Wearable Pre-Impact Fall Detection System Based on 3D Accelerometer and Subject's Height

This study presents a low-power wearable system able to predict a fall by detecting a pre-impact condition, performed through a simple analysis of motion data (acceleration) and height of the subject. The system can detect a fall in all directions with an average consumption of 5.91 mA; i.e., it can...

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Veröffentlicht in:	IEEE sensors journal Jg. 22; H. 2; S. 1738 - 1745
Hauptverfasser:	Ferreira de Sousa, Felipe Augusto Sodre, Escriba, Christophe, Avina Bravo, Eli Gabriel, Brossa, Vincent, Fourniols, Jean-Yves, Rossi, Carole
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 15.01.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Institute of Electrical and Electronics Engineers
Schlagworte:	Accelerometers Air bags Algorithms Biomedical monitoring Classification algorithms Customizable algorithm Electronics Engineering Sciences Fall detection fall detection system False alarms Injuries Instrumentation and Detectors Lead time Physics pre-impact detection Senior citizens Sensitivity Signal and Image processing threshold-based wearable systems Wearable technology Threshold-based Pre-impact detection Wearable systems Customizable algorithm Fall Detection System
ISSN:	1530-437X, 1558-1748
Online-Zugang:	Volltext
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