Dataset Information

Use of wearable sensors to assess compliance of asthmatic children in response to lockdown measures for the COVID-19 epidemic.

ABSTRACT: Between March and April 2020, Cyprus and Greece health authorities enforced three escalated levels of public health interventions to control the COVID-19 pandemic. We quantified compliance of 108 asthmatic schoolchildren (53 from Cyprus, 55 from Greece, mean age 9.7 years) from both countries to intervention levels, using wearable sensors to continuously track personal location and physical activity. Changes in 'fraction time spent at home' and 'total steps/day' were assessed with a mixed-effects model adjusting for confounders. We observed significant mean increases in 'fraction time spent at home' in Cyprus and Greece, during each intervention level by 41.4% and 14.3% (level 1), 48.7% and 23.1% (level 2) and 45.2% and 32.0% (level 3), respectively. Physical activity in Cyprus and Greece demonstrated significant mean decreases by - 2,531 and - 1,191 (level 1), - 3,638 and - 2,337 (level 2) and - 3,644 and - 1,961 (level 3) total steps/day, respectively. Significant independent effects of weekends and age were found on 'fraction time spent at home'. Similarly, weekends, age, humidity and gender had an independent effect on physical activity. We suggest that wearable technology provides objective, continuous, real-time location and activity data making possible to inform in a timely manner public health officials on compliance to various tiers of public health interventions during a pandemic.

SUBMITTER: Kouis P

PROVIDER: S-EPMC7971022 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Use of wearable sensors to assess compliance of asthmatic children in response to lockdown measures for the COVID-19 epidemic.

Kouis Panayiotis P Michanikou Antonis A Anagnostopoulou Pinelopi P Galanakis Emmanouil E Michaelidou Eleni E Dimitriou Helen H Matthaiou Andreas M AM Kinni Paraskevi P Achilleos Souzana S Zacharatos Harris H Papatheodorou Stefania I SI Koutrakis Petros P Nikolopoulos Georgios K GK Yiallouros Panayiotis K PK

Scientific reports 20210315 1

Between March and April 2020, Cyprus and Greece health authorities enforced three escalated levels of public health interventions to control the COVID-19 pandemic. We quantified compliance of 108 asthmatic schoolchildren (53 from Cyprus, 55 from Greece, mean age 9.7 years) from both countries to intervention levels, using wearable sensors to continuously track personal location and physical activity. Changes in 'fraction time spent at home' and 'total steps/day' were assessed with a mixed-effect ...[more]

PMID: 33723342

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Project description:Huntington's disease (HD), like many other neurological disorders, affects both lower and upper limb function that is typically assessed in the clinic - providing a snapshot of disease symptoms. Wearable sensors enable the collection of real-world data that can complement such clinical assessments and provide a more comprehensive insight into disease symptoms. In this context, almost all studies are focused on assessing lower limb function via monitoring of gait, physical activity and ambulation. In this study, we monitor upper limb function during activities of daily living in individuals with HD (n = 16), prodromal HD (pHD, n = 7), and controls (CTR, n = 16) using a wrist-worn wearable sensor, called PAMSys ULM, over seven days. The participants were highly compliant in wearing the sensor with an average daily compliance of 99% (100% for HD, 98% for pHD, and 99% for CTR). Goal-directed movements (GDM) of the hand were detected using a deep learning model, and kinematic features of each GDM were estimated. The collected data was used to predict disease groups (i.e., HD, pHD, and CTR) and clinical scores using a combination of statistical and machine learning-based models. Significant differences in GDM features were observed between the groups. HD participants performed fewer GDMs with long duration (> 7.5 seconds) compared to CTR (p-val = 0.021, d = -0.86). In velocity and acceleration metrics, the highest effect size feature was the entropy of the velocity zero-crossing length segments (HD vs CTR p-val <0.001, d = -1.67; HD vs pHD p-val = 0.043, d=-0.98; CTR vs pHD p-val = 0.046, d=0.96). In addition, this same variable showed a strongest correlation with clinical scores. Classification models achieved good performance in distinguishing HD, pHD and CTR individuals with a balanced accuracy of 67% and a 0.72 recall for the HD group, while regression models accurately predicted clinical scores. Notably the explained variance for the upper extremity function subdomain scale of Unified Huntington's Disease Rating Scale (UHDRS) was the highest, with the model capturing 60% of the variance. Our findings suggest the potential of wearables and machine learning for early identification of phenoconversion, remote monitoring in HD, and evaluating new treatments efficacy in clinical trials and medicine.

Project description:The coronavirus disease 2019 (COVID-19) is one of the most severe global health uncertainties to date. Although significant global effort has been put into implementing COVID-19 pandemic control measures such as lockdowns, travel restrictions, and hygiene precautions, the transmission is expected to resurface once these efforts are discontinued. We aimed to determine the prevalence and factors associated with compliance with presidential 53-day lockdown measures in June-July 2021 in northern Uganda. In this cross-sectional study, 587 adult participants (≥18 years old) from northern Uganda were selected using a systematic sampling method. Data collection involved interviewer-administered questionnaires with an internal validity of Cronbach's α = .72. Socio-demographic characteristics of participants were described, and multivariable modified Poisson regressions were performed to assess prevalence ratios between dependent and selected independent variables, with respective P values at 95% confidence intervals. All analyses were conducted using Stata 17.0. Participants' compliance with the presidential lockdown directives was high at 88%(95% CI: 85%-90%). Compliance with the presidential directives was more likely among participants who agreed to the lockdown measures [adjusted Prevalence Ratio, aPR = 1.28 (95% CI: 1.10-1.49; P = .001)] compared to those who did not, and more likely among those who were afraid of death from COVID-19 [aPR = 1.08 (95% CI: 1.01-1.15; P = .023)] than those who did not. However, compliance was less likely among males [aPR = 0.91 (95% CI: 0.86-0.97; P = .002)] compared to females, those aged 35 to 44 years [aPR = 0.87 (95% CI: 0.79-0.97; P = .013)] compared to those less 25 years; and unmarried [aPR = 0.89 (95% CI: 0.82-0.97; P = .011)] compared to the married. Compliance with the COVID-19 presidential lockdown measures in northern Uganda was high. The factors associated with compliance were the fear of death and agreement with presidential lockdown measures. However, compliance was less likely among males, unmarried persons, and persons aged 35 to 44. The authors recommend more community engagements, participation, sensitization, mobilization, and simultaneous application of multiple public health approaches to improve compliance and control of COVID-19.

Dataset Information

Use of wearable sensors to assess compliance of asthmatic children in response to lockdown measures for the COVID-19 epidemic.

Publications

Use of wearable sensors to assess compliance of asthmatic children in response to lockdown measures for the COVID-19 epidemic.

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