Enhanced Fall Detection and Prediction Using Heterogeneous Hidden Markov Models in Indoor Environment

Enhanced Fall Detection and Prediction Using Heterogeneous Hidden Markov Models in Indoor Environment

Falls among the elderly pose a significant risk, often leading to serious injuries and a decline in overall well-being. This study employs an Heterogenous Hidden Markov Model (HHMM) that utilizes 3D vision-based body articulation data to propose an innovative method for fall detection and prediction...

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Bibliographic Details
Main Authors: Oumaima Guendoul, Hamd Ait Abdelali, Youness Tabii, Rachid Oulad Haj Thami, Omar Bourja
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Sensors
fall detection
fall prediction
algorithms
computer vision
artificial intelligence
Online Access:https://ieeexplore.ieee.org/document/10734116/
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https://ieeexplore.ieee.org/document/10734116/

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