A novel sleep/wake identification method with video analysis

Automatic sleep pattern analysis has been a very important research issue for the diagnosis in sleep medicine. This paper proposes a nonintrusive sleep/wake identification method based on computer vision approach to extract visual sleep activity and sleep/wake patterns. This approach is robust to noise, contrast and illumination variations of infrared videos. The proposed method extracts body motion context by illumination compensation and background subtraction algorithms, and sleep status is recognized by linear regression of body motion context. Experiments are conducted on the video polysomnography data from 18 persons recorded in sleep laboratory. The sleep/wake status identified from the infrared videos is verified with the ground truth that is scored by a sleep technician from the polysomnography data according to standard medical operation. High accuracy of the experiments demonstrates the validity of the proposed method.

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