TY - GEN
T1 - A robust and fast seizure detector for IoT edge
AU - Sayeed, Md Abu
AU - Mohanty, Saraju P.
AU - Kougianos, Elias
AU - Yanambaka, Venkata Prasanath
AU - Zaveri, Hitten
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Epilepsy is a neurological disorder which has negative impact on human life quality. Epilepsy affects almost 1% of the world population necessitating a unified system for fast seizure detection as well as remote health monitoring to enhance the daily lives of the epilepsy patients. We envision a smart seizure detection framework in the edge of the Internet of Things (IoT) which is capable of detecting seizures as well as monitoring the patient's healthcare activity remotely. Detection of seizure is performed using the discrete wavelet transform, statistical feature extraction, and a naive Bayes (NB) classifier. The proposed system was implemented and validated using Simulink, ThingSpeak, and off-the-shelf microcontrollers. Experimental results show that the proposed system reduces latency by 44% compared to a cloud-IoT based system and reports a classification accuracy of 98.65%.
AB - Epilepsy is a neurological disorder which has negative impact on human life quality. Epilepsy affects almost 1% of the world population necessitating a unified system for fast seizure detection as well as remote health monitoring to enhance the daily lives of the epilepsy patients. We envision a smart seizure detection framework in the edge of the Internet of Things (IoT) which is capable of detecting seizures as well as monitoring the patient's healthcare activity remotely. Detection of seizure is performed using the discrete wavelet transform, statistical feature extraction, and a naive Bayes (NB) classifier. The proposed system was implemented and validated using Simulink, ThingSpeak, and off-the-shelf microcontrollers. Experimental results show that the proposed system reduces latency by 44% compared to a cloud-IoT based system and reports a classification accuracy of 98.65%.
KW - Electroencephalogram (EEG)
KW - Epilepsy
KW - Feature Extraction
KW - IoT
KW - Naive Bayes Classifier
KW - Seizure Detection
UR - http://www.scopus.com/inward/record.url?scp=85067110392&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85067110392&partnerID=8YFLogxK
U2 - 10.1109/iSES.2018.00042
DO - 10.1109/iSES.2018.00042
M3 - Conference contribution
AN - SCOPUS:85067110392
T3 - Proceedings - 2018 IEEE 4th International Symposium on Smart Electronic Systems, iSES 2018
SP - 156
EP - 160
BT - Proceedings - 2018 IEEE 4th International Symposium on Smart Electronic Systems, iSES 2018
T2 - 4th IEEE International Symposium on Smart Electronic Systems, iSES 2018
Y2 - 17 December 2018 through 19 December 2018
ER -