Viability of Cardiac Parameters Measured Unobtrusively Using Capacitive Coupled Electrocardiography (cECG) to Estimate Driver Performance

Abstract

A non-contact capacitive coupled electrocardiography (cECG) system to estimate driver’s fatigue is presented in this paper. Twenty male volunteers participated in this paper on a high fidelity driving simulator. To validate the cECG system, we have correlated it with conventional single lead ECG systems. Effect of perspiration on the cECG signal was also observed. Heart dynamics based on Poincare plot was estimated to observe fatigue. Magnitude square coherence analysis provided good coherence between conventional ECG and cECG signals whereas, signal quality of the cECG signals was observed better as time progressed probably due to effect of perspiration. Significant change (p < 0.05) in HRV dynamics and frequency measure of cECG signals was observed during course of driving. Correlation coefficients between non-linear indices of HRV (SD1, SD2, and SD1/SD2) and frequency measure indices of HRV (LF, HF, and LF/HF) were tested by the Spearman rank correlation test. Result from non-linear and frequency indices analysis of HRV showed significant change (p < 0.05) during course of simulated driving. Validation of cECG with conventional ECG will be very helpful in considering cECG as a good replacement of conventional ECG to detect non-contact ubiquitous driver performance monitoring.