ArticleIEEE journal of solid-state circuits2022
An Implantable Neuromorphic Sensing System Featuring Near-sensor Computation and Send-on-Delta Transmission for Wireless Neural Sensing of Peripheral Nerves.
Article in IEEE journal of solid-state circuits, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Organoid intelligence: a promising paradigm for autism spectrum disorder research.Molecular psychiatry · 2026Review
- Neuromorphic Technologies for Neuroengineering: From Adaptive Stimulation to SNN-Based Inference and Deployable Biointerfaces.Sensors (Basel, Switzerland) · 2026Review
- Distributed implantable microchips as wireless networks for neural sensing and stimulation.Frontiers in neuroscience · 2026Review
- Control of spatiotemporal activation of organ-specific fibers in the swine vagus nerve by intermittent interferential current stimulation.Nature communications · 2025Article
- An Event-Based Neural Compressive Telemetry With >11× Loss-Less Data Reduction for High-Bandwidth Intracortical Brain Computer Interfaces.IEEE transactions on biomedical circuits and systems · 2024Article
- The rise of bioelectronic medicine.Bioelectronic medicine · 2024Review
- A 4-Channel 0.23The ... Midwest Symposium on Circuits and Systems conference proceedings : MWSCAS. Midwest Symposium on Circuits and Systems · 2024Article
- Neuromorphic hardware for somatosensory neuroprostheses.Nature communications · 2024Review
- An asynchronous wireless network for capturing event-driven data from large populations of autonomous sensors.Nature electronics · 2024Article
- The Fifth Bioelectronic Medicine Summit: today's tools, tomorrow's therapies.Bioelectronic medicine · 2023Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
This paper presents a bio-inspired 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×, while maintaining a low normalized RMS error of 4% after reconstruction. The proposed NSS consists of three sub-circuits. A clockless level-crossing (LC) ADC with background offset calibration has been employed to reduce the data rate, while maintaining a high signal to quantization noise ratio. A fully synthesized spiking neural network (SNN) extracts temporal features of compound action potential signals consumes only 13 μW. An event-driven pulse-based body channel communication (Pulse-BCC) with serialized address-event representation encoding (AER) schemes minimizes transmission energy and form factor. The prototype is fabricated in 40-nm CMOS occupying a 0.32-mm
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.