With the advent of high-density micro-electrodes arrays, developing neural probes satisfying the real-time and stringent power-efficiency requirements becomes more challenging. A smart neural probe is an essential device in future neuroscientific research and medical applications. To realize such devices, we present a 22 nm FDSOI SoC with complex on-chip real-time data processing and training for neural signal analysis. It consists of a digitally-assisted 16-channel analog front-end with 1.52 μ W/Ch, dedicated bio-processing accelerators for spike detection and classification with 2.79 μ W/Ch, and a 125 MHz RISC-V CPU, utilizing adaptive body biasing at 0.5 V with a supporting 1.79 TOPS/W MAC array. The proposed SoC shows a proof-of-concept of how to realize a high-level integration of various on-chip accelerators to satisfy the neural probe requirements for modern applications.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:82996 |
| Date | 20 January 2023 |
| Creators | Zeinolabedin, Seyed Mohammad Ali, Schüffny, Franz Marcus, George, Richard, Kelber, Florian, Bauer, Heiner, Scholze, Stefan, Hänzsche, Stefan, Stolba, Marco, Dixius, Andreas, Ellguth, Georg, Walter, Dennis, Höppner, Sebastian, Mayr, Christian |
| Publisher | IEEE |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/acceptedVersion, doc-type:article, info:eu-repo/semantics/article, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 1940-9990, 10.1109/TBCAS.2022.3142987, info:eu-repo/grantAgreement/European Commission/H2020 | RIA/824162//A Synaptically connected brain-silicon Neural Closed-loop Hybrid system/SYNCH |
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