Implementation and pilot testing of an Android-based real-time activity detection system

Real-time measurement of physical activity type on mobile devices could advance physical activity measurement studies and create new opportunities for real-time health interventions that promote physical activity. In this work, an algorithm for four-class activity detection ("Ambulation",...

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Online Access:http://hdl.handle.net/2047/d20003208
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spelling ndltd-NEU--neu-12362021-05-25T05:09:36ZImplementation and pilot testing of an Android-based real-time activity detection systemReal-time measurement of physical activity type on mobile devices could advance physical activity measurement studies and create new opportunities for real-time health interventions that promote physical activity. In this work, an algorithm for four-class activity detection ("Ambulation", "Cycling", "Sedentary" and "Other") from wrist or ankle accelerometer-based activity monitors was extended to run in real-time on Android mobile phones with wireless accelerometers. Experiments validating the method using an existing activity dataset were replicated in the new Java-based system and results were verified to be consistent with the former MATLAB implementation by Mannini et al. The Android application was implemented with two modes: the continuous mode, which was suitable for instant classification (10s latency) and a power-efficient burst mode, which could be utilized in large scale study but with longer latency (up to 70s latency).http://hdl.handle.net/2047/d20003208
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sources NDLTD
description Real-time measurement of physical activity type on mobile devices could advance physical activity measurement studies and create new opportunities for real-time health interventions that promote physical activity. In this work, an algorithm for four-class activity detection ("Ambulation", "Cycling", "Sedentary" and "Other") from wrist or ankle accelerometer-based activity monitors was extended to run in real-time on Android mobile phones with wireless accelerometers. Experiments validating the method using an existing activity dataset were replicated in the new Java-based system and results were verified to be consistent with the former MATLAB implementation by Mannini et al. The Android application was implemented with two modes: the continuous mode, which was suitable for instant classification (10s latency) and a power-efficient burst mode, which could be utilized in large scale study but with longer latency (up to 70s latency).
title Implementation and pilot testing of an Android-based real-time activity detection system
spellingShingle Implementation and pilot testing of an Android-based real-time activity detection system
title_short Implementation and pilot testing of an Android-based real-time activity detection system
title_full Implementation and pilot testing of an Android-based real-time activity detection system
title_fullStr Implementation and pilot testing of an Android-based real-time activity detection system
title_full_unstemmed Implementation and pilot testing of an Android-based real-time activity detection system
title_sort implementation and pilot testing of an android-based real-time activity detection system
publishDate
url http://hdl.handle.net/2047/d20003208
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