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A Comparative Overview of Technological Advances in Fall Detection Systems for Elderly People
Omar Flor-Unda1, Rafael Arcos-Reina2, Cristina Estrella-Caicedo3
1Ingeniería Industrial, Facultad de Ingeniería y Ciencias Aplicadas, Universidad de las Américas, Quito 170125, Ecuador.
Sensors (Basel, Switzerland)
|December 31, 2025
Summary
Technological advancements in fall detection systems for older adults are crucial for remote monitoring and safety. Combining image analysis with AI and IoT offers superior accuracy and real-time decision-making for improved quality of life.
Area of Science:
- Gerontology and Health Technology
- Artificial Intelligence in Healthcare
- Internet of Things (IoT) for Elderly Care
Background:
- Global population is aging, with older adults projected to be 35% of the population in industrialized countries by 2050.
- This demographic shift necessitates technological solutions for remote monitoring and automatic risk alarm activation to enhance the quality of life for seniors.
- Fall detection systems are vital for ensuring the safety and independence of the elderly population.
Purpose of the Study:
- To conduct a scoping review of technological solutions for detecting falls in older adults developed over the last decade.
- To describe the operational principles, effectiveness, advantages, limitations, and future trends of these fall detection technologies.
- To identify leading technological approaches for fall detection in the elderly population.
Main Methods:
- Scoping review conducted under the PRISMA methodology.
- Literature search across major scientific databases: SCOPUS, ScienceDirect, Web of Science, PubMed, IEEE Xplore, and Taylor & Francis.
- Analysis of technological solutions focusing on principles of operation, effectiveness, and limitations.
Main Results:
- Inertial systems utilizing accelerometers and gyroscopes are predominant due to low cost and availability.
- Approaches combining image analysis with artificial intelligence (AI) and machine learning (ML) algorithms demonstrate superior accuracy and robustness.
- Multisensory solutions based on IoT technologies are advancing, integrating diverse data sources for optimized real-time decision-making.
Conclusions:
- While inertial systems are common, AI-powered image analysis offers higher performance in fall detection.
- IoT-based multisensory systems represent a promising future trend for integrated and intelligent elderly care solutions.
- Continued technological development in fall detection is essential to support the growing aging population and improve their quality of life.
