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MulPi: A Multi-Class and Patient-Independent Computing-in-SRAM Seizure Classifier

Publication ,  Conference
Kim, B; Huang, Q; Taylor, B; Zheng, Q; Ku, J; Ramos, N; Yeats, E; Chen, Y; Li, HR
Published in: 2024 IEEE Biomedical Circuits and Systems Conference, BioCAS 2024
January 1, 2024

Authentic detection and prediction of seizures require 1) multi-class (Mul) and 2) patient-independent (Pi) classification. Recent implementable chips for seizure classification rarely satisfy the two requirements due to restricted resources in small chips; therefore, high efficiency is imperative along with accuracy. This paper introduces an efficient MulPi chip, fabricated for the first time to simultaneously fulfill multiclass and patient independence, based on a co-design approach. We develop a 5-layer convolutional neural network (CNN), MulPiCNN, with advanced training techniques for lightness and accuracy. At the hardware level, our SRAM-based chip leverages computing-in-memory (CIM) for efficiency. The fabricated MulPi chip is distinguished from prior CIMs in two folds, namely ISRWCIM: a) input-stationary (IS) CIM for resource-saving, and b) row-wise (RW) computing to address a challenge of SRAM CIM, empowered by our novel 2T-Hadamard product unit (HPU). MulPi outperforms state-of-the-art chips with 98.5% sensitivity and 99.2% specificity, classifying in 0.12 s and 0.348 mm2

Duke Scholars

Published In

2024 IEEE Biomedical Circuits and Systems Conference, BioCAS 2024

DOI

Publication Date

January 1, 2024
 

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Kim, B., Huang, Q., Taylor, B., Zheng, Q., Ku, J., Ramos, N., … Li, H. R. (2024). MulPi: A Multi-Class and Patient-Independent Computing-in-SRAM Seizure Classifier. In 2024 IEEE Biomedical Circuits and Systems Conference, BioCAS 2024. https://doi.org/10.1109/BioCAS61083.2024.10798153
Kim, B., Q. Huang, B. Taylor, Q. Zheng, J. Ku, N. Ramos, E. Yeats, Y. Chen, and H. R. Li. “MulPi: A Multi-Class and Patient-Independent Computing-in-SRAM Seizure Classifier.” In 2024 IEEE Biomedical Circuits and Systems Conference, BioCAS 2024, 2024. https://doi.org/10.1109/BioCAS61083.2024.10798153.
Kim B, Huang Q, Taylor B, Zheng Q, Ku J, Ramos N, et al. MulPi: A Multi-Class and Patient-Independent Computing-in-SRAM Seizure Classifier. In: 2024 IEEE Biomedical Circuits and Systems Conference, BioCAS 2024. 2024.
Kim, B., et al. “MulPi: A Multi-Class and Patient-Independent Computing-in-SRAM Seizure Classifier.” 2024 IEEE Biomedical Circuits and Systems Conference, BioCAS 2024, 2024. Scopus, doi:10.1109/BioCAS61083.2024.10798153.
Kim B, Huang Q, Taylor B, Zheng Q, Ku J, Ramos N, Yeats E, Chen Y, Li HR. MulPi: A Multi-Class and Patient-Independent Computing-in-SRAM Seizure Classifier. 2024 IEEE Biomedical Circuits and Systems Conference, BioCAS 2024. 2024.

Published In

2024 IEEE Biomedical Circuits and Systems Conference, BioCAS 2024

DOI

Publication Date

January 1, 2024