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Background Individuals in Uganda's urban slums have unmet mental health needs due to limited healthcare infrastructure, poor environmental conditions, and extreme poverty. Researchers often use wearable devices to measure factors associated with mental health including sleep, physical activity, and exposure to environmental stressors. However, the use of wearables for research purposes in low-resource settings is limited. This pilot study investigated the feasibility and acceptability of wearables and accompanying daily diaries to assess sleep and other health indicators in young women living in Kampala's slums. Methods Women ( n = 60 total, two groups) aged 18–24 living in three urban slums participated in 5-day pilot protocols comprised of wearing Garmin vívoactive 3 smartwatches and completing daily diaries concerning sleep and physical activities. Participants completed surveys about their experiences. We based analyses on survey findings and data completeness. Results All participants responded to daily diaries. All but one reported wearing the device nonstop and 51 had recoverable heart rate data with median data coverage of 93.2%. Most devices (87.5%) recorded data for 5 days without running out of battery. Some participants (8.5%) found the wearable uncomfortable during the day, and 25% found it uncomfortable at night. Few participants (6.7%) reported feeling unsafe with the wearable, with most reports occurring prior to the availability of bracelet-like wearable covers. Conclusions Study protocols implementing wearables and complimentary daily diaries are feasible in this urban population. However, important contextual factors including participant and researcher training and safety concerns warrant additional considerations for acceptable utilization of wearable devices for research in other low-resource settings.
Background Individuals in Uganda's urban slums have unmet mental health needs due to limited healthcare infrastructure, poor environmental conditions, and extreme poverty. Researchers often use wearable devices to measure factors associated with mental health including sleep, physical activity, and exposure to environmental stressors. However, the use of wearables for research purposes in low-resource settings is limited. This pilot study investigated the feasibility and acceptability of wearables and accompanying daily diaries to assess sleep and other health indicators in young women living in Kampala's slums. Methods Women ( n = 60 total, two groups) aged 18–24 living in three urban slums participated in 5-day pilot protocols comprised of wearing Garmin vívoactive 3 smartwatches and completing daily diaries concerning sleep and physical activities. Participants completed surveys about their experiences. We based analyses on survey findings and data completeness. Results All participants responded to daily diaries. All but one reported wearing the device nonstop and 51 had recoverable heart rate data with median data coverage of 93.2%. Most devices (87.5%) recorded data for 5 days without running out of battery. Some participants (8.5%) found the wearable uncomfortable during the day, and 25% found it uncomfortable at night. Few participants (6.7%) reported feeling unsafe with the wearable, with most reports occurring prior to the availability of bracelet-like wearable covers. Conclusions Study protocols implementing wearables and complimentary daily diaries are feasible in this urban population. However, important contextual factors including participant and researcher training and safety concerns warrant additional considerations for acceptable utilization of wearable devices for research in other low-resource settings.
Background Robust measurements of children’s postures and movements are required to understand their impact on health and wellbeing. Recent advances in wearable sensor technology may enable the development of accurate measurements. Motus, a wearable sensor based system for surveillance of postures and movements, has shown high accuracy among adults. However, its accuracy to measure postures and movements among children is unknown. This study aimed to evaluate the criterion validity of Motus to measure common postures and movements among children between 3–14 years old in a laboratory setting. We further assessed if the sex or age of children impacted accuracy. Method Data were collected on 48 children who attended a structured ~ 1-hour data collection session at a Curtin University laboratory with their caregivers. The session was video recorded and thigh acceleration was measured using a SENS accelerometer. Data from the accelerometer were processed and classified into nine postures and movements using the Motus software. Human-coded video provided the ground truth to calculate sensitivity, specificity, precision, F1-scores, and balanced accuracy. Results We observed good to very good overall accuracy (F1-score = 61.9, balanced accuracy = 81.1%) and for classifying lying, sitting, standing (ranging between 63.2–85.3%). Walking and running were classified with moderate to very good accuracy. The lowest accuracy was observed for classifying stair climbing. We found a higher accuracy for stair climbing among girls compared to boys and for older compared to younger age-groups for walking, running and stair climbing. Conclusion Motus showed moderate to very good accuracy for detecting lying, sitting, standing, and running among children. The system could be improved for classifying the more dynamic postures and movements (i.e. walking, running and stair climbing), particularly among younger children and developed further to measure more child-specific postures and movements.
Background: ActiMotus, a thigh-accelerometer-based software used for the classification of postures and movements (PaMs), has shown high accuracy among adults and school-aged children; however, its accuracy among younger children and potential differences between sexes are unknown. This study aimed to evaluate the accuracy of ActiMotus to measure PaMs among children between 3 and 14 years and to assess if this was influenced by the sex or age of children. Method: Forty-eight children attended a structured ~1-hour data collection session at a laboratory. Thigh acceleration was measured using a SENS accelerometer, which was classified into nine PaMs using the ActiMotus software. Human-coded video recordings of the session provided the ground truth. Results: Based on both F1 scores and balanced accuracy, the highest levels of accuracy were found for lying, sitting, and standing (63.2–88.2%). For walking and running, accuracy measures ranged from 48.0 to 85.8%. The lowest accuracy was observed for classifying stair climbing. We found a higher accuracy for stair climbing among girls compared to boys and for older compared to younger age groups for walking, running, and stair climbing. Conclusions: ActiMotus could accurately detect lying, sitting, and standing among children. The software could be improved for classifying walking, running, and stair climbing, particularly among younger children.
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