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 and Yun Seop Yu

Journal of Applied Mathematics, 2014, vol. 2014, issue 1

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.

Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1155/2014/896030

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:jnljam:v:2014:y:2014:i:1:n:896030

Access Statistics for this article

More articles in Journal of Applied Mathematics from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().