An Implantable Neuromorphic Sensing System Featuring Near-Sensor Computation and Send-on-Delta Transmission for Wireless Neural Sensing of Peripheral Nerves

IEEE Journal of Solid-State Circuits(2022)

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摘要
This article presents a bioinspired, event-driven neuromorphic sensing system (NSS) capable of performing on-chip feature extraction and “send-on-delta” pulse-based transmission, targeting peripheral nerve neural recording applications. The proposed NSS employs event-based sampling which, by leveraging the sparse nature of electroneurogram (ENG) signals, achieves a data compression ratio of $> 125\times $ , while maintaining a low normalized rms error (NRMSE) of 4% after reconstruction. The proposed NSS consists of three sub-circuits. A clockless level-crossing (LC) analog-to-digital converter (ADC) with background offset calibration has been employed to reduce the data rate, while maintaining a high signal to quantization noise ratio (SQNR). A fully synthesized spiking neural network (SNN) extracts temporal features of compound action potential (CAP) signals and consumes only 13 $\mu \text{W}$ . An event-driven, pulse-based body channel communication (Pulse-BCC) with serialized address-event representation (AER) encoding schemes minimizes transmission energy and form factor. The prototype is fabricated in 40-nm CMOS occupying a 0.32-mm 2 active area and consumes in total 28.2 and 50 $\mu \text{W}$ power in feature extraction and full diagnosis mode, respectively. The presented NSS also extracts temporal features of CAP signals with 10- $\mu \text{s}$ precision.
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关键词
Action potentials (APs),body channel communication (BCC),electroneurogram (ENG),feature extraction,level-crossing (LC) analog-to-digital converters (ADC)s,neural recording,neural sensors,neuromorphic,peripheral nerves,spiking neural networks (SNNs)
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