Fall-prediction algorithm using a neural network for safety enhancement of elderly

Shih Hung Yang, Wenlong Zhang, Yizou Wang, Masayoshi Tomizuka

研究成果: Conference contribution

13 引文 斯高帕斯(Scopus)

摘要

Among the elderly, falls are a well-known safety hazard, often resulting in major injury, hospitalization and death. To reduce the injuries caused by falls, it is first necessary to predict a fall as early as possible and then to provide protection for the person who is falling. This paper proposes a fall-prediction algorithm (FPA) that can predict whether the person will fall within one-walking-step. The fall prediction is different from the fall detection, and it is intended to predict a fall before it occurs and provide sufficient time to enable a safety mechanism. The proposed FPA adopts a neural network to perform prediction in which the inputs are accelerations and angular rates of upper trunk and the output presents fall or no fall. A wearable inertial sensor package with a triple axis accelerometer and a triple axis gyroscope is developed to measure the required motion data. Five subjects were asked to wear the inertial sensor package and perform a number of simulated falls. The experimental results show that the FPA could predict a fall 0.4 seconds prior to the beginning of the fall. The time interval is sufficient to inflate an airbag covering the head, trunk, and hip, an intervention that would reduce fall-related injuries among older people.

原文English
主出版物標題2013 CACS International Automatic Control Conference, CACS 2013 - Conference Digest
頁面245-249
頁數5
DOIs
出版狀態Published - 2013 十二月 1
事件2013 CACS International Automatic Control Conference, CACS 2013 - Nantou, Taiwan
持續時間: 2013 十二月 22013 十二月 4

出版系列

名字2013 CACS International Automatic Control Conference, CACS 2013 - Conference Digest

Other

Other2013 CACS International Automatic Control Conference, CACS 2013
國家/地區Taiwan
城市Nantou
期間13-12-0213-12-04

All Science Journal Classification (ASJC) codes

  • 控制與系統工程

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