Analysis and Quantification of Physical Fatigue in Automobile Drivers: A Biomedical Approach

Abstract

Vehicular accidents from fatigue due to sleep-deprived driving are rapidly increasing among heavy vehicle drivers. Consequently, a critical analysis of drivers’ fatigue in real time, using established clinical parameters, and subsequent scoring is of dire need in automobile sector. Such a scoring system would be helpful in validating the fatigue detecting devices based on non-contact features that can be installed onboard. Therefore, this study aimed to analyze and quantify physical fatigue during sleep-deprived simulated driving and their utility in developing objective score for fatigue assessment. The genesis and progression of physical fatigue was also analyzed in apparently healthy and pathological condition such as tauopathy. In the first set of experiments, the behavioral changes, cognition and motor performance in response to induced fatigue was analyzed in αCAMK-II-4R tau (transgenic/Tg) mice model of tautopathy (n=24) and were compared with those of wild-type mice (n =24). The mice were subjected to Accelerated Rotarod Test (ART), Open Field Test (OFT), Elevated Plus Maze Test (EPMT), Light and Dark Transition Test (LDT) and Forced Swimming Test (FST) for a comprehensive motor and cognitive performance analysis. Results showed that, genesis and progress of fatigue followed similar trend under physiological condition and pathological condition like tauopathy although the signs and symptoms of physical fatigue in mice models of tauopathy were more pronounced compared to healthy ones. Thus, a fatigue score system developed on healthy individuals may also be applied on pathological conditions that make the subjects vulnerable to fatigue. Subsequently, to quantify the manifestations of physical fatigue, twelve seasoned drivers were subjected to simulated driving session for 30 h and electroencephalogram (EEG),electrocardiogram (ECG) and spirometer recordings were taken for each individual at 3h intervals. In addition, peripheral blood samples were collected and analyzed at 8 h intervals for random blood sugar (RBS), blood urea (BUN) and serum creatinine. Results revealed that, energy and entropy features of EEG showed significant discrimination across time points in α and θ-bands at Cz electrode. The power spectrum density of HF (high frequency) components of ECG decreased with advancing stress and fatigue indicating sympathetic predominance with severity in fatigue. Spirometer recording confirmed gradual decrease in FEV1/FVC ratio (Forced Expiratory Volume at 1stsec / Forced Vital Capacity) as fatigue progressed. On the other hand, all blood biomarkers increased with the progress of fatigue but RBS and creatinine showed better discrimination across time-points.....