A Hybrid Analysis Approach of Physiological Signals Based on Excessive Sleepiness and Distraction State Detection

The early detection of sleepiness is vital to the research of sleep since physiological signals are the most accurate source of measurements for this purpose. The goal of this research is to create a system that can identify sleepiness and distraction that is both more accurate and effective than the current traditional sleepiness detection devices, which are either unreliable, expensive, or uncomfortable for the driver. Since physiological signals like electroencephalography (EEG) and electrocardiography (ECG) contain characteristics of various mental and physical states that can be accurately interpreted using certain parameters, the excessive sleepiness and distraction detection method used in this study is based on the combination of these signals in order to improve detection performance and help reduce traffic accidents. Overall, the LabVIEW simulation findings are highly significant and show that the suggested approach can be a dependable solution for a practical drowsy and distracted driving detection system that is both accurate and easy to wear.