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Your search keyword '"Mayr, Christian"' showing total 5 results
Start Over Author "Mayr, Christian" Journal ieee transactions on biomedical circuits and systems
5 results on '"Mayr, Christian"'

1. A 16-Channel Fully Configurable Neural SoC With 1.52 $\mu$W/Ch Signal Acquisition, 2.79 $\mu$W/Ch Real-Time Spike Classifier, and 1.79 TOPS/W Deep Neural Network Accelerator in 22 nm FDSOI

Author

Zeinolabedin, Seyed Mohammad Ali, primary, Schuffny, Franz Marcus, additional, George, Richard, additional, Kelber, Florian, additional, Bauer, Heiner, additional, Scholze, Stefan, additional, Hanzsche, Stefan, additional, Stolba, Marco, additional, Dixius, Andreas, additional, Ellguth, Georg, additional, Walter, Dennis, additional, Hoppner, Sebastian, additional, and Mayr, Christian, additional

Published
2022
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5. A 16-Channel Fully Configurable Neural SoC With 1.52 μW/Ch Signal Acquisition, 2.79 μW/Ch Real-Time Spike Classifier, and 1.79 TOPS/W Deep Neural Network Accelerator in 22 nm FDSOI.

Author

Zeinolabedin SMA, Schuffny FM, George R, Kelber F, Bauer H, Scholze S, Hanzsche S, Stolba M, Dixius A, Ellguth G, Walter D, Hoppner S, and Mayr C

Subjects
Cyclic N-Oxides, Electrodes, Neural Networks, Computer, Signal Processing, Computer-Assisted
Abstract

With the advent of high-density micro-electrodes arrays, developing neural probes satisfying the real-time and stringent power-efficiency requirements becomes more challenging. A smart neural probe is an essential device in future neuroscientific research and medical applications. To realize such devices, we present a 22 nm FDSOI SoC with complex on-chip real-time data processing and training for neural signal analysis. It consists of a digitally-assisted 16-channel analog front-end with 1.52 μW/Ch, dedicated bio-processing accelerators for spike detection and classification with 2.79 μW/Ch, and a 125 MHz RISC-V CPU, utilizing adaptive body biasing at 0.5 V with a supporting 1.79 TOPS/W MAC array. The proposed SoC shows a proof-of-concept of how to realize a high-level integration of various on-chip accelerators to satisfy the neural probe requirements for modern applications.

Published
2022
Full Text
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