Real-time Fall Monitoring System for the Elderly Based on Multimodal Sensor Fusion

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Review analyzes multimodal sensor fusion, revealing optimal strategies for fall monitoring in elderly populations.

The three-level attention fusion architecture shows superior performance in complex scenarios for fall monitoring.
Comparative analysis of multimodal sensor strategies highlights the need for effective data fusion architectures.
Current fall monitoring systems face challenges like limited open-source data and lack of night-time solutions.
Future research should focus on integrating Transformer architecture with privacy computing for enhanced monitoring.

Wanning Chen (2025) studied this question.

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