Embedded DSP-based telehealth radar system for remote in-door fall detection

Area of Science:

• * Digital Health
• * Biomedical Engineering
• * Geriatric Care Technology

Background:

• * Growing need for remote patient monitoring to support independent living for the elderly.
• * Limitations of existing telehealth systems in real-time emergency detection.
• * Importance of reliable fall detection for preventing serious health consequences.

Purpose of the Study:

• * To introduce and evaluate an embedded telehealth system for continuous, automatic, and remote fall emergency detection.
• * To demonstrate a cost-effective and efficient healthcare solution for elderly well-being.
• * To detail the system's hardware and software implementation for real-time monitoring.

Main Methods:

• * Development of an embedded telehealth system comprising a radar sensor and base station.
• * Implementation of a fall detection algorithm utilizing least-square support vector machines (LS-SVM) processed via a digital signal processor.
• * Validation through experimental tests involving 65 mimicked fall incidents with 16 subjects under controlled conditions.

Main Results:

• * The proposed telehealth system demonstrated 100% sensitivity in detecting simulated fall events in real time.
• * The system achieved zero false positives during experimental validation.
• * Successful real-time monitoring was achieved under conditions without signal power, coverage, or obstacle limitations.

Conclusions:

• * The embedded radar-based telehealth system is a highly effective solution for real-time fall detection.
• * The system offers a reliable and accurate method for remote monitoring, enhancing elderly care.
• * This technology supports independent living by providing continuous safety and emergency detection.