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2014 Fall-Detection Algorithm Using 3-Axis Acceleration: Combination with Simple Threshold and Hidden Markov Model
Dongha Lim, Chulho Park, Nam Ho Kim, Sang-Hoon Kim, Yun Seop Yu
J. Appl. Math. 2014(SI01): 1-8 (2014). DOI: 10.1155/2014/896030

Abstract

Falls are a serious medical and social problem among the elderly. This has led to the development of automatic fall-detection systems. To detect falls, a fall-detection algorithm that combines a simple threshold method and hidden Markov model (HMM) using 3-axis acceleration is proposed. To apply the proposed fall-detection algorithm and detect falls, a wearable fall-detection device has been designed and produced. Several fall-feature parameters of 3-axis acceleration are introduced and applied to a simple threshold method. Possible falls are chosen through the simple threshold and are applied to two types of HMM to distinguish between a fall and an activity of daily living (ADL). The results using the simple threshold, HMM, and combination of the simple method and HMM were compared and analyzed. The combination of the simple threshold method and HMM reduced the complexity of the hardware and the proposed algorithm exhibited higher accuracy than that of the simple threshold method.

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Dongha Lim. Chulho Park. Nam Ho Kim. Sang-Hoon Kim. Yun Seop Yu. "Fall-Detection Algorithm Using 3-Axis Acceleration: Combination with Simple Threshold and Hidden Markov Model." J. Appl. Math. 2014 (SI01) 1 - 8, 2014. https://doi.org/10.1155/2014/896030

Information

Published: 2014
First available in Project Euclid: 27 February 2015

Digital Object Identifier: 10.1155/2014/896030

Rights: Copyright © 2014 Hindawi

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Vol.2014 • No. SI01 • 2014
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