An advanced first aid system has been developed with hybridized fall detection algorithm (FDB-HRT) which includes drones, smartphones, and sensors to remotely monitor heartbeat and risk of fall in the elderly. The device provides urgent first aid via a drone if a fall occurs.
A team of researchers from Iraq and the University of South Australia proposed this advanced first aid system (AFAS) for the elderly in outdoor settings, based on a wireless body-area sensor network (WBSN) to monitor. to monitor and provide first aid to patients prone to falling (such as those with atrial fibrillation). A hybridized algorithm that combines HR measurement and acceleration to detect falls, named “fall detection based on heart rate threshold” (FDB-HRT). The measurement accuracies of the HB sensor and GPS module were validated relative to benchmark systems.
For the validation of the device, five volunteers were invited to evaluate the performance of the heartbeat sensor relative to a benchmark device, and the extracted data was validated using statistical analysis. In addition, the accuracy of fall detections and the recorded locations of fall incidents were validated.
- The proposed FDB-HRT algorithm was 99.16% and 99.2% accurate with regard to heart rate measurement and fall detection, respectively.
- In addition, the geolocation error of patient fall incidents based on a GPS module was evaluated by mean absolute error analysis for 17 different locations in three cities in Iraq.
- Mean absolute error was 1.08 × 10−5° and 2.01 × 10−5° for latitude and longitude data relative to data from the GPS Benchmark system.
- In addition, the results revealed that in urban areas, the UAV succeeded in all missions and arrived at the patient’s locations before the ambulance, with an average time savings of 105 s.
- Moreover, a time saving of 31.81% was achieved when using the UAV to transport a first aid kit to the patient compared to an ambulance.
Summing-up the observation, the authors concluded that when compared to delivering first aid via ambulance, our design greatly reduces delivery time. The proposed advanced first aid system outperformed previous systems presented in the literature in terms of accuracy of heart rate measurement, fall detection, and information messages and UAV arrival time.
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