TY - GEN
T1 - A neural network based infant monitoring system to facilitate diagnosis of epileptic seizures
AU - Ogura, Yuya
AU - Hayashi, Hideaki
AU - Nakashima, Shota
AU - Soh, Zu
AU - Shibanoki, Taro
AU - Shimatani, Koji
AU - Takeuchi, Akihito
AU - Nakamura, Makoto
AU - Okumura, Akihisa
AU - Kurita, Yuichi
AU - Tsuji, Toshio
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/11/4
Y1 - 2015/11/4
N2 - In this paper, we propose an infant monitoring system that automatically detects epileptic seizures in domestic and hospital environments. The proposed system measures the movements and electroencephalogram (EEG) signals of an infant using a video camera and an electroencephalograph. Seizure features are then extracted from the video images and EEG signals, and the evaluation indices based on medical knowledge are calculated from the features. The system employs a probabilistic neural network for the automatic detection of seizures, thereby allowing the choice/combination of evaluation indices appropriate for the environment via network training. We tested the system in simulated domestic and hospital environments. The validity of the proposed system was reinforced by the results of comparisons with clinical diagnoses.
AB - In this paper, we propose an infant monitoring system that automatically detects epileptic seizures in domestic and hospital environments. The proposed system measures the movements and electroencephalogram (EEG) signals of an infant using a video camera and an electroencephalograph. Seizure features are then extracted from the video images and EEG signals, and the evaluation indices based on medical knowledge are calculated from the features. The system employs a probabilistic neural network for the automatic detection of seizures, thereby allowing the choice/combination of evaluation indices appropriate for the environment via network training. We tested the system in simulated domestic and hospital environments. The validity of the proposed system was reinforced by the results of comparisons with clinical diagnoses.
UR - http://www.scopus.com/inward/record.url?scp=84953331397&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84953331397&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2015.7319665
DO - 10.1109/EMBC.2015.7319665
M3 - Conference contribution
C2 - 26737565
AN - SCOPUS:84953331397
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 5614
EP - 5617
BT - 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
Y2 - 25 August 2015 through 29 August 2015
ER -