NDLI: Fall-detection solution for mobile platforms using accelerometer and gyroscope data

Content Provider	IEEE Xplore Digital Library
Author	De Cillisy, F. De Simioy, F. Guidoy, F. Incalzi, R.A. Setolay, R.
Copyright Year	2015
Description	Author affiliation: Dept. of Gerontology &Geriatrics, Univ. Campus Bio-Medico di Roma, Rome, Italy (Incalzi, R.A.) \|\| Complex Syst. & Security Lab, Univ. Campus Bio-Medico di Roma, Rome, Italy (De Cillisy, F.; De Simioy, F.; Guidoy, F.; Setolay, R.)
Abstract	Falls are a major health risk that diminish the quality of life among elderly people. Apart from falls themselves, most dramatic consequences are usually related with long lying periods that can cause serious side effects. These findings call for pervasive long-term fall detection systems able to automatically detect falls. In this paper, we propose an effective fall detection algorithm for mobile platforms. Using data retrieved from wearable sensors, such as Inertial Measurements Units (IMUs) and/or SmartPhones (SPs), our algorithm is able to detect falls using features extracted from accelerometer and gyroscope. While mostly of the mobile-based solutions for fall management deal only with accelerometer data, in the proposed approach we combine the instantaneous acceleration magnitude vector with changes of the user's heading in a Threshold Based Algorithm (TBA). In such a way, we were able to handle falls detection with minimal computational load, increasing the overall system accuracy with respect to traditional fall management methods. Experimental results show the strong detection performance of the proposed solution in discriminating between falls and typical Activities of Daily Living (ADLs) presenting fall-like acceleration patterns.
Starting Page	3727
Ending Page	3730
File Size	658942
Page Count	4
File Format	PDF
ISSN	1557170X
e-ISBN	9781424492718
DOI	10.1109/EMBC.2015.7319203
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-25
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Accelerometers Acceleration Gyroscopes Legged locomotion Support vector machines Senior citizens
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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