NDLI: Quantitative analysis of the fall-risk assessment test with wearable inertia sensors

Content Provider	IEEE Xplore Digital Library
Author	Tmaura, T. Zakaria, N.A. Kuwae, Y. Sekine, M. Minato, K. Yoshida, M.
Copyright Year	2013
Description	Author affiliation: Dept. of Biomed. Eng., Osaka Electro-Commun. Univ., Neyagawa, Japan (Tmaura, T.; Sekine, M.; Yoshida, M.) \|\| Grad. Sch. if Inf. Sci., Nara Inst. of Sci. & Technol., Ikoma, Japan (Zakaria, N.A.; Minato, K.) \|\| Daigo Hosp., Miyazaki, Japan (Kuwae, Y.)
Abstract	We performed a quantitative analysis of the fall-risk assessment test using a wearable inertia sensor focusing on two tests: the time up and go (TUG) test and the four square step test (FSST). These tests consist of various daily activities, such as sitting, standing, walking, stepping, and turning. The TUG test was performed by subjects at low and high fall risk, while FSST was performed by healthy elderly and hemiplegic patients with high fall risk. In general, the total performance time of activities was evaluated. Clinically, it is important to evaluate each activity for further training and management. The wearable sensor consisted of an accelerometer and angular velocity sensor. The angular velocity and angle of pitch direction were used for TUG evaluation, and those in the pitch and yaw directions at the thigh were used for FSST. Using the threshold of the angular velocity signal, we classified the phase corresponding to each activity. We then observed the characteristics of each activity and recommended suitable training and management. The wearable sensor can be used for more detailed evaluation in fall risk management. The wearable sensor can be used more detailed evaluation for fall-risk management test.
Starting Page	7217
Ending Page	7220
File Size	340145
Page Count	4
File Format	PDF
ISBN	9781457702167
ISSN	1557170X
DOI	10.1109/EMBC.2013.6611223
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-03
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sensors Angular velocity Senior citizens Legged locomotion Thigh Wireless sensor networks Wireless communication
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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