An Active Microchannel Neural Interface with Artifact Reduction
Open accessAbstract
High-density neural electrodes in microchannel interfaces require in-situ amplification of the neural signals and rejection of high-voltage stimulus pulses leaking to the channel in order to adequately detect neural signals in the presence of concurrent stimulation. This paper presents the design of an active microchannel neural interface in 0.18 μm CMOS employing neural recording and stimulation. To reduce stimulus artifacts, a novel method is proposed that disconnects the recording module during concurrent channel stimulation and automatically applies detection and reduction of stimulus artifacts from adjacent channels using a tunable filter. Simulations show that the method provides at least 54 dB artifact attenuation.
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A hybrid approach is often adopted that combines multiple structures for effective artifact detection and cancellation while adhering to the system power and area constraints.
“A hybrid approach is often adopted that combines multiple structures for effective artifact detection and cancellation while adhering to the system power and area constraints [152], [192], [193].”
From Active Neural Interface Circuits and Systems for Selective Control of Peripheral Nerves: A Review (2024) · cites this paper as [193]
The Proposed Method describes combining signal blanking and pole shifting to reduce artifacts. Artifact Detection describes a comparator designed for detection without compromising power or area. The paper presents this as its proposed design, however, and does not establish that hybrid approaches are often adopted. (LLM, conf=0.84)
Experimental — accuracy not yet measuredMonitoring the recorded signal via a differential comparator enables automatic detection of stimulus artifacts based on their pre-determined amplitude characteristics.
“Monitoring the recorded signal via a differential comparator enables automatic detection of stimulus artifacts based on their pre-determined amplitude characteristics [193].”
From Active Neural Interface Circuits and Systems for Selective Control of Peripheral Nerves: A Review (2024) · cites this paper as [193]
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Cites
Vagus Nerve and Vagus Nerve Stimulation, a Comprehensive Review: Part III
Yuan, H., & Silberstein, S. D. (2015) · Headache The Journal of Head and Face Pain · doi:10.1111/head.12649 · Cited by 381 · see citing works
An Implantable 455-Active-Electrode 52-Channel CMOS Neural Probe
Lopez, C. M., Andrei, A., Mitra, S., Welkenhuysen, M., Eberle, W., Bartic, C., Puers, R., Yazicioglu, R. F., & Gielen, G. G. E. (2014) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2013.2284347 · Cited by 264 · see citing works
Toward true closed-loop neuromodulation: artifact-free recording during stimulation.
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A Microchannel Neuroprosthesis for Bladder Control After Spinal Cord Injury in Rat
Chew, D. J., Zhu, L., Delivopoulos, E., Minev, I. R., Musick, K. M., Mosse, C. A., Craggs, M., Donaldson, N., Lacour, S. P., McMahon, S. B., et al. (2013) · Science Translational Medicine · doi:10.1126/scitranslmed.3007186 · Cited by 123 · see citing works
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Microchannel-based regenerative scaffold for chronic peripheral nerve interfacing in amputees
Srinivasan, A., Tahilramani, M., Bentley, J. T., Gore, R. K., Millard, D. C., Mukhatyar, V. J., Joseph, A., Haque, A. S., Stanley, G. B., English, A. W., et al. (2015) · Biomaterials · doi:10.1016/j.biomaterials.2014.11.035 · Cited by 67 · see citing works
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A Multichannel High-Frequency Power-Isolated Neural Stimulator With Crosstalk Reduction
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Self-citationShadmani, A., Viswam, V., Chen, Y., Bounik, R., Dragas, J., Radivojevic, M., Geissler, S., Sitnikov, S., Muller, J., & Hierlemann, A. (2019) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2018.2890530 · Cited by 24 · see citing works
An ASIC for Recording and Stimulation in Stacked Microchannel Neural Interfaces
Lancashire, H. T., Jiang, D., Demosthenous, A., & Donaldson, N. (2019) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2019.2891284 · Cited by 15 · see citing works
Self-citationMicrochannel neural interface manufacture by stacking silicone and metal foil laminae
Lancashire, H. T., Vanhoestenberghe, A., Pendegrass, C. J., Ajam, Y. A., Magee, E., Donaldson, N., & Blunn, G. W. (2016) · Journal of Neural Engineering · doi:10.1088/1741-2560/13/3/034001 · Cited by 13 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 1
- V. Viswam, Y. Chen, A. Shadmani, J. Dragas, R. Bounik, R. Milos, J. Muller and A. Hierlemann, "2048 Action Potential Recording Channels With 2.4 uVrms Noise and Stimulation Artifact Suppression," in IEEE Biomed. Circuits Syst. Conf., 2016.
Cited by
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Active Neural Interface Circuits and Systems for Selective Control of Peripheral Nerves: A Review
Habibollahi, M., Jiang, D., Lancashire, H. T., & Demosthenous, A. (2024) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2024.3430038 · Cited by 11 · see citing works
“Monitoring the recorded signal via a differential comparator enables automatic detection of stimulus artifacts based on their pre-determined amplitude characteristics [193].”
Self-citation
- Authors
- Habibollahi, M., Hanzaee, F. F., Jiang, D., Lancashire, H., & Demosthenous, A.
- Affiliations
- University College London (GB)
- Venue
- 2021 IEEE International Symposium on Circuits and Systems (ISCAS)
- Publisher
- IEEE
- Published
- 2021-05
- Pages
- 1-4
- ISSN
- 0271-4302 (ISSN-L)
- OpenAlex
- W3159892806
- Cited by
- 5
- References
- 12
- Citations by year
- 2026: 1 · 2024: 2 · 2023: 1 · 2022: 1
- FWCI
- 1.89
- Type
- conference paper
- Language
- en
- Open access
- green
- discovery.ucl.ac.uk
- Licence
- Locations
- IEEE International Symposium on Circuits and Systems proceedings (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- European Commission
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Analog and Mixed-Signal Circuit Design
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Physical Sciences › Engineering › Electrical and Electronic Engineering › CCD and CMOS Imaging Sensors
- Keywords
- neural recording, neurostimulation, tunable filters
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