CONCLUSIONS

Protein requirements in 14 studies were higher than the current reference for each sex, life stage, and physical activity that are related to protein requirements. In the future, protein requirements of various populations including sex and life stage could be assessed using the IAAO methods worldwide.

Association between physical activity and the prevalence of tumorigenic bacteria in the gut microbiota of Japanese adults: a cross-sectional study

Escherichia coli harboring polyketide synthase (pks+ E. coli) has been suggested to contribute to colorectal cancer development. Physical activity is strongly associated with lower colorectal cancer risks, but its effects on pks+ E. coli remain unclear. The aim of this study was to investigate the association between pks+ E. coli prevalence and physical activity. A cross-sectional study was conducted on 222 Japanese adults (27-79-years-old, 73.9% female). Triaxial accelerometers were used to measure light-intensity physical activity, moderate-to-vigorous intensity physical activity, the physical activity level, step-count, and time spent inactive. Fecal samples collected from participants were used to determine the prevalence of pks+ E. coli. Multivariate logistic regression analysis and restricted cubic spline curves were used to examine the association between pks+ E. coli prevalence and physical activity. The prevalence of pks+ E. coli was 26.6% (59/222 participants). The adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for the highest tertile with reference to the lowest tertile of physical activity variables were as follows: light-intensity physical activity (OR 0.63; 95% CI 0.26-1.5), moderate-to-vigorous intensity physical activity (OR 0.85; 95% CI 0.39-1.87), physical activity level (OR 0.69; 95% CI 0.32-1.51), step-count (OR 0.92; 95% CI 0.42-2.00) and time spent inactive (OR 1.30; 95% CI 0.58-2.93). No significant dose-response relationship was found between all physical activity variables and pks+ E. coli prevalence. Our findings did not suggest that physical activity has beneficial effects on the prevalence of pks+ E. coli. Longitudinal studies targeting a large population are needed to clarify this association.

Mobile Health and Preventive Medicine

Wearable devices providing health-related data (mobile health [mHealth]) have grown in numbers and types of data available over the past 2 decades. Applications in prevention with some of the longest track records are activity trackers to promote fitness (primary prevention), mobile electrocardiogram devices to detect arrhythmias (secondary prevention), and continuous glucose monitoring to improve glycemic control in type 2 diabetes (tertiary prevention). Continued integration of multiple diverse data streams and improved interfaces with individuals (such as artificial intelligence-driven health coaches), and health care teams (as in the hospital-at-home concept), promise to optimize use of mHealth to improve clinical and public health outcomes.

Predicting energy intake with an accelerometer-based intake-balance method

Nutritional interventions often rely on subjective assessments of energy intake (EI), but these are susceptible to measurement error. To introduce an accelerometer-based intake-balance method for assessing EI using data from a time-restricted eating (TRE) trial. Nineteen participants with overweight/obesity (25-63 years old; 16 females) completed a 12-week intervention (NCT03129581) in a control group (unrestricted feeding; n 8) or TRE group (n 11). At the start and end of the intervention, body composition was assessed by dual-energy X-ray absorptiometry (DXA) and daily energy expenditure (EE) was assessed for 2 weeks via wrist-worn accelerometer. EI was back-calculated as the sum of net energy storage (from DXA) and EE (from accelerometer). Accelerometer-derived EI estimates were compared against estimates from the body weight planner of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Mean EI for the control group declined by 138 and 435 kJ/day for the accelerometer and NIDDK methods, respectively (both P ≥ 0·38), v. 1255 and 1469 kJ/day, respectively, for the TRE group (both P < 0·01). At follow-up, the accelerometer and NIDDK methods showed excellent group-level agreement (mean bias of -297 kJ/day across arms; standard error of estimate 1054 kJ/day) but high variability at the individual level (limits of agreement from -2414 to +1824 kJ/day). The accelerometer-based intake-balance method showed plausible sensitivity to change, and EI estimates were biologically and behaviourally plausible. The method may be a viable alternative to self-report EI measures. Future studies should assess criterion validity using doubly labelled water.

Prediction of the Physical Activity Level of Community-Dwelling Older Japanese Adults with a Triaxial Accelerometer Containing a Classification Algorithm for Ambulatory and Non-Ambulatory Activities

Accurate methods for the prediction of the total energy expenditure and physical activity level (PAL) in community-dwelling older adults have not been established. Therefore, we examined the validity of estimating the PAL using an activity monitor (Active style Pro HJA-350IT, [ASP]) and proposed correction formulae for such populations in Japan. Data for 69 Japanese community-dwelling adults aged 65 to 85 years were used. The total energy expenditure in free-living conditions was measured with the doubly labeled water method and the measured basal metabolic rate. The PAL was also estimated from metabolic equivalent (MET) values obtained with the activity monitor. Adjusted MET values were also calculated with the regression equation of Nagayoshi et al. (2019). The observed PAL was underestimated, but significantly correlated, with the PAL from the ASP. When adjusted using the Nagayoshi et al. regression equation, the PAL was overestimated. Therefore, we developed regression equations to estimate the actual PAL (Y) from the PAL obtained with the ASP for young adults (X) as follows: women: Y = 0.949 × X + 0.205, mean ± standard deviation of the prediction error = 0.00 ± 0.20; men: Y = 0.899 × X + 0.371, mean ± standard deviation of the prediction error = 0.00 ± 0.17.

Prophylactic relationship between mental health disorder symptoms and physical activity of Royal Canadian Mounted Police Cadets during the cadet training program

Objective

Royal Canadian Mounted Police report experiencing extremely frequent potentially psychologically traumatic events (PPTE). In a recent study, approximately half of participating RCMP screened positive for one or more mental disorders, which is approximately five times the diagnostic proportion for the general Canadian population. Increased reporting of mental health symptoms been linked to PPTE exposures. Programs promoting physical activity may be useful interventions to supplement or pair with mental health interventions, providing anxiolytic, antidepressant, and stress-buffering effects. The current study was designed to assess the relationship between physical activity behaviors and reported mental health disorder symptoms of cadets during the Royal Mounted Canadian Police (RCMP) Cadet Training Program (CTP). The current study also examined the relationship between exercise and mental health disorder symptoms of cadets during the CTP.

Methods

The study included data from 394 cadets (76.1% male). An analysis of variance (ANOVA) and a series of t-tests were used to assess several differences across sociodemographic groups. Bivariate Spearman's Rank correlations were performed between the average number of active calories burned per day, as recorded by Apple Watches, and changes in self-reported mental health disorder symptoms (i.e., Generalized Anxiety Disorder [GAD], Major Depressive Disorder [MDD], Posttraumatic Stress Disorder [PTSD], Social Anxiety Disorder [SAD]. Alcohol Use Disorders [AUD], Panic Disorder [PD]) from pre-training (starting the CTP) to pre-deployment (completing the CTP) 26 weeks later.

Results

There were statistically significant correlations between physical activity and self-reported mental health disorder symptom scores during CTP. Cadets who performed more physical activity from pre-training to pre-deployment had statistically significantly greater decreases in symptoms of GAD (ρ = -0.472, p < 0.001), MDD (ρ = -0.307, p < 0.001), PTSD (ρ = -0.343, p < 0.001), and AUD (ρ = -0.085, p < 0.05). There was no statistically significant relationship between physical activity and changes in PD symptoms (ρ = -0.037, p > 0.05). There were also no statistically significant relationships between pre-CTP mental health disorder symptom scores and the volume of physical activity performed during CTP.

Conclusion

There was evidence of a significant relationship between reductions in mental health disorder symptom scores and physical activity during the 26-week CTP. The results highlight the role that exercise can play as an important tool for reducing mental health disorder symptoms, considering there was no relationship between pre-CTP baseline mental health scores and physical activity performed during CTP. Further research is needed to understand differences in physical activity behaviours among cadets and serving RCMP.

Energy Expenditure of Disaster Relief Operations Estimated Using a Tri-Axial Accelerometer and a Wearable Heart Rate Monitor

The management of nutrition, food, and health for disaster relief personnel is one of the crucial aspects for carrying out effective rescue activities during large-scale natural disasters, such as a big earthquake, flooding, and landslide following heavy rainfall or man-made disasters, such as widespread fire in industrial areas. Rescue workers, such as fire fighters and rescue teams who work on the disaster relief operations, have to work long, hard, and irregular hours that require energy (both intake and expenditure), with especially altered eating patterns. Reliable estimates of the energy expenditure (TEE) for such disaster relief operations have not been fully established. Here, we propose to clarify the energy expenditure for each type of large-scale disaster activity conducted by fire fighters. Thirty fire fighters (survey participants in this research) who participated in the simulation training of large-scale disaster activities wore tri-axial accelerometers and heart rate monitors during training; and, post-training, 28 fire fighters submitted complete activity record tables. An estimation formula combining tri-axial accelerometer and heart rate monitor data was used. Additionally, energy expenditure per hour (excluding resting energy expenditure: REE) (per average body weight of participants) was calculated for 10 types of large-scale disaster response activities. We propose utilization of these data as a reference value for examining the TEE of firefighting and rescue operations in future large-scale disasters.

Regional Difference in the Impact of COVID-19 Pandemic on Domain-Specific Physical Activity, Sedentary Behavior, Sleeping Time, and Step Count: Web-Based Cross-sectional Nationwide Survey and Accelerometer-Based Observational Study

BACKGROUND

Physical activity (PA) and sedentary behavior (SB) have been affected by the COVID-19 pandemic and its restrictive environments, such as social distancing and lockdown measures. However, regional differences in the changes in domain-specific PA and SB in response to the COVID-19 pandemic are not clearly understood.

OBJECTIVE

This study aimed to examine regional differences in domain-specific PA and SB, as well as sleeping time in response to the COVID-19 pandemic in Japan.

METHODS

A web-based cross-sectional nationwide survey and an accelerometer-based longitudinal observation were conducted. In the web-based survey, we recruited 150 Japanese men and 150 Japanese women for each of the following age groups: 20s, 30s, 40s, 50s, 60s, and 70s (n=1800). A total of 1627 adults provided valid responses to web-based surveillance from June to July 2020. Participants were recruited from urban (Greater Tokyo Area, n=1028), urban-rural (regional core cities, n=459), or rural (regional small and medium cities, n=140) areas. They answered sociodemographic and health-related questions and retrospectively registered the PA data of their average day before and during the COVID-19 pandemic in a web-based PA record system. In the accelerometer-based observation, PA and step count data were obtained using a triaxial accelerometer on people living in urban (n=370) and rural (n=308) areas.

RESULTS

Before the COVID-19 pandemic, there were no significant differences between these 3 regions in the time spent sleeping, staying at home, working or studying, and exercising (P>.05). By contrast, people living in urban areas had a longer duration of SB and transportation and a shorter duration of moderate-to-vigorous PA and lying or napping time compared with people living in rural areas (P>.05). During the COVID-19 pandemic, a significant decrease was observed in transportation time in urban (-7.2 min/day, P<.001) and urban-rural (-2.0 min/day, P=.009) areas but not in rural (-0.4 min/day, P=.52) areas. The moderate-to-vigorous PA was decreased in urban (-31.3 min/day, P<.001) and urban-rural (-30.0 min/day, P<.001) areas but not in rural areas (-17.3 min/day, P=.08). A significant increase was observed in time spent sleeping in urban (+22.4 min/day, P<.001) and urban-rural (+24.2 min/day, P<.001) but not in rural areas (+3.9 min/day, P=.74). Lying or napping was increased in urban (+14.9 min/day, P<.001) but not in rural areas (-6.9 min/day, P=.68). PA and step count obtained using an accelerometer significantly decreased in urban (P<.05) but not in rural areas (P>.05).

CONCLUSIONS

The effect of the COVID-19 pandemic on PA and SB was significantly dependent on living area, even in a single country. The effects of PA and SB were greater in the Greater Tokyo Area and regional core cities but were not observed in regional small and medium cities in Japan.

"suMus," a novel digital system for arm movement metrics and muscle energy expenditure

Objective: In the field of non-treatable muscular dystrophies, promising new gene and cell therapies are being developed and are entering clinical trials. Objective assessment of therapeutic effects on motor function is mandatory for economical and ethical reasons. Main shortcomings of existing measurements are discontinuous data collection in artificial settings as well as a major focus on walking, neglecting the importance of hand and arm movements for patients' independence. We aimed to create a digital tool to measure muscle function with an emphasis on upper limb motility. Methods: suMus provides a custom-made App running on smartwatches. Movement data are sent to the backend of a suMus web-based platform, from which they can be extracted as CSV data. Fifty patients with neuromuscular diseases assessed the pool of suMus activities in a first orientation phase. suMus performance was hence validated in four upper extremity exercises based on the feedback of the orientation phase. We monitored the arm metrics in a cohort of healthy volunteers using the suMus application, while completing each exercise at low frequency in a metabolic chamber. Collected movement data encompassed average acceleration, rotation rate as well as activity counts. Spearman rank tests correlated movement data with energy expenditure from the metabolic chamber. Results: Our novel application "suMus," sum of muscle activity, collects muscle movement data plus Patient-Related-Outcome-Measures, sends real-time feedback to patients and caregivers and provides, while ensuring data protection, a long-term follow-up of disease course. The application was well received from the patients during the orientation phase. In our pilot study, energy expenditure did not differ between overnight fasted and non-fasted participants. Acceleration ranged from 1.7 ± 0.7 to 3.2 ± 0.5 m/sec² with rotation rates between 0.9 ± 0.5 and 2.0 ± 3.4 rad/sec. Acceleration and rotation rate as well as derived activity counts correlated with energy expenditure values measured in the metabolic chamber for one exercise (r = 0.58, p < 0.03). Conclusion: In the analysis of slow frequency movements of upper extremities, the integration of the suMus application with smartwatch sensors characterized motion parameters, thus supporting a use in clinical trial outcome measures. Alternative methodologies need to complement indirect calorimetry in validating accelerometer-derived energy expenditure data.

Acceptability and use of waist-worn physical activity monitors in Jamaican adolescents: lessons from the field

OBJECTIVE

We report our experience with a validated waist-worn activity monitor in Jamaican adolescents attending urban high schools. Seventy-nine adolescents from the Global Diet and Activity Research (GDAR) study, recruited from 5 urban Jamaican high schools (two coeducational (n = 37), two all-female schools (n = 32) and one all-boys school (n = 10)) were asked to wear Actigraph wGT3X-BT accelerometers for 7 days (24-h), removing the device only when bathing or swimming. They also logged wake up and bed times in an activity diary. Accelerometry was considered valid if at least 4 days with ≥ 10-h monitor wear were recorded. Validity was compared by adolescent demographic and school characteristics. We also reviewed the students' written feedback on objective physical activity measurement.

RESULTS

Participants, 80.5% female, had a mean age of 15.5 ± 0.8 years with 60% attending schools in low-income communities. Accelerometer return rates were > 98% with 84% providing valid data. Validity did not vary by age group, sex and school setting. While participants were excited about participating in the accelerometer sub-study, commonly reported challenges included monitor discomfort during sleep and maintaining the study diary. Objective measurement of physical activity using 24-h waist-worn accelerometers is feasible and acceptable in Jamaican adolescents.

Machine learning modeling practices to support the principles of AI and ethics in nutrition research

BACKGROUND

Nutrition research is relying more on artificial intelligence and machine learning models to understand, diagnose, predict, and explain data. While artificial intelligence and machine learning models provide powerful modeling tools, failure to use careful and well-thought-out modeling processes can lead to misleading conclusions and concerns surrounding ethics and bias.

METHODS

Based on our experience as reviewers and journal editors in nutrition and obesity, we identified the most frequently omitted best practices from statistical modeling and how these same practices extend to machine learning models. We next addressed areas required for implementation of machine learning that are not included in commercial software packages.

RESULTS

Here, we provide a tutorial on best artificial intelligence and machine learning modeling practices that can reduce potential ethical problems with a checklist and guiding principles to aid nutrition researchers in developing, evaluating, and implementing artificial intelligence and machine learning models in nutrition research.

CONCLUSION

The quality of AI/ML modeling in nutrition research requires iterative and tailored processes to mitigate against potential ethical problems or to predict conclusions that are free of bias.

Phase angle obtained via bioelectrical impedance analysis and objectively measured physical activity or exercise habits

The phase angle (PhA), measured via bioelectrical impedance analysis, is considered an indicator of cellular health, where higher values reflect higher cellularity, cell membrane integrity, and better cell function. This study aimed to examine the relationship between PhA and exercise habits or objectively measured physical activity. We included 115 people aged 32-69 years. The body composition and PhA were measured using a bioelectrical impedance device. Physical activity and sedentary behavior (SB) were assessed using a triaxial accelerometer. Exercise habits were also obtained through structured interviews, and participants were categorized into the no exercise habit (No-Ex), resistance training exercise habit (RT), or aerobic training exercise habit (AT) groups. Objectively measured moderate-to-vigorous physical activity or step count significantly correlated with PhA, independent of age, sex, height, percent body fat, body cell mass, and leg muscle power. In contrast, SB was not significant determinants of PhA. People who exercised regularly (RT or AT) had significantly higher PhA values than did those in the No-Ex group. Furthermore, the PhA was not significantly different between the RT and AT groups. Regularly engaging in exercise with moderate-to-vigorous intensity may improve or maintain muscle cellular health and muscle quality.

Validation of accelerometer placement to capture energy expenditure using doubly labeled water

This study compared accelerometer-measured physical activity by body placement to daily total energy expenditure (TEE) and activity energy expenditure (AEE) measured using doubly labeled water (DLW). Forty-nine adult participants wore accelerometers placed on the nondominant wrist, dominant wrist, and chest while also undergoing DLW assessments. In adjusted models, wrist-measured physical activity (p < 0.05), but not chest-measured physical activity (p > 0.05), was associated with TEE and AEE and explained a significant amount of variance that was not explained by age, sex, height, or body composition (R2 change = 0.04-0.08; all p < 0.05). Accelerometer placement location is an important consideration when using accelerometry to provide information about energy expenditure.

Step-count outcomes of 13 different activity trackers: Results from laboratory and free-living experiments

BACKGROUND

Many activity trackers have been developed, but steps can still be inconsistent from one monitor to another.

RESEARCH QUESTION

What are the differences and associations between the steps of 13 selected consumer-based and research-grade wearable devices during 1 standardized day in a metabolic chamber and 15-day free-living trials?

METHODS

In total, 19 healthy adults between 21 and 50 years-old participated in this study. Participants were equipped with 12 accelerometer-based active trackers and one pedometer (Yamasa) in order to monitor the number of steps per day. The devices were worn on the waist (ActiGraph, Omron, Actimarker, Lifedorder, Withings, and Yamasa) or non-dominant wrist (Fitbit, Garmin, Misfit, EPSON, and Jawbone), or placed in a pocket (Omron CaloriScan, and TANITA). Participants performed structured activities over a 24 h period in a chamber (Standardized day), and steps were monitored in the same participants in free-living trials for 15 successive days using the same monitors (free-living days).

RESULTS

When the 13 monitors were ranked by their steps, waist-worn ActiGraph was located at the center (7th) of the monitors both in the Standardized (12,252 ± 598 steps/day, mean ± SD) and free-living days (9295 ± 4027 steps/day). The correlation between the accelerometer-based devices was very high (r = 0.87-0.99). However, the steps of Yamasa was significantly lower in both trials than ActiGraph. The wrist-worn accelerometers had significantly higher steps than other devices both trials (P < 0.05). The differences between ActiGraph and Actimarker or Lifecorder was less than 100 steps/day in the Standardized day, and the differences between ActiGraph and Active Style Pro was less than 100 steps/day in the free-living days. Regression equation was also performed for inter-device compatibility.

SIGNIFICANCE

Step obtained from the wrist-worn, waist-worn, and pocket-type activity trackers were significantly different from each other but still highly correlated in free-living conditions.

Wearables in Cardiovascular Disease

Wearable devices stand to revolutionize the way healthcare is delivered. From consumer devices that provide general health information and screen for medical conditions to medical-grade devices that allow collection of larger datasets that include multiple modalities, wearables have a myriad of potential uses, especially in cardiovascular disorders. In this review, we summarize the underlying technologies employed in these devices and discuss the regulatory and economic aspects of such devices as well as the future implications of their use.

Enhancing instantaneous oxygen uptake estimation by non-linear model using cardio-pulmonary physiological and motion signals

Oxygen uptake (VO₂) is an important parameter in sports medicine, health assessment and clinical treatment. At present, more and more wearable devices are used in daily life, clinical treatment and health care. The parameters obtained by wearables have great research potential and application prospect. In this paper, an instantaneous VO₂ estimation model based on XGBoost was proposed and verified by using data obtained from a medical-grade wearable device (Beijing SensEcho) at different posture and activity levels. Furthermore, physiological characteristics extracted from single-lead electrocardiogram, thoracic and abdominal respiration signal and tri-axial acceleration signal were studied to optimize the model. There were 29 healthy volunteers recruited for the study to collect data while stationary (lying, sitting, standing), walking, Bruce treadmill test and recuperating with SensEcho and the gas analyzer (Metalyzer 3B). The results show that the VO₂ values estimated by the proposed model are in good agreement with the true values measured by the gas analyzer (R² = 0.94 ± 0.03, n = 72,235), and the mean absolute error (MAE) is 1.83 ± 0.59 ml/kg/min. Compared with the estimation method using a separate heart rate as input, our method reduced MAE by 54.70%. At the same time, other factors affecting the performance of the model were studied, including the influence of different input signals, gender and movement intensity, which provided more enlightenment for the estimation of VO₂. The results show that the proposed model based on cardio-pulmonary physiological signals as inputs can effectively improve the accuracy of instantaneous VO₂ estimation in various scenarios of activities and was robust between different motion modes and state. The VO₂ estimation method proposed in this paper has the potential to be used in daily life covering the scenario of stationary, walking and maximal exercise.

Quality Evaluation of Free-living Validation Studies for the Assessment of 24-Hour Physical Behavior in Adults via Wearables: Systematic Review

Background

Wearable technology is a leading fitness trend in the growing commercial industry and an established method for collecting 24-hour physical behavior data in research studies. High-quality free-living validation studies are required to enable both researchers and consumers to make guided decisions on which study to rely on and which device to use. However, reviews focusing on the quality of free-living validation studies in adults are lacking.

Objective

This study aimed to raise researchers’ and consumers’ attention to the quality of published validation protocols while aiming to identify and compare specific consistencies or inconsistencies between protocols. We aimed to provide a comprehensive and historical overview of which wearable devices have been validated for which purpose and whether they show promise for use in further studies.

Methods

Peer-reviewed validation studies from electronic databases, as well as backward and forward citation searches (1970 to July 2021), with the following, required indicators were included: protocol must include real-life conditions, outcome must belong to one dimension of the 24-hour physical behavior construct (intensity, posture or activity type, and biological state), the protocol must include a criterion measure, and study results must be published in English-language journals. The risk of bias was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool with 9 questions separated into 4 domains (patient selection or study design, index measure, criterion measure, and flow and time).

Results

Of the 13,285 unique search results, 222 (1.67%) articles were included. Most studies (153/237, 64.6%) validated an intensity measure outcome such as energy expenditure. However, only 19.8% (47/237) validated biological state and 15.6% (37/237) validated posture or activity-type outcomes. Across all studies, 163 different wearables were identified. Of these, 58.9% (96/163) were validated only once. ActiGraph GT3X/GT3X+ (36/163, 22.1%), Fitbit Flex (20/163, 12.3%), and ActivPAL (12/163, 7.4%) were used most often in the included studies. The percentage of participants meeting the quality criteria ranged from 38.8% (92/237) to 92.4% (219/237). On the basis of our classification tree to evaluate the overall study quality, 4.6% (11/237) of studies were classified as low risk. Furthermore, 16% (38/237) of studies were classified as having some concerns, and 72.9% (173/237) of studies were classified as high risk.

Conclusions

Overall, free-living validation studies of wearables are characterized by low methodological quality, large variability in design, and focus on intensity. Future research should strongly aim at biological state and posture or activity outcomes and strive for standardized protocols embedded in a validation framework. Standardized protocols for free-living validation embedded in a framework are urgently needed to inform and guide stakeholders (eg, manufacturers, scientists, and consumers) in selecting wearables for self-tracking purposes, applying wearables in health studies, and fostering innovation to achieve improved validity.

Wearable activity trackers-advanced technology or advanced marketing?

Wearable devices represent one of the most popular trends in health and fitness. Rapid advances in wearable technology present a dizzying display of possible functions: from thermometers and barometers, magnetometers and accelerometers, to oximeters and calorimeters. Consumers and practitioners utilize wearable devices to track outcomes, such as energy expenditure, training load, step count, and heart rate. While some rely on these devices in tandem with more established tools, others lean on wearable technology for health-related outcomes, such as heart rhythm analysis, peripheral oxygen saturation, sleep quality, and caloric expenditure. Given the increasing popularity of wearable devices for both recreation and health initiatives, understanding the strengths and limitations of these technologies is increasingly relevant. Need exists for continued evaluation of the efficacy of wearable devices to accurately and reliably measure purported outcomes. The purposes of this review are (1) to assess the current state of wearable devices using recent research on validity and reliability, (2) to describe existing gaps between physiology and technology, and (3) to offer expert interpretation for the lay and professional audience on how best to approach wearable technology and employ it in the pursuit of health and fitness. Current literature demonstrates inconsistent validity and reliability for various metrics, with algorithms not publicly available or lacking high-quality validation studies. Advancements in wearable technology should consider standardizing validation metrics, providing transparency in used algorithms, and improving how technology can be tailored to individuals. Until then, it is prudent to exercise caution when interpreting metrics reported from consumer-wearable devices.

Data Collection Mechanisms in Health and Wellness Apps: Review and Analysis

BACKGROUND

There has been a steady rise in the availability of health wearables and built-in smartphone sensors that can be used to collect health data reliably and conveniently from end users. Given the feature overlaps and user tendency to use several apps, these are important factors impacting user experience. However, there is limited work on analyzing the data collection aspect of mobile health (mHealth) apps.

OBJECTIVE

This study aims to analyze what data mHealth apps across different categories usually collect from end users and how these data are collected. This information is important to guide the development of a common data model from current widely adopted apps. This will also inform what built-in sensors and wearables, a comprehensive mHealth platform should support.

METHODS

In our empirical investigation of mHealth apps, we identified app categories listed in a curated mHealth app library, which was then used to explore the Google Play Store for health and medical apps that were then filtered using our selection criteria. We downloaded these apps from a mirror site hosting Android apps and analyzed them using a script that we developed around the popular AndroGuard tool. We analyzed the use of Bluetooth peripherals and built-in sensors to understand how a given app collects health data.

RESULTS

We retrieved 3251 apps meeting our criteria, and our analysis showed that 10.74% (349/3251) of these apps requested Bluetooth access. We found that 50.9% (259/509) of the Bluetooth service universally unique identifiers to be known in these apps, with the remainder being vendor specific. The most common health-related Bluetooth Low Energy services using known universally unique identifiers were Heart Rate, Glucose, and Body Composition. App permissions showed the most used device module or sensor to be the camera (669/3251, 20.57%), closely followed by location (598/3251, 18.39%), with the highest occurrence in the staying healthy app category.

CONCLUSIONS

We found that not many health apps used built-in sensors or peripherals for collecting health data. The small number of the apps using Bluetooth, with an even smaller number of apps using standard Bluetooth Low Energy services, indicates a wider use of proprietary algorithms and custom services, which restrict the device use. The use of standard profiles could open this ecosystem further and could provide end users more options for apps. The relatively small proportion of apps using built-in sensors along with a high reliance on manual data entry suggests the need for more research into using sensors for data collection in health and fitness apps, which may be more desirable and improve end user experience.

Wearable Sensors and Machine Learning for Hypovolemia Problems in Occupational, Military and Sports Medicine: Physiological Basis, Hardware and Algorithms

Hypovolemia is a physiological state of reduced blood volume that can exist as either (1) absolute hypovolemia because of a lower circulating blood (plasma) volume for a given vascular space (dehydration, hemorrhage) or (2) relative hypovolemia resulting from an expanded vascular space (vasodilation) for a given circulating blood volume (e.g., heat stress, hypoxia, sepsis). This paper examines the physiology of hypovolemia and its association with health and performance problems common to occupational, military and sports medicine. We discuss the maturation of individual-specific compensatory reserve or decompensation measures for future wearable sensor systems to effectively manage these hypovolemia problems. The paper then presents areas of future work to allow such technologies to translate from lab settings to use as decision aids for managing hypovolemia. We envision a future that incorporates elements of the compensatory reserve measure with advances in sensing technology and multiple modalities of cardiovascular sensing, additional contextual measures, and advanced noise reduction algorithms into a fully wearable system, creating a robust and physiologically sound approach to manage physical work, fatigue, safety and health issues associated with hypovolemia for workers, warfighters and athletes in austere conditions.

Association of accelerometer-measured physical activity with kidney function in a Japanese population: the DOSANCO Health Study

BACKGROUND

Sedentary behavior and decreased physical activity are associated with reduced kidney function, yet most evidence is based on self-reported physical activity. This study investigated the association between accelerometer-based physical activity level and kidney function in a general Japanese population.

METHODS

A cross-sectional study was conducted in 440 community-dwelling Japanese participants, aged 35-79 years. Time (min/d) was assessed for the following types of physical activity: sedentary behavior, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). Kidney function was assessed using estimated glomerular filtration rate (eGFR). A linear regression model was employed to calculate the β coefficient of eGFR for a 60-min/d increase in sedentary behavior and LPA and a 10-min/d increase in MVPA. A logistic regression model was used to calculate the odds ratio for low eGFR (< 60 versus ≥60 mL/min/1.73m²) for a 60-min/d or 10-min/d increase in each physical activity type.

RESULTS

MVPA time and eGFR were positively associated in both men and women, after adjusting for age, body mass index, and other clinical characteristics (Men: β, 0.91; P = 0.021; Women: β, 0.70; P = 0.034). In women, sedentary behavior and eGFR were inversely associated after adjusting for the same factors (β, - 1.06; P = 0.048). The odds ratio (95% confidence interval) for low eGFR associated with a 60-min increase in sedentary behavior was 1.65 (1.07-2.55) after adjusting for the same factors in women.

CONCLUSION

Longer sedentary behavior and shorter MVPA time were associated with lower kidney function in the Japanese population.

Recommendations for Determining the Validity of Consumer Wearables and Smartphones for the Estimation of Energy Expenditure: Expert Statement and Checklist of the INTERLIVE Network

BACKGROUND

Consumer wearables and smartphone devices commonly offer an estimate of energy expenditure (EE) to assist in the objective monitoring of physical activity to the general population. Alongside consumers, healthcare professionals and researchers are seeking to utilise these devices for the monitoring of training and improving human health. However, the methods of validation and reporting of EE estimation in these devices lacks rigour, negatively impacting on the ability to make comparisons between devices and provide transparent accuracy.

OBJECTIVES

The Towards Intelligent Health and Well-Being Network of Physical Activity Assessment (INTERLIVE) is a joint European initiative of six universities and one industrial partner. The network was founded in 2019 and strives towards developing best-practice recommendations for evaluating the validity of consumer wearables and smartphones. This expert statement presents a best-practice validation protocol for consumer wearables and smartphones in the estimation of EE.

METHODS

The recommendations were developed through (1) a systematic literature review; (2) an unstructured review of the wider literature discussing the potential factors that may introduce bias during validation studies; and (3) evidence-informed expert opinions from members of the INTERLIVE network.

RESULTS

The systematic literature review process identified 1645 potential articles, of which 62 were deemed eligible for the final dataset. Based on these studies and the wider literature search, a validation framework is proposed encompassing six key domains for validation: the target population, criterion measure, index measure, testing conditions, data processing and the statistical analysis.

CONCLUSIONS

The INTERLIVE network recommends that the proposed protocol, and checklists provided, are used to standardise the testing and reporting of the validation of any consumer wearable or smartphone device to estimate EE. This in turn will maximise the potential utility of these technologies for clinicians, researchers, consumers, and manufacturers/developers, while ensuring transparency, comparability, and replicability in validation.

TRIAL REGISTRATION

PROSPERO ID: CRD42021223508.

Association between Water and Energy Requirements with Physical Activity and Fat-Free Mass in Preschool Children in Japan

Water and energy are essential for the human body. The doubly labeled water (DLW) method measures water turnover (WT) and total energy expenditure (TEE), which serves as a benchmark for the adequate intake (AI) of water and estimated energy requirements (EER). The objective of the current study was to examine the association of WT and TEE with physical activity and body composition in Japanese preschool children. We included 41 preschool children (22 girls, 19 boys) aged 3–6 in this study. WT, TEE, and fat-free mass (FFM) were obtained using DLW. Physical activity was measured using a triaxial accelerometer and categorized as light (LPA; 1.5–2.9 Metabolic equivalents, METs) and of moderate-to-vigorous intensity (MVPA; ≥3.0 METs). Exercise duration (Ex) was defined as ≥4.0 METs of physical activity. WT and TEE moderately positively correlated with Ex, but not with LPA. WT moderately positively correlated with BW and FFM while TEE strongly. We established predictive equations for WT and TEE using body weight (BW), FFM, step count, and Ex to guide the AI of water and EER in Japanese preschool children. We found that FFM and step count are the determinants of TEE, and that BW and Ex are the determinants of WT in preschool children.

A Sensor-Based mHealth Platform for Remote Monitoring and Intervention of Frailty Patients at Home

Frailty syndrome is an independent risk factor for serious health episodes, disability, hospitalization, falls, loss of mobility, and cardiovascular disease. Its high reversibility demands personalized interventions among which exercise programs are highly efficient to contribute to its delay. Information technology-based solutions to support frailty have been recently approached, but most of them are focused on assessment and not on intervention. This paper describes a sensor-based mHealth platform integrated in a service-based architecture inside the FRAIL project towards the remote monitoring and intervention of pre-frail and frail patients at home. The aim of this platform is constituting an efficient and scalable system for reducing both the impact of aging and the advance of frailty syndrome. Among the results of this work are: (1) the development of elderly-focused sensors and platform; (2) a technical validation process of the sensor devices and the mHealth platform with young adults; and (3) an assessment of usability and acceptability of the devices with a set of pre-frail and frail patients. After the promising results obtained, future steps of this work involve performing a clinical validation in order to quantify the impact of the platform on health outcomes of frail patients.

Establishing a Global Standard for Wearable Devices in Sport and Exercise Medicine: Perspectives from Academic and Industry Stakeholders

Millions of consumer sport and fitness wearables (CSFWs) are used worldwide, and millions of datapoints are generated by each device. Moreover, these numbers are rapidly growing, and they contain a heterogeneity of devices, data types, and contexts for data collection. Companies and consumers would benefit from guiding standards on device quality and data formats. To address this growing need, we convened a virtual panel of industry and academic stakeholders, and this manuscript summarizes the outcomes of the discussion. Our objectives were to identify (1) key facilitators of and barriers to participation by CSFW manufacturers in guiding standards and (2) stakeholder priorities. The venues were the Yale Center for Biomedical Data Science Digital Health Monthly Seminar Series (62 participants) and the New England Chapter of the American College of Sports Medicine Annual Meeting (59 participants). In the discussion, stakeholders outlined both facilitators of (e.g., commercial return on investment in device quality, lucrative research partnerships, and transparent and multilevel evaluation of device quality) and barriers (e.g., competitive advantage conflict, lack of flexibility in previously developed devices) to participation in guiding standards. There was general agreement to adopt Keadle et al.'s standard pathway for testing devices (i.e., benchtop, laboratory, field-based, implementation) without consensus on the prioritization of these steps. Overall, there was enthusiasm not to add prescriptive or regulatory steps, but instead create a networking hub that connects companies to consumers and researchers for flexible guidance navigating the heterogeneity, multi-tiered development, dynamicity, and nebulousness of the CSFW field.

The Wearable Physical Fitness Training Device Based on Fuzzy Theory

Mobile Edge Computing and Communication (MECC) can be deployed in close proximity with sensing devices and act as middleware between cloud and local networks. The health and fitness movement has become extremely popular recently. Endurance activities, such as marathons, triathlons, and cycling have also grown in popularity. However, with more people participating in these activities, more accidents and injuries occur—ranging from heat stroke, to heart attacks, shock, or hypoxia. All physical training activities include a risk of injury and accidents. Therefore, any research that offers a means of reducing injury risk will significantly contribute to the personal fitness field. Moreover, with the growing popularity of wearable devices and the rise of the MECC, the development and application of wearable devices that can connect to the MECC has become widespread, producing many new innovations. Although many wearable devices, such as wrist straps and smart watches, are available and able to detect individual physiological data, they cannot monitor the human body in a state of motion. Therefore, this study proposes a set of monitoring parameters for a novel wearable device connected to the MECC based on fitness management to assist fitness trainers in effective prompted strength training, and to offer timely warnings in the event of an injury risk. The data collected by the monitoring device using fuzzy theory include risk factor, body temperature, heart rate, and blood oxygen concentration. The proposed system can display in real-time the current physiological state of a wearer/user. The introduction of this device will hopefully enable trainers to immediately and effectively control and monitor the intensity of a training session, while increasing training safety, and offer crucial and immediate diagnostic information so that the correct treatment can be applied without delay in the event of injury.

Estimating Total Energy Expenditure for Fire-Fighters during Large Scale Disaster Response Training Using a Tri-Axial Accelerometer

The present study was conducted to estimate total energy expenditure (TEE) of fire-fighters using tri axial-accelerometers in conjunction with an activity log survey on a large number of subjects undergoing training mimicking a large-scale disaster. Subjects were 240 fire-fighters participating in a two-day fire-fighting training dedicated to large-scale natural disasters. Data was analyzed by job type of activity group and the job rank, and by comparing the average. The average TEE of the total survey training period is about 3619 (±499) kcal, which is the same value of expenditure for professional athletes during the soccer game season. From the activity group, the rescue and other teams consumed significantly more energy than the fire and Emergency Medical Team (EMS) teams. From the job rank, Fire Captain (conducting position) consumed significantly lower energy than the Fire Lieutenant and Fire Sergeant. Furthermore, it was found that a middle position rank consumed the most energy. This research supports a need to reconsider the current rescue food (and protocols) to supplement the energy expenditure of fire-fighters. In addition, since there was a significant difference between the job type and the job rank, it is necessary to examine the energy amount and shape suitable for each.

Person-Generated Health Data in Women's Health: Protocol for a Scoping Review

BACKGROUND

Due to their ability to collect person-generated health data, digital tools and connected health devices may hold great utility in disease prevention, chronic disease self-monitoring and self-tracking, as well as in tailoring information and educational content to fit individual needs. Facilitators and barriers to the use of digital health technologies vary across demographics, including sex. The "femtech" market is growing rapidly, and women are some of the largest adopters of digital health technologies.

OBJECTIVE

This paper aims to provide the background and methods for conducting a scoping review on the use of person-generated health data from connected devices in women's health. The objectives of the scoping review are to identify the various contexts of digital technologies in women's health and to consolidate women's views on the usability and acceptability of the devices.

METHODS

Searches were conducted in the following databases: Medline, Embase, APA PsycInfo, CINAHL Complete, and Web of Science Core Collection. We included articles from January 2015 to February 2020. Screening of articles was done independently by at least two authors in two stages. Data charting is being conducted in duplicate. Results will be reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) checklist.

RESULTS

Our search identified 9102 articles after deduplication. As of November 2020, the full-text screening stage is almost complete and data charting is in progress. The scoping review is expected to be completed by Fall 2021.

CONCLUSIONS

This scoping review will broadly map the literature regarding the contexts and acceptability of digital health tools for women. The results from this review will be useful in guiding future digital health and women's health research.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/26110.

Impact of Ergonomics on Cardiometabolic Risk in Office Workers: Transition to Activity-Based Working With Height-Adjustable Desk

OBJECTIVE

Ergonomic office redesigning possibly improves physical activity (PA) and sedentary behavior (SB); however, its impact on cardiometabolic risk has not yet been determined. This study aimed to examine the effect of office relocation on cardiometabolic risk factors.

METHODS

Annual health check-up data of 95 office workers from four offices in Tokyo, Japan, who relocated to an office with activity-based working (ABW) and height-adjustable desk (HAD) and a propensity-score matched control-cohort were analyzed. PA and SB on weekdays were measured only in the relocation group before and 10 months after relocation.

RESULTS

Significant interactions were observed for waist circumference, high-density lipoprotein cholesterol, and glycosylated hemoglobin (HbA1c). HbA1c changes showed a significant negative association with moderate-to-vigorous-intensity PA.

CONCLUSION

An ABW office with HAD improves cardiometabolic risk factors in office workers, possibly through changes in PA and SB.

Wearable Devices for Physical Activity and Healthcare Monitoring in Elderly People: A Critical Review

The availability of wearable devices (WDs) to collect biometric information and their use during activities of daily living is significantly increasing in the general population. These small electronic devices, which record fitness and health-related outcomes, have been broadly utilized in industries such as medicine, healthcare, and fitness. Since they are simple to use and progressively cheaper, they have also been used for numerous research purposes. However, despite their increasing popularity, most of these WDs do not accurately measure the proclaimed outcomes. In fact, research is equivocal about whether they are valid and reliable methods to specifically evaluate physical activity and health-related outcomes in older adults, since they are mostly designed and produced considering younger subjects' physical and mental characteristics. Additionally, their constant evolution through continuous upgrades and redesigned versions, suggests the need for constant up-to-date reviews and research. Accordingly, this article aims to scrutinize the state-of-the-art scientific evidence about the usefulness of WDs, specifically on older adults, to monitor physical activity and health-related outcomes. This critical review not only aims to inform older consumers but also aid researchers in study design when selecting physical activity and healthcare monitoring devices for elderly people.

Physical Activity Evaluation Using a Voice Recognition App: Development and Validation Study

BACKGROUND

Historically, the evaluation of physical activity has involved a variety of methods such as the use of questionnaires, accelerometers, behavior records, and global positioning systems, each according to the purpose of the evaluation. The use of web-based physical activity evaluation systems has been proposed as an easy method for collecting physical activity data. Voice recognition technology not only eliminates the need for questionnaires during physical activity evaluation but also enables users to record their behavior without physically touching electronic devices. The use of a web-based voice recognition system might be an effective way to record physical activity and behavior.

OBJECTIVE

The purpose of this study was to develop a physical activity evaluation app to record behavior using voice recognition technology and to examine the app's validity by comparing data obtained using both the app and an accelerometer simultaneously.

METHODS

A total of 20 participants (14 men, 6 women; mean age 19.1 years, SD 0.9) wore a 3-axis accelerometer and inputted behavioral data into their smartphones for a period of 7 days. We developed a behavior-recording system with a voice recognition function using a voice recognition application programming interface. The exercise intensity was determined from the text data obtained by the voice recognition program. The measure of intensity was metabolic equivalents (METs).

RESULTS

From the voice input data of the participants, 601 text-converted data could be confirmed, of which 471 (78.4%) could be automatically converted into behavioral words. In the time-matched analysis, the mean daily METs values measured by the app and the accelerometer were 1.64 (SD 0.20) and 1.63 (SD 0.20), respectively, between which there was no significant difference (P=.57). There was a significant correlation between the average METs obtained from the voice recognition app and the accelerometer in the time-matched analysis (r=0.830, P<.001). In the Bland-Altman plot for METs measured by the voice recognition app as compared with METs measured by accelerometer, the mean difference between the two methods was very small (0.02 METs), with 95% limits of agreement from -0.26 to 0.22 METs between the two methods.

CONCLUSIONS

The average METs value measured by the voice recognition app was consistent with that measured by the 3-axis accelerometer and, thus, the data gathered by the two measurement methods showed a high correlation. The voice recognition method also demonstrated the ability of the system to measure the physical activity of a large number of people at the same time with less burden on the participants. Although there were still issues regarding the improvement of automatic text data classification technology and user input compliance, this research proposes a new method for evaluating physical activity using voice recognition technology.

Effects of a single bout of walking on postprandial triglycerides in men of Chinese, European and Japanese descent: a multisite randomised crossover trial

Introduction

Elevated non-fasting triglyceride (TG) concentrations are a risk factor for cardiovascular diseases but can be reduced after acute exercise. Ethnic-based differences in the magnitude of postprandial lipaemia and the extent that acute exercise reduces postprandial TG are poorly characterised across some ethnicities including those of East Asian origin. This paper describes the protocol of a multisite randomised crossover study comparing the effect of acute walking on postprandial TG in two groups of East Asian men with European men.

Methods and analysis

Twenty Japanese, 20 Singaporean Chinese and 20 white British healthy men (21–39 years) recruited from Japan, Singapore and the UK, respectively, will complete two, 2-day trials. Fasted and postprandial venous blood samples and arterial blood pressure measurements will be taken over 6 hours the day after either: (1) 60-min treadmill walking; or (2) a rest day of normal living. The primary outcome is the difference in postprandial TG among ethnic groups after rest and walking. Secondary outcomes include cholesterol, glucose, insulin, ketone bodies, preheparin lipoprotein lipase, C-reactive protein and systolic/diastolic blood pressure.

Ethics and dissemination

The study was approved by the Ethics Review Committee on Research with Human Subjects of Waseda University and the Nanyang Technological University Institutional Review Board. Relevant approval will be obtained from the UK site. Research findings will be disseminated through peer-reviewed journal publication and health conferences.

Trial registration number

UMIN000038625.

White Matter Integrity Is Associated With the Amount of Physical Activity in Older Adults With Super-aging

Previous studies have introduced the concept of “SuperAgers,” defined as older adults with youthful memory performance associated with the increased cortical thickness of the anterior cingulate cortex. Given that age-related structural brain changes are observed earlier in the white matter (WM) than in the cortical areas, we investigated whether WM integrity is different between the SuperAgers (SA) and typical agers (TA) and whether it is associated with superior memory performance as well as a healthy lifestyle. A total of 35 SA and 55 TA were recruited for this study. Further, 3.0-T magnetic resonance imaging (MRI), neuropsychological tests, and lifestyle factors related to cognitive function, such as physical activity and duration of sleep, were evaluated in all participants. SA was defined as individuals demonstrating the youthful performance of verbal and visual memory, as measured by the Seoul Verbal Learning Test (SVLT) and the Rey-Osterrieth Complex Figure Test (RCFT), respectively. Tract-based spatial statistics (TBSS) analysis was used to compare the diffusion values such as fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD) between the SA and TA. SA exhibited better performance in memory, attention, visuospatial, and frontal executive functions than the TA did. SA also exhibited greater amounts of physical activity than the TA did. As compared to TA, SA demonstrated higher FA with lower MD, RD, and AD in the corpus callosum and higher FA and lower RD in the right superior longitudinal fasciculus (SLF), which is significantly associated with memory function. Interestingly, FA values of the body of corpus callosum were correlated with the amount of physical activity. Our findings suggest that WM integrity of the corpus callosum is associated with superior memory function and a higher level of physical activities in SA compared to TA.

Using Smart Bracelets to Assess Heart Rate Among Students During Physical Education Lessons: Feasibility, Reliability, and Validity Study

Background

An increasing number of wrist-worn wearables are being examined in the context of health care. However, studies of their use during physical education (PE) lessons remain scarce.

Objective

We aim to examine the reliability and validity of the Fizzo Smart Bracelet (Fizzo) in measuring heart rate (HR) in the laboratory and during PE lessons.

Methods

In Study 1, 11 healthy subjects (median age 22.0 years, IQR 3.75 years) twice completed a test that involved running on a treadmill at 6 km/h for 12 minutes and 12 km/h for 5 minutes. During the test, participants wore two Fizzo devices, one each on their left and right wrists, to measure their HR. At the same time, the Polar Team2 Pro (Polar), which is worn on the chest, was used as the standard. In Study 2, we went to 10 schools and measured the HR of 24 students (median age 14.0 years, IQR 2.0 years) during PE lessons. During the PE lessons, each student wore a Polar device on their chest and a Fizzo on their right wrist to measure HR data. At the end of the PE lessons, the students and their teachers completed a questionnaire where they assessed the feasibility of Fizzo. The measurements taken by the left wrist Fizzo and the right wrist Fizzo were compared to estimate reliability, while the Fizzo measurements were compared to the Polar measurements to estimate validity. To measure reliability, intraclass correlation coefficients (ICC), mean difference (MD), standard error of measurement (SEM), and mean absolute percentage errors (MAPE) were used. To measure validity, ICC, limits of agreement (LOA), and MAPE were calculated and Bland-Altman plots were constructed. Percentage values were used to estimate the feasibility of Fizzo.

Results

The Fizzo showed excellent reliability and validity in the laboratory and moderate validity in a PE lesson setting. In Study 1, reliability was excellent (ICC>0.97; MD<0.7; SEM<0.56; MAPE<1.45%). The validity as determined by comparing the left wrist Fizzo and right wrist Fizzo was excellent (ICC>0.98; MAPE<1.85%). Bland-Altman plots showed a strong correlation between left wrist Fizzo measurements (bias=0.48, LOA=–3.94 to 4.89 beats per minute) and right wrist Fizzo measurements (bias=0.56, LOA=–4.60 to 5.72 beats per minute). In Study 2, the validity of the Fizzo was lower compared to that found in Study 1 but still moderate (ICC>0.70; MAPE<9.0%). The Fizzo showed broader LOA in the Bland-Altman plots during the PE lessons (bias=–2.60, LOA=–38.89 to 33.69 beats per minute). Most participants considered the Fizzo very comfortable and easy to put on. All teachers thought the Fizzo was helpful.

Conclusions

When participants ran on a treadmill in the laboratory, both left and right wrist Fizzo measurements were accurate. The validity of the Fizzo was lower in PE lessons but still reached a moderate level. The Fizzo is feasible for use during PE lessons.

The accuracy of fitness watches for the measurement of heart rate and energy expenditure during moderate intensity exercise

BACKGROUND

As new technology emerges and updated fitness watches are released to the market, it is important to examine their accuracy. The aim of the current study was to examine the accuracy of three commercially available activity trackers in assessing heart rate (HR) and energy expenditure (EE) during moderate intensity exercise.

METHODS

Twenty healthy participants (Age: 20.5±0.7 yrs., Ht: 173.4±10.8 cm, BM: 72.8±13.9 kg, BMI: 24.0±2.5 kg/m²) wore two fitness watches (FB: Fitbit Versa^TM, San Francisco, CA, USA; and PI: Polar Ignite^TM, Polar Electro Oy, Kempele, Finland) and a chest-worn HR monitor (PTP: Polar TeamPro Sensor^TM, Polar Electro) during a 12-minute exercise protocol at incremental speeds. An electrocardiogram (ECG) and indirect calorimetry were used as criterion measures for HR and EE. Mean absolute percentage error (MAPE) was calculated to determine measurement error.

RESULTS

The MAPE values for HR were 11.6±8.7% for the FB, 11.0±10.0% for the PI, and 6.3±5.2% for the PTP. For EE, MAPE values were 9.6±7.2% for the FB, 16.7±19.6% for the PI and 13.8±13.0% for the PTP.

CONCLUSIONS

Fitness watches relying on optical measures of HR underestimate HR compared to criterion measures during moderate intensity exercise. Despite providing a more accurate measure of HR, a chest-worn monitor does not provide a more accurate estimate of EE compared to fitness watches. The Fitbit provided the most accurate measure of EE when compared to the Polar Ignite watch and chest-worn device.

Total Energy Expenditure, Body Composition, Physical Activity, and Step Count in Japanese Preschool Children: A Study Based on Doubly Labeled Water

Adequate energy intake is essential for the healthy development of children, and the estimated energy requirement of children is determined by total daily energy expenditure (TDEE) and energy deposition for growth. A previous study in Japanese tweens indicated that TDEE could be estimated by fat-free mass (FFM) and step count. The aims of this study were to measure TDEE in Japanese preschool children and to confirm whether TDEE can be estimated by FFM and step count in preschool children. Twenty-one children aged 4-6 years old (11 girls and 10 boys; age, 5.1 (0.9) years; height, 107.2 (6.6) cm; weight, 17.5 (1.7) kg; BMI, 15.3 (1.3); mean (SD)) participated in this study. FFM and 7-day TDEE were obtained by doubly labeled water (DLW). Participants wore accelerometers during the DLW measurement period. No significant differences were observed in age-adjusted height, weight, BMI, FFM (13.0 (1.5) kg), or TDEE (1300 (174) kcal/day) between girls and boys. Girls had significantly higher percent fat and a lower daily step count than boys. Stepwise regression analysis revealed that FFM and step count were significant predictors of TDEE; TDEE (kcal/day) = 85.0 × FFM (kg) + 0.0135 × step count (steps/day). This accounted for 74% of TDEE variance. The current study confirmed that FFM and step count are major determinants of TDEE in Japanese preschool children as well as adolescents, although further research is needed to obtain precise equations.

Impact of Activity-Based Working and Height-Adjustable Desks on Physical Activity, Sedentary Behavior, and Space Utilization among Office Workers: A Natural Experiment

It has been reported that office environment is an important determinant of physical activity (PA) and sedentary behavior (SB) in office workers. However, the effect of changes in office environment (office renovation) is unclear. The purpose of this study was to examine PA, SB, and space utilization changes among office workers in response to office renovation. This study was a natural experiment at three offices of a single company in Tokyo, Japan. The participants were, 13 workers from one office in the renovation group (mean age: 37.9 ± 10.8 years, percentage of females: 23.1%) and 29 from two offices in the control group (mean age: 42.3 ± 11.2 years, percentage of females: 31.0%). In the renovation, introduction of activity-based working (ABW) and installation of height-adjustable desks (HAD) were adopted. The ABW office was designed to provide various shared workstations, enabling the workers to choose workstations depending on their task or mood. Accelerometer measurement and object detection method using artificial intelligence (AI) technology for video images were used to assess behavior and space utilization before and after the renovation. Two weeks after the renovation, significant improvements in SB (pre- to post-renovation improvements: 346.8 ± 28.6 to 321.2 ± 17.8 min/working-hours) and PA (total PA: 173.2 ± 28.6 to 198.8 ± 17.8 min/working-hours; and light-intensity PA: 130.4 ± 27.1 to 150.7 ± 31.0 min/working-hours) were observed. In addition, the results of the object detection analysis showed that the central aisle of the office and shared HAD workstations near the entrance or window were utilized more frequently than the other spaces. This study suggested that office renovation could improve SB and PA immediately after the renovation. Moreover, utilized spaces and HAD workstations could play an important role to enhance employees’ activity in an ABW office.