An Active Microchannel Neural Interface for Implantable Electrical Stimulation and Recording
A mm-sized, implantable neural interface for bidirectional control of the peripheral nerves with microchannel electrodes is presented in this paper. The application-specific integrated circuit (ASIC) developed in a 0.18 $\mu$m CMOS technology is designed to achieve highly selective, concurrent control of 300-$\mu$m-wide groups of small nerve sections. It has in-situ, high-voltage-compliant (45 V) electrical stimulation and low-voltage (1.8 V) neural recording in each channel. Biphasic stimulus current pulses up to 124 $\mu$A, with a 2 $\mu$A resolution are generated between 7.4 Hz and 20 kHz frequencies to stimulate and block neural activity. Action potentials are measured across a 10 kHz bandwidth with a variable gain response that ranges up to 72 dB. The neural recording front-end implements a low-power and low-noise biopotential amplifier with an input-referred noise (IRN) of 2.74 $\mu$V<sub>rms</sub> across the full measurement bandwidth. Automatic detection and reduction of stimulus artifacts is realised using a pole-shifting mechanism with a 1-ms amplifier recovery time. Versatile control of concurrently-operating channels is achieved in a two-channel, 2.31 mm<sup>2</sup> interface ASIC using local control that allows up to seven devices to operate in parallel. In vitro validation of the active interface shows feasibility for closed-loop peripheral nerve control, while ex vivo analyses of concurrent stimulation and recording demonstrates the measured neural response to electrical stimuli.
Authors
- Andreas Demosthenous (ORCID: https://orcid.org/0000-0003-0623-963X)
- Dai Jiang (ORCID: https://orcid.org/0000-0001-9575-8831)
- Maryam Habibollahi (ORCID: https://orcid.org/0000-0003-2755-0750)
- Henry T. Lancashire (ORCID: https://orcid.org/0000-0002-1377-7439)
Institutions
- University College London (GB)
Publication Details
- Journal
- IEEE Transactions on Biomedical Circuits and Systems
- Published
- 2025-01-27
- DOI
- https://doi.org/10.1109/tbcas.2025.3533612
- Citations
- 5
- Primary Topic
- Neuroscience and Neural Engineering
- Type
- article
- Field-Weighted Citation Impact
- 4.55