TY - GEN
T1 - An Edge-computing Platform for Low-Latency and Low-power Wearable Medical Devices for Epilepsy
AU - Sayeed, Md Abu
AU - Nasrin, Fatahia
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Epilepsy is a neurological disorder that affects 1% of people globally. The development of a portable, low-power, and low-latency wearable sensor is a growing need to address epilepsy. An edge-computing-based wearable sensor has been presented that uses a pulse exclusion mechanism (PEM) and a random forest classifier to identify seizures at a reduced delay and minimal power consumption. Datasets recorded from the scalp electrode are utilized to demonstrate the feasibility of using the method as a wearable medical device. Including the edge-IoT platform in place of cloud IoT offers a considerable reduction in system latency. The optimized edge-computing platform reduces power usage significantly compared to existing methods. The reduced latency and battery usage make the proposed device faster and more energy-efficient, which may be useful for low-power wearable devices.
AB - Epilepsy is a neurological disorder that affects 1% of people globally. The development of a portable, low-power, and low-latency wearable sensor is a growing need to address epilepsy. An edge-computing-based wearable sensor has been presented that uses a pulse exclusion mechanism (PEM) and a random forest classifier to identify seizures at a reduced delay and minimal power consumption. Datasets recorded from the scalp electrode are utilized to demonstrate the feasibility of using the method as a wearable medical device. Including the edge-IoT platform in place of cloud IoT offers a considerable reduction in system latency. The optimized edge-computing platform reduces power usage significantly compared to existing methods. The reduced latency and battery usage make the proposed device faster and more energy-efficient, which may be useful for low-power wearable devices.
KW - Edge-computing
KW - Electroencephalography (EEG)
KW - Feature Reduction
KW - Internet of Things (IoT)
KW - Wearable Device
UR - http://www.scopus.com/inward/record.url?scp=85168764129&partnerID=8YFLogxK
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U2 - 10.1109/WMCS58822.2023.10194265
DO - 10.1109/WMCS58822.2023.10194265
M3 - Conference contribution
AN - SCOPUS:85168764129
T3 - Proceedings of the 2023 IEEE Texas Symposium on Wireless and Microwave Circuits and Systems, WMCS 2023
BT - Proceedings of the 2023 IEEE Texas Symposium on Wireless and Microwave Circuits and Systems, WMCS 2023
T2 - 2023 IEEE Texas Symposium on Wireless and Microwave Circuits and Systems, WMCS 2023
Y2 - 19 April 2023 through 20 April 2023
ER -