Correlation analysis between drowsiness and heart rate variability parameters

Abstract

Electrocardiography (ECG) is an important physiological signal that reflects the autonomic nervous system (ANS) activity. The correlation between ANS measures and sleepiness has been used to assess the drowsiness of a person from spectral analysis of heart rate variability (HRV). Power spectral analysis of HRV derived from RR interval time series gives three frequency bands, namely very low frequency band (0.003-0.04 Hz), low frequency band (0.04-0.15 Hz) and high frequency band (0.15-0.4 Hz). Drowsiness has an adverse effect on the reaction time, alertness and concentration level of vehicle driver that can reduce driver performance. Surveys suggest that driver fatigue is one of the main causes of road accidents, contributing up to 20% of all road accidents. Researches have shown that bio-signals like electrocardiography, electroencephalography, blood pressure, etc. are affected by the mental state of the individual, and thus, these physiological signals can be used to assess the mental state of individuals. Hence, it is possible to make a system to monitor the driver drowsiness based on bio-signal. Recording EEG and EOG involves attaching electrodes on the head which is not comfortable, and may cause distraction to the driver. ECG is thus a better choice as it is possible to set up non-intrusively by placing electrically conductive fabric on the steering wheel and driver seat as electrodes. Non-contact electrodes have also been tested. Low frequency band power spectrum is related with sympathetic and parasympathetic activity of ANS, whereas high frequency band power spectrum is related with parasympathetic activity of ANS. The sympathetic nervous system signals the body to be in a more alert state whereas the parasympathetic nervous system signals the body to be in a more relaxed state. The objective of this paper is to analyze the changes in spectral components of HRV when one becomes drowsy and detect drowsiness.