Application of heart rate variability analysis to electrocardiogram recorded outside the driver's awareness from an automobile steering wheel

Abstract

Background: Approximately 5% of motor vehicle deaths are assumed to be occur because of a cardiac event thought to be triggered by multiple factors. One important factor is an imbalance of sympathetic and parasympathetic nervous activities, which can be measured by analyzing heart rate variability (HRV). Therefore, a system has been developed to make electrocardiographic (ECG) recordings outside the driver's awareness from the steering wheel (steering-ECG) with an algorithm to remove noise. Methods and Results: Steering-ECG and ECG from a chest lead (chest-ECG) were recorded simultaneously in 10 normal subjects while they were driving for 90 min. For each of 4 parameters (instantaneous heart rate, low-and high-frequency components of HRV, and the ratio of these components in all subjects), mutual information was used to examine whether the fluctuation from the steering-ECG resembled that from the chest-ECG. The mutual information of each parameter was larger than 0.047 with 95% confidence interval (mutual information values vary from 0 to 1; threshold of significance: 0.047). Hence, the fluctuation of each steering-ECG parameter resembled its chest-ECG counterpart. Conclusions: This system heralds a new driver-safety strategy by reporting alteration of autonomic nervous activity during driving.