National Repository of Grey Literature 3 records found  Search took 0.01 seconds. 
Human behaviour monitoring system based on smartphone and bracelet data analysis
Mikulec, Marek ; Zvončák, Vojtěch (referee) ; Mekyska, Jiří (advisor)
There has been established new technological field using smart phones and wearable devices for medical research since the arrival of health 4.0. The main goal of this work is to design, implement and test new system for monitoring people´s behaviour using smart phone and wearable device. These smart compoments should oblige requirements of health~4.0. This work uses open source software AWARE Framework and data from Fitbit API. The final system enables gathering and sharing 36 measurable metrics from smart phone and wearable device. Furthermore it secures efective access to gathered data and puts particular emphasis on the security of the system. Finally the system was used to examine a patterns of REM (Rapid Eye Movement) sleep behaviour disorder.
Using wearables to monitor physical activity
Mádlová, Zdenka ; Větrovský, Tomáš (advisor) ; Omcirk, Dan (referee)
Title: Using wearables to monitor physical activity Objectives: The aim of this study is to assess the validity of the Fitbit Charge 5 compared to the ActiGraph wGT3x-BT for the assessment of physical activity (steps, time spent in moderate physical activity, vigorous physical activity and moderate to vigorous physical activity) in adults. Methods: The Fitbit Charge 5 commercial physical activity monitor was compared to the ActiGraph wGT3x-BT under daily living conditions. Healthy adults (n=32) wore both devices in a 7-day field study. Data were analyzed based on days for steps, minutes of moderate physical activity, minutes of vigorous physical activity and minutes of moderate to vigorous physical activity. Pearson's correlation coefficient and Bland-Altman plot were used to assess the correlation between the Fitbit Charge 5 device and the criterion. Mean percentage error (MPE) and mean absolute percentage error (MAPE) were calculated to assess differences. Results: The Fitbit Charge 5 had a very strong correlation (r = 0,94; 95% CI 0,92- 0,96) on the step measurement with criterion. The MAPE value was 23%. A weak correlation with respect to the criterion was demonstrated for the measured physical activity of moderate intensity (r = 0,33; 95% CI 0,27- 0,39). For vigorous physical activity a...
Human behaviour monitoring system based on smartphone and bracelet data analysis
Mikulec, Marek ; Zvončák, Vojtěch (referee) ; Mekyska, Jiří (advisor)
There has been established new technological field using smart phones and wearable devices for medical research since the arrival of health 4.0. The main goal of this work is to design, implement and test new system for monitoring people´s behaviour using smart phone and wearable device. These smart compoments should oblige requirements of health~4.0. This work uses open source software AWARE Framework and data from Fitbit API. The final system enables gathering and sharing 36 measurable metrics from smart phone and wearable device. Furthermore it secures efective access to gathered data and puts particular emphasis on the security of the system. Finally the system was used to examine a patterns of REM (Rapid Eye Movement) sleep behaviour disorder.

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