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Updated: Oct 17, 2025

Design and Analysis for Fall Detection System Simplification

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

A Hierarchical Approach to Activity Recognition and Fall Detection Using Wavelets and Adaptive Pooling.

Abbas Shah Syed¹, Daniel Sierra-Sosa², Anup Kumar¹

¹Department of Computer Science and Engineering, University of Louisville, Louisville, KY 40208, USA.

Sensors (Basel, Switzerland)

|October 13, 2021

Summary

This summary is machine-generated.

This study introduces a new wavelet and adaptive pooling framework for human activity recognition and fall detection using inertial sensors. The system achieved a 94.67% F1 score, offering a computationally efficient solution for real-time applications.

Failed At:

2026-06-19T13:39:12.445358+00:00

Keywords:

Internet of Things (IoT)activity recognition artificial intelligence cyber physical systems direction and severity fall detection smart health

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