@inproceedings{cf6f7d4399e34561aa46ff37b223df34,
title = "Real-Time Epilepsy Detection with IMU and Low Power Processor Design",
abstract = "In this work, we proposed a system that supplies real-time epilepsy detection system (RED system) with a single inertial measurement unit (IMU) and a low power processing unit. Since the accuracy can reach 99.81%, the specificity can reach 99.81%, and false positive rate of 0.19%, it not only ensures reliability but also provides a quantification analysis for diagnosis. The proposed method has been verified by 60 patients and the processing unit has been implemented into a chip using TSMC 0.18 μm process, which proves the feasibility of mobile device to the RED system.",
keywords = "ASIC, IMU, epilepsy detection, real-time",
author = "Su, {Yu Ju} and Wen, {Kuei Ann} and Cheng, {Mei Yun} and Chang, {Chen Nen}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 14th Biomedical Engineering International Conference, BMEiCON 2022 ; Conference date: 10-11-2022 Through 13-11-2022",
year = "2022",
doi = "10.1109/BMEiCON56653.2022.10012112",
language = "English",
series = "BMEiCON 2022 - 14th Biomedical Engineering International Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "BMEiCON 2022 - 14th Biomedical Engineering International Conference",
address = "United States",
}