A method of posture monitoring and falling detection based on physiological and behavioral characteristics of the elderly

Shiyun Zhou; Zhijia Yang; Yuxuan Mao; Haisong Tang; Yanchen Liu; Xiaozheng Liu; Liquan Dong

doi:10.1117/12.2550263

12 March 2020 A method of posture monitoring and falling detection based on physiological and behavioral characteristics of the elderly

Shiyun Zhou, Zhijia Yang, Yuxuan Mao, Haisong Tang, Yanchen Liu, Xiaozheng Liu, Liquan Dong

Author Affiliations +

Proceedings Volume 11434, 2019 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments; 114341I (2020) https://doi.org/10.1117/12.2550263
Event: 2019 International Conference on Optical Instruments and Technology, 2019, Beijing, China

Abstract

At present, the problem of population aging has become a hot spot of international concern, especially in China, and the international community urgently needs a universally applicable health care system for the elderly. Recent research shows that falling is the biggest threat to the health of the elderly. Based on thihe physiological and behavioral characteristics of the elderly, the paper discusses an algorithm for the recognition of motion state and fall detection of elderly applied to wearable devices to ensure timely rescue after a fall. The algorithm continuously acquires acceleration information during the movement of the elderly through a six-axis acceleration sensor. Firstly, the acceleration data is filtered, then the combined acceleration is calculated, and multiple features of the continuous data are extracted, and then the softmax method is used to classify the different motion states to realize the alarm of the fall. The algorithm extracts the feature vector by the magnitude of the combined acceleration, which solves the problem that the single acceleration in the traditional algorithm must solves the coordinate axis, which may waste much calculating time. The algorithm is validated by using the existing data set, and the accuracy of the algorithm is up to 89%. It is an effective way to detect falls.

Citation Download Citation

Shiyun Zhou, Zhijia Yang, Yuxuan Mao, Haisong Tang, Yanchen Liu, Xiaozheng Liu, and Liquan Dong "A method of posture monitoring and falling detection based on physiological and behavioral characteristics of the elderly", Proc. SPIE 11434, 2019 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments, 114341I (12 March 2020); https://doi.org/10.1117/12.2550263

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
13 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Detection and tracking algorithms

Sensors

Data acquisition

Data modeling

Digital filtering

Video surveillance

Gesture recognition

Show All Keywords

Keywords/Phrases

Search In:

Publication Years