1. 68-channel neural signal processing system-on-chip with integrated feature extraction, compression, and hardware accelerators for neuroprosthetics in 22 nm FDSOI.
- Author
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Guo L, Weiße A, Zeinolabedin SMA, Schüffny FM, Stolba M, Ma Q, Wang Z, Scholze S, Dixius A, Berthel M, Partzsch J, Walter D, Ellguth G, Höppner S, George R, and Mayr C
- Abstract
Introduction: Multi-channel electrophysiology systems for recording of neuronal activity face significant data throughput limitations, hampering real-time, data-informed experiments. These limitations impact both experimental neurobiology research and next-generation neuroprosthetics., Methods: We present a novel solution that leverages the high integration density of 22nm fully-depleted silicon-on-insulator technology to address these challenges. The proposed highly integrated programmable System-on-Chip (SoC) comprises 68-channel 0.41 μW/Ch recording frontends, spike detectors, 16-channel 0.87-4.39 μW/Ch action potentials and 8-channel 0.32 μW/Ch local field potential codecs, as well as a multiply-accumulate-assisted power-efficient processor operating at 25 MHz (5.19 μW/MHz). The system supports on-chip training processes for compression, training, and inference for neural spike sorting. The spike sorting achieves an average accuracy of 91.48 or 94.12% depending on the utilized features. The proposed programmable SoC is optimized for reduced area (9 mm
2 ) and power. On-chip processing and compression capabilities free up the data bottlenecks in data transmission (up to 91% space saving ratio), and moreover enable a fully autonomous yet flexible processor-driven operation., Discussion: Combined, these design considerations overcome data-bottlenecks by allowing on-chip feature extraction and subsequent compression., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Guo, Weiße, Zeinolabedin, Schüffny, Stolba, Ma, Wang, Scholze, Dixius, Berthel, Partzsch, Walter, Ellguth, Höppner, George and Mayr.)- Published
- 2024
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