Abstract
The number of vehicle accidents due to driver drowsiness continues to increase. Therefore, prompt and effective detection for driver health during driving is crucial to improvement of traffic safety. A set of real-time health detection system built into a smart steering wheel for the driver is proposed in the paper. The driver's health condition (drowsiness) is detected by a developed algorithm by monitoring the driver’s biological signals, including respiration, hand grip force, photoplethysmogram (PPG), and electrocardiogram (ECG). Meanwhile the driver's state of arrhythmia, as a common cardiac disease, can be diagnosed too. The test results indicate that the developed real-time driver health detection system can effectively monitor the state of vigilance and the cardiac state, i.e. arrhythmia, of the driver.
Highlights
The Traffic Accident Analysis Center (2012) reports that the number of traffic accidents caused by driver carelessness has gradually increased
The proposed real-time health detection system applied onto the smart steering wheel is composed of three biological sensors, an interface circuit, a data acquisition board (DAQ), and a personal computer (PC)
The PPG signal is acquired from a PPG sensor, which consists of a light-emitting diode (LED) and a phototransistor (PT) attached to the steering wheel
Summary
The Traffic Accident Analysis Center (2012) reports that the number of traffic accidents caused by driver carelessness has gradually increased. It is significant to detect driver health efficiently and in real time during driving in order to improve of traffic safety. Researchers have developed many methods to monitor driver’s state of vigilance. In this study, considering convenience of monitoring the driver as driving, respiration, hand gripping force, and electrocardiogram (ECG) signals are utilized to detect wake or sleep stages of the driver by analyzing Heart Rate (HR) and Heart Rate Variability (HRV). Driver’s physiological signals were monitored via a smart steering wheel and analyzed to determine driver’s health state. This is the reason why we call the developed steering wheel with acquisition and analysis of driver’s physiological signals as the smart steering wheel.
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