Hidden Information Technology and Data Processing in Drowsiness Detection in Normal Adults based on Pulse Signal and ECG Detection in normal adults based on Pulse Signal and ECG

摘要

An objective measurement to evaluate sleep-wake state was studied based on the hidden information among ECG and pulse signals that might offer insights into the nature of sleep. Pulse transit time (FIT) and Wavelet entropy (WE) were computed for twenty sets data which come from self-designed experiments to distinguish the two different states of mental. A significant increase of PTT and decrease of WE ware correlated with the state of drowsiness, and both feature t-test results were p<0.01, thus showing that these features have significant differences between awake and sleepy state. Furthermore, the two characteristics can be recommended as objective indicators for distinguishing the human mental states.