A Fall Detection System based on SensorTag and Windows 10 IoT Core

DOI

10.2991/mse-15.2016.41How to use a DOI?

Keywords

Fall Detection; Wearable Sensors; Data Fusion

Abstract

Falls that lead to fatal injury have become a great challenge that cannot be neglected for elderly people. In this study, a surveillance system based on SensorTag and Windows 10 IoT Core for real-time fall detection is proposed. Raw data including three-dimensional accelerometer, gyroscope, and magnetometer are provided by SensotTag. Windows 10 IoT Core device makes use of these information to get the orientation of the subject by efficient data fusion and fall detection algorithms. Microsoft Azure services and Mobile/PC applications are also designed to achieve seamless data processing, analyzing, storing and acquiring at any time from any place as long as they have access to the Internet. Tests of the proposed system are performed according to experimental protocols including intentional falls and activities of daily lives. The results show that the proposed fall detection solution is reliable and effective.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yuejiao Cheng
AU  - Chenglong Jiang
AU  - Jiong Shi
PY  - 2016/03
DA  - 2016/03
TI  - A Fall Detection System based on SensorTag and Windows 10 IoT Core
BT  - Proceedings of the 2015 International Conference on Mechanical Science and Engineering
PB  - Atlantis Press
SP  - 238
EP  - 244
SN  - 2352-5401
UR  - https://doi.org/10.2991/mse-15.2016.41
DO  - 10.2991/mse-15.2016.41
ID  - Cheng2016/03
ER  -