Implementation of a real-time fall detection system based on hybrid threshold analysis algorithm and machine learning algorithm-Reference-Cited by-同舟云学术

Implementation of a real-time fall detection system based on hybrid threshold analysis algorithm and machine learning algorithm

Published:2022-07-11 Issue: Volume: Page:
ISSN:
Container-title:2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Xu Yangjin¹,He Zhiyi¹,Zhang Xiangxin²,Li Denghui¹,Li Renbo¹,Ni Weiming¹

Affiliation:

1. School of Information Science and Technology, Fudan University,Department of Communication Science and Engineering,Shanghai,China,200438

2. Shanghai Internet of Things Co LTD (SHIOTC),Research and Development Department,Shanghai,China,200042

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9870821/9870822/09871342.pdf?arnumber=9871342

Reference23 articles.

1. Implementation of a Real-Time Human Movement Classifier Using a Triaxial Accelerometer for Ambulatory Monitoring

2. The development of an accelerometer and gyroscope based sensor to distinguish between activities of daily living and fall-events;bourke;IFMBE Proc,0

3. Distinguishing fall activities from normal activities by angular rate characteristics and high-speed camera characterization

4. Fall-detection solution for mobile platforms using accelerometer and gyroscope data

5. Fall detection algorithms for real-world falls harvested from lumbar sensors in the elderly population: A machine learning approach

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1. PIPTO: Precise Inertial-Based Pipeline for Threshold-Based Fall Detection Using Three-Axis Accelerometers;Sensors;2023-09-18