Real-Time ECG-Based Detection of Fatigue Driving Using Sample Entropy

Real-Time ECG-Based Detection of Fatigue Driving Using Sample Entropy

In present work, the heart rate variability (HRV) characteristics, calculated by sample entropy (SampEn), were used to analyze the driving fatigue state at successive driving stages. Combined with the relative power spectrum ratio β/(θ + α), subjective questionnaire, and brain network parameters of electroencephalogram (EEG) signals, the relationships between the different characteristics for d...

Real-Time Head Detection with Kinect for Driving Fatigue Detection

Having found the contour of each region, we can use any ellipse fitting algorithm to fit an ellipse for the contour points. We calculate fitness for each region using the formula below (less fitness value means higher fitness degree): ∑n i=1 δi n · h (1) In conclusion, we calculate the normalized average offset of every contour points. After we get the fitness of each region. We return the regi...

Real-Time EEG-Based Detection of Fatigue Driving Danger for Accident Prediction

This paper proposes a real-time electroencephalogram (EEG)-based detection method of the potential danger during fatigue driving. To determine driver fatigue in real time, wavelet entropy with a sliding window and pulse coupled neural network (PCNN) were used to process the EEG signals in the visual area (the main information input route). To detect the fatigue danger, the neural mechanism of d...

Towards Real-Time Affect Detection Based on Sample Entropy Analysis of Expressive Gesture

Aiming at providing a solid foundation to the creation of future affect detection applications in HCI, we propose to analyze human expressive gesture by computing movement Sample Entropy (SampEn). This method provides two main advantages: (i) it is adapted to the non-linearity and non-stationarity of human movement; (ii) it allows a fine-grain analysis of the information encoded in the movement...

Detection of Congenital Mullerian Anomalies Using Real-Time 3D Sonography