English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper presents microwatt end-to-end neural signal processing hardwarefor deployment-stage real-time upper-limb movement intent decoding. This modulefeatures intercellular spike detection, sorting, and decoding operations for a96-channel prosthetic implant. We design the algorithms for those operations toachieve minimal computation complexity while matching or advancing the accuracyof state-of-art Brain-Computer-Interface sorting and movement decoding. Basedon those algorithms, we devise the architect of the neural signal processinghardware with the focus on hardware reuse and event-driven operation. Thedesign achieves among the highest levels of integration, reducing wireless datarate by more than four orders of magnitude. The chip prototype in a 180-nmhigh-VTH, achieving the lowest power dissipation of 0.61 uW for 96 channels,21X lower than the prior art at a comparable/better accuracy even withintegration of kinematic state estimation computation.

A 6.3-Nanowatt-per-Channel 96-Channel Neural Spike Processor for a Movement-Intention-Decoding Brain-Computer-Interface Implant