Image-based sleep motion recognition using artificial neural networks

Abstract

The movement is one of the most important factors to evaluate the sleep quality. In general, the sleep motion is hardly investigated, and it must take a long time to observe the motion of the patient in terms of a pre-recoded video storage media with high speed playing. This paper proposes an image-based solution to recognize the sleep motions. We use the contact free and IR-based night vision camera to capture the video frames during the sleep of the patient. The video frames are used to recognize the orientations and the directions such as the body up, body down, body right, and body left. In addition to the image processing, the proposed artificial neural network (ANN) sleep motion recognition solution is composed of two neural networks. These two neural networks are organized as in a cascade configuration. The first ANN model is used to identify the orientation features from the images; and the follower ANN model is constructed based on the features that are identified by the first ANN model to recognize the direction. Finally, the implementations and the practical results of this work are all illustrated in this paper.