A Self-Aware Power Management Model for Epileptic Seizure Systems Based on Patient-Specific Daily Seizure Pattern

We analyze and compare various hardware-based epileptic seizure systems and discuss the challenges and opportunities for reducing power consumption and increasing the battery lifetime. Furthermore, we propose a power management model that employs patient-specific seizure patterns to manage the power...

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Bibliographic Details
Main Authors: Varnosfaderani, Shiva Maleki, Rahman, Rihat, Sarhan, Nabil J., Alhawari, Mohammad
Format: Conference Proceeding
Language:English
Subjects:
Deep learning
energy efficiency
epileptic seizure monitoring
patient-specific daily seizure pattern
self-aware power management model
Online Access:Request full text
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Description
Summary:We analyze and compare various hardware-based epileptic seizure systems and discuss the challenges and opportunities for reducing power consumption and increasing the battery lifetime. Furthermore, we propose a power management model that employs patient-specific seizure patterns to manage the power consumption of the overall system. This model determines the patient-specific seizure pattern and switches the system to sleep mode when the likelihood of seizure occurrence is zero or very low. Our analysis shows that our proposed power management model could effectively reduce the power consumption by 49\% compared to the complex model while the performance reduction is less than 1\%.
ISSN:2159-1679
DOI:10.1109/ICM60448.2023.10378881