Title :
21.8 A 16-ch patient-specific seizure onset and termination detection SoC with machine-learning and voltage-mode transcranial stimulation
Author :
Bin Altaf, Muhammad Awais ; Chen Zhang ; Yoo, Jerald
Author_Institution :
Masdar Inst. of Sci. & Technol., Abu Dhabi, United Arab Emirates
Abstract :
Multichannel EEG seizure detection SoCs are widely used in medical practice and in research [1]-[3]. Due to huge variation in seizure patterns, patient-specific seizure detection is very crucial. [1], [2] presents 8-channel (ch) SoCs with moderate latency (~2s) but without seizure termination detection and stimulation. [3] implements a closed-loop SoC but is not patient-specific, and moreover, is invasive. This paper presents an ultra-low power 16-ch "non-invasive, patient-specific" seizure onset and termination detection SoC with channels multiplexing AFE and pulsating voltage transcranial electrical stimulation (PVTES).
Keywords :
electroencephalography; learning (artificial intelligence); medical signal detection; medical signal processing; PVTES; SoC termination detection; closed-loop SoC; machine-learning; multichannel EEG seizure detection; patient-specific seizure detection; pulsating voltage transcranial electrical stimulation; ultralow power 16-ch noninvasive patient-specific seizure onset; voltage-mode transcranial stimulation; Band-pass filters; Electroencephalography; Impedance; Iron; Multiplexing; System-on-chip; Training;
Conference_Titel :
Solid- State Circuits Conference - (ISSCC), 2015 IEEE International
Conference_Location :
San Francisco, CA
Print_ISBN :
978-1-4799-6223-5
DOI :
10.1109/ISSCC.2015.7063092