Towards an Accelerometer-Based Elderly Fall Detection System Using Cross-Disciplinary Time Series Features

Towards an Accelerometer-Based Elderly Fall Detection System Using Cross-Disciplinary Time Series Features

Fall causes trauma or critical injury among the geriatric population which is a second leading accidental cause of post-injury mortality around the world. It is crucial to keep elderly people under supervision by ensuring proper privacy and comfort. Thus the elderly fall detection and prediction usi...

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Bibliographic Details
Main Authors: Md. Jaber Al Nahian, Tapotosh Ghosh, Md. Hasan Al Banna, Mohammed A. Aseeri, Mohammed Nasir Uddin, Muhammad Raisuddin Ahmed, Mufti Mahmud, M. Shamim Kaiser
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Machine learning
feature selection
activities of daily living
feature extraction
signal magnitude vector
Online Access:https://ieeexplore.ieee.org/document/9344695/

Internet

https://ieeexplore.ieee.org/document/9344695/

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