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A 41.2 nJ/class, 32-Channel On-Chip Classifier for Epileptic Seizure Detection.

, , , , and . EMBC, page 3693-3696. IEEE, (2018)

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A 41.2 nJ/class, 32-Channel On-Chip Classifier for Epileptic Seizure Detection., , , , and . EMBC, page 3693-3696. IEEE, (2018)Challenges and Opportunities of Edge AI for Next-Generation Implantable BMIs., , and . AICAS, page 190-193. IEEE, (2022)Cost-Efficient Classification for Neurological Disease Detection., , and . BioCAS, page 1-4. IEEE, (2019)Closed-Loop Neural Interfaces with Embedded Machine Learning., , and . ICECS, page 1-4. IEEE, (2020)33.3 MiBMI: A 192/512-Channel 2.46mm² Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes., , , , , and . ISSCC, page 546-548. IEEE, (2024)A 0.21-ps FOM Capacitor-Less Analog LDO with Dual-Range Load Current for Biomedical Applications., and . BioCAS, page 1-5. IEEE, (2023)Tunnel FET-based ultra-low power, low-noise amplifier design for bio-signal acquisition., , , , , and . ISLPED, page 57-62. ACM, (2014)Resting Tremor Detection in Parkinson's Disease with Machine Learning and Kalman Filtering., , and . BioCAS, page 1-4. IEEE, (2018)Compressive multichannel cortical signal recording., , , , and . ICASSP, page 4305-4309. IEEE, (2013)Analysis and Characterization of Variability in Subthreshold Source-Coupled Logic Circuits., , , , and . IEEE Trans. Circuits Syst. I Regul. Pap., 62-I (2): 458-467 (2015)