An Advanced First Aid System Based on an Unmanned Aerial Vehicles and a Wireless Body Area Sensor Network for Elderly...

Area of Science:

• Gerontology
• Biomedical Engineering
• Emergency Medicine

Background:

• Falls pose significant risks to elderly individuals, especially those with heart conditions.
• Current emergency response systems may face delays in reaching patients, impacting outcomes.

Purpose of the Study:

• To develop and evaluate an advanced first aid system for monitoring elderly patients at risk of falling.
• To utilize an unmanned aerial vehicle (UAV) for rapid delivery of first aid supplies.
• To propose a hybridized fall detection algorithm (FDB-HRT) integrating acceleration and heart rate data.

Main Methods:

• A hybridized fall detection algorithm (FDB-HRT) combining acceleration and heart rate threshold was developed.
• Heartbeat sensor performance was evaluated against a benchmark device with statistical validation.
• Accuracy of fall detection and geolocation of incidents were validated using a GPS module.
• UAV mission performance, including arrival time and time savings, was compared to ambulance response.

Main Results:

• The FDB-HRT algorithm achieved 99.16% accuracy for heart rate measurement and 99.2% for fall detection.
• Geolocation error for fall incidents was minimal (mean absolute error of 1.08 × 10^-5° latitude, 2.01 × 10^-5° longitude).
• UAVs arrived at patient locations faster than ambulances in urban areas, saving an average of 105 seconds.
• A 31.81% time saving was achieved in transporting first aid kits via UAV compared to ambulances.

Conclusions:

• The proposed advanced first aid system significantly reduces delivery time for emergency supplies compared to traditional ambulance services.
• The system demonstrates superior accuracy in heart rate measurement and fall detection.
• The UAV-based approach offers a faster and more efficient emergency response for elderly patients prone to falls and with heart conditions.