Research Article
Fall Detection with Orientation Calibration Using a Single Motion Sensor
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@INPROCEEDINGS{10.1007/978-3-319-58877-3_31, author={Shuo Yu and Hsinchun Chen}, title={Fall Detection with Orientation Calibration Using a Single Motion Sensor}, proceedings={Wireless Mobile Communication and Healthcare. 6th International Conference, MobiHealth 2016, Milan, Italy, November 14-16, 2016, Proceedings}, proceedings_a={MOBIHEALTH}, year={2017}, month={6}, keywords={Fall detection Sensor orientation calibration Machine learning}, doi={10.1007/978-3-319-58877-3_31} }- Shuo Yu
Hsinchun Chen
Year: 2017
Fall Detection with Orientation Calibration Using a Single Motion Sensor
MOBIHEALTH
Springer
DOI: 10.1007/978-3-319-58877-3_31
Abstract
Falls are a major threat for senior citizens living independently. Sensor technologies and fall detection algorithms have emerged as a reliable, low-cost solution for this issue. We proposed a sensor orientation calibration algorithm to better address the uncertainty issue faced by fall detection algorithms in real world applications. We conducted controlled experiments of simulated fall events and non-fall activities on student subjects. We evaluated our proposed algorithm using sequence matching based machine learning approaches on five different body positions. The algorithm achieved an F-measure of 90 to 95% in detecting falls. Sensors worn as necklace pendants or in chest pockets performed best.
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