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Development and feasibility of a wearable infant wrist band for the objective measurement of physical activity using accelerometery.

ABSTRACT: Background:It is important to be able to reliably and feasibly measure infant and toddler physical activity in order to determine adherence to current physical activity guidelines and effects on early life development, growth and health. This study aimed to describe the development of an infant wearable wrist-worn band for the measurement of physical activity; to determine the feasibility of the device data for observational measurement of physical activity and to determine the caregiver reported acceptability of the infant wearable wrist band. Methods:After various iterations of prototypes and piloting thereof, a final wearable band was designed to fit an Axivity AX3 monitor. Mother and infant/toddler (aged 3-24 months) pairs (n?=?152) were recruited, and mothers were asked for their child to wear the band with enclosed monitor at all times for 1 week (minimum 3 days). Feasibility was assessed by determining technical reliability of the data, as well as wear time and compliance according to requirements for observational measurement. Acceptability was assessed via questionnaire. Results:Technical reliability of the Axivity AX3 monitors in this age group was good. After excluding days that did not have at least 15 h of wear time, only 2% of participants had less than three valid days of data remaining, and 4% of participants had no data (due to device loss or data loss). Therefore, 94% of participants were compliant, having three or more days of wear with at least 15 h of wear per day, thus providing enough valid data for observational measurement. The majority (60%) of mothers reported being "very happy" with the safety of the device, while only 8% were "a little worried". A large majority (86%) of mothers stated that the band attracted attention from others, although this was mostly attributed to curiosity about the function of the band. Most (80%) of participants rated the comfort of the band as "comfortable", and 10% rated it as "very comfortable". Conclusions:The infant wearable band proved to be feasible and acceptable according to the criteria tested, and compliance wearing the band was good. We have therefore provided a replicable, comfortable and acceptable wearable band for the measurement of infant and toddler physical activity.

SUBMITTER: Prioreschi A

PROVIDER: S-EPMC5831201 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe rapid advancements in science and technology of wrist-wearable activity devices offer considerable potential for clinical applications. Self-monitoring of physical activity (PA) with activity devices is helpful to improve the PA levels of adolescents. However, knowing the accuracy of activity devices in adolescents is necessary to identify current levels of PA and assess the effectiveness of intervention programs designed to increase PA.ObjectiveThe study aimed to determine the validity of the 11 commercially available wrist-wearable activity devices for monitoring total steps and total 24-hour total energy expenditure (TEE) in healthy adolescents under simulated free-living conditions.MethodsNineteen (10 male and 9 female) participants aged 14 to 18 years performed a 24-hour activity cycle in a metabolic chamber. Each participant simultaneously wore 11 commercial wrist-wearable activity devices (Mi Band 2 [XiaoMi], B2 [Huawei], Bong 2s [Meizu], Amazfit [Huamei], Flex [Fitbit], UP3 [Jawbone], Shine 2 [Misfit], GOLiFE Care-X [GoYourLife], Pulse O2 [Withings], Vivofit [Garmin], and Loop [Polar Electro]) and one research-based triaxial accelerometer (GT3X+ [ActiGraph]). Criterion measures were total EE from the metabolic chamber (mcTEE) and total steps from the GT3X+ (AGsteps).ResultsPearson correlation coefficients r for 24-hour TEE ranged from .78 (Shine 2, Amazfit) to .96 (Loop) and for steps ranged from 0.20 (GOLiFE) to 0.57 (Vivofit). Mean absolute percent error (MAPE) for TEE ranged from 5.7% (Mi Band 2) to 26.4% (Amazfit) and for steps ranged from 14.2% (Bong 2s) to 27.6% (Loop). TEE estimates from the Mi Band 2, UP3, Vivofit, and Bong 2s were equivalent to mcTEE. Total steps from the Bong 2s were equivalent to AGsteps.ConclusionsOverall, the Bong 2s had the best accuracy for estimating TEE and total steps under simulated free-living conditions. Further research is needed to examine the validity of these devices in different types of physical activities under real-world conditions.

Project description:BACKGROUND:South Asians are one of the fastest growing ethnic groups in western countries with a high incidence of chronic diseases like metabolic syndrome and cardiovascular disease occurring at younger ages and lower body weight compared with white Europeans. Physically active lifestyle and reduced sedentary time are modifiable risk factors that can decrease burden of chronic diseases. Population-level surveys based on self-report show South Asians engage in low levels of physical activity. Because of known limitations with self-report data, we aimed to synthesize available evidence to generate a physical activity /sedentary time profile of South Asians from studies using accelerometry. METHODS:We systematically searched Medline, EMBASE, CINAHL, PsycINFO, and SportDiscus. We included studies applying accelerometry to measure physical activity /sedentary time under free-living. Studies with an exclusive focus on drugs or including participants with health conditions/physical disability, and special populations (athletes/pregnant women) were excluded. Two authors independently adjudicated inclusion of citations at title/abstract and full text. We applied a standardized data abstraction form to extract relevant data. We evaluated methodological quality using Newcastle Ottawa Quality Assessment Scale. Due to variability and inconsistencies in measurement and reporting of physical activity /sedentary time, we only provide a narrative synthesis. FINDINGS:We identified only 14 studies(n = 1,338). Despite using similar accelerometry assumptions, we noted variability in reported outcomes for physical activity and sedentary time. Sedentary time ranged from 482(98) to 587 min/day. Mean light physical activity ranged from 211.69(67. 38) to 574(227) min/day. Moderate to vigorous physical activity among South Asian women ranged from 17-41 min/day and among men, 32-43 min/day. CONCLUSION:South Asians exhibited higher levels of physical activity when compared to the Canadian population level survey but not when compared to the American population level survey. Overall, fewer studies, and small sample sizes led to considerable variability limiting any effective comparisons. Results highlight the importance of conducting methodologically robust studies based on random sampling to advance the field, and to capture true levels of sedentary time and physical activity in the South Asian population.

Project description:BackgroundSubclinical (ie, threshold) social anxiety can greatly affect young people's lives, but existing solutions appear inadequate considering its rising prevalence. Wearable sensors may provide a novel way to detect social anxiety and result in new opportunities for monitoring and treatment, which would be greatly beneficial for persons with social anxiety, society, and health care services. Nevertheless, indicators such as skin temperature measured by wrist-worn sensors have not been used in prior work on physiological social anxiety detection.ObjectiveThis study aimed to investigate whether subclinical social anxiety in young adults can be detected using physiological data obtained from wearable sensors, including heart rate, skin temperature, and electrodermal activity (EDA).MethodsYoung adults (N=12) with self-reported subclinical social anxiety (measured using the widely used self-reported version of the Liebowitz Social Anxiety Scale) participated in an impromptu speech task. Physiological data were collected using an E4 Empatica wearable device. Using the preprocessed data and following a supervised machine learning approach, various classification algorithms such as Support Vector Machine, Decision Tree, Random Forest, and K-Nearest Neighbours (KNN) were used to develop models for 3 different contexts. Models were trained to differentiate (1) between baseline and socially anxious states, (2) among baseline, anticipation anxiety, and reactive anxiety states, and (3) social anxiety among individuals with social anxiety of differing severity. The predictive capability of the singular modalities was also explored in each of the 3 supervised learning experiments. The generalizability of the developed models was evaluated using 10-fold cross-validation as a performance index.ResultsWith modalities combined, the developed models yielded accuracies between 97.54% and 99.48% when differentiating between baseline and socially anxious states. Models trained to differentiate among baseline, anticipation anxiety, and reactive anxiety states yielded accuracies between 95.18% and 98.10%. Furthermore, the models developed to differentiate between social anxiety experienced by individuals with anxiety of differing severity scores successfully classified with accuracies between 98.86% and 99.52%. Surprisingly, EDA was identified as the most effective singular modality when differentiating between baseline and social anxiety states, whereas ST was the most effective modality when differentiating anxiety among individuals with social anxiety of differing severity.ConclusionsThe results indicate that it is possible to accurately detect social anxiety as well as distinguish between levels of severity in young adults by leveraging physiological data collected from wearable sensors.

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Development and feasibility of a wearable infant wrist band for the objective measurement of physical activity using accelerometery.

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