Evaluation of fall detection by computer vision and radar
DOI:
https://doi.org/10.17979/ja-cea.2025.46.12069Keywords:
Visión por computador, Aprendizaje Profundo, Sensores y actuadores inteligentes, Robots móvil, Detección de caídasAbstract
Falls are the most frequent accident among the elderly and, when they occur at home, nearly 70% of those who fall are unable to get up on their own or seek help immediately. Therefore, automatic fall detection systems are essential to ensure a rapid response, reduce inattention time and improve the quality of life of the elderly. This study compares two approaches for detection in the home environment: a fixed radar system, evaluated in different configurations, and a computer vision-based detector integrated into a mobile robot, whose mobility allows it to cover blind areas without the need for prior calibration. Both systems were tested under controlled conditions, simulating five types of fall in four different locations. This paper presents the results obtained after experimentation, as well as the most suitable contexts for the application of each detection system.
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Copyright (c) 2025 Celia Sánchez-Girón, Jaime Duque-Domingo, Jaime Gómez-García-Bermejo, Eduardo Zalama
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
