TY - JOUR
T1 - Artificial neural networks based sleep motion recognition using night vision cameras
AU - Kuo, Chung Hsien
AU - Yang, Fang Chung
AU - Tsai, Ming Yuan
AU - Lee, Ming Yih
PY - 2004/4/25
Y1 - 2004/4/25
N2 - The body 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 body positions and the body 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 body position 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 body direction. Finally, the implementations and the practical results of this work are all illustrated in this paper.
AB - The body 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 body positions and the body 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 body position 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 body direction. Finally, the implementations and the practical results of this work are all illustrated in this paper.
KW - Artificial neural network
KW - Machine vision
KW - Sleep motion recognition
KW - Sleep quality evaluation
UR - http://www.scopus.com/inward/record.url?scp=2942711815&partnerID=8YFLogxK
U2 - 10.4015/S101623720400013X
DO - 10.4015/S101623720400013X
M3 - 文章
AN - SCOPUS:2942711815
SN - 1016-2372
VL - 16
SP - 79
EP - 86
JO - Biomedical Engineering - Applications, Basis and Communications
JF - Biomedical Engineering - Applications, Basis and Communications
IS - 2
ER -