| 000 | 02487 am a22003373u 4500 | ||
|---|---|---|---|
| 042 | _adc | ||
| 100 | 1 | 0 |
_aHe, Yuming _eauthor _92761 |
| 700 | 1 | 0 |
_aCorradi, Federico _eauthor _92762 |
| 700 | 1 | 0 |
_aShi, Chengyao _eauthor _92763 |
| 700 | 1 | 0 |
_avan der Ven, Stan _eauthor _92764 |
| 700 | 1 | 0 |
_aTimmermans, Martijn _eauthor _92765 |
| 700 | 1 | 0 |
_aStuijt, Jan _eauthor _92766 |
| 700 | 1 | 0 |
_aDetterer, Paul _eauthor _92767 |
| 700 | 1 | 0 |
_aHarpe, Pieter _eauthor _92768 |
| 700 | 1 | 0 |
_aLindeboom, Lucas _eauthor _92769 |
| 700 | 1 | 0 |
_aHermeling, Evelien _eauthor _92770 |
| 700 | 1 | 0 |
_aLangereis, Geert _eauthor _92771 |
| 700 | 1 | 0 |
_aChicca, Elisabetta _eauthor _92772 |
| 700 | 1 | 0 |
_aLiu, Yao-Hong _eauthor |
| 245 | 0 | 0 | _aAn Implantable Neuromorphic Sensing System Featuring Near-sensor Computation and Send-on-Delta Transmission for Wireless Neural Sensing of Peripheral Nerves |
| 260 | _c2022-10. | ||
| 500 | _a/pmc/articles/PMC7614138/ | ||
| 500 | _a/pubmed/36741239 | ||
| 520 | _aThis 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(2) active area and consumes in total 28.2 μW and 50 μW power in feature extraction and full diagnosis mode, respectively. The presented NSS also extracts temporal features of compound action potential signals with 10-μs precision. | ||
| 540 | _a | ||
| 546 | _aen | ||
| 690 | _aArticle | ||
| 655 | 7 |
_aText _2local |
|
| 786 | 0 | _nIEEE J Solid-State Circuits | |
| 856 | 4 | 1 |
_uhttp://dx.doi.org/10.1109/JSSC.2022.3193846 _zConnect to this object online. |
| 999 |
_c2360 _d2360 |
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