Low-Power Circuits for Brain–Machine Interfaces
Abstract
This paper presents work on ultra-low-power circuits for brain-machine interfaces with applications for paralysis prosthetics, stroke, Parkinson's disease, epilepsy, prosthetics for the blind, and experimental neuroscience systems. The circuits include a micropower neural amplifier with adaptive power biasing for use in multi-electrode arrays; an analog linear decoding and learning architecture for data compression; low-power radio-frequency (RF) impedance-modulation circuits for data telemetry that minimize power consumption of implanted systems in the body; a wireless link for efficient power transfer; mixed-signal system integration for efficiency, robustness, and programmability; and circuits for wireless stimulation of neurons with power-conserving sleep modes and awake modes. Experimental results from chips that have stimulated and recorded from neurons in the zebra finch brain and results from RF power-link, RF data-link, electrode-recording and electrode-stimulating systems are presented. Simulations of analog learning circuits that have successfully decoded prerecorded neural signals from a monkey brain are also presented.
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Another power-scheduling method is to adapt each amplifier channel's current consumption according to the background noise at its respective electrode.
“Therefore, another power-scheduling method is to adapt the current consumption of each amplifier channel according to the background noise present at the respective electrode [17, 122, 141].”
From Implantable neurotechnologies: a review of integrated circuit neural amplifiers (2016) · cites this paper as [122]
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A Review on Neural Amplifier Design for Brain–Machine Interface
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Neurointerfaces: Review and development
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Rapoport, B. I., & Sarpeshkar, R. (2011) · IGI Global eBooks · doi:10.4018/978-1-60960-018-1.ch010 · Cited by 2 · see citing works
Self-citationNath, S., Kumar, N., Guha, K., Baishnab, K. L., & Rao, K. S. (2024) · Microsystem Technologies · doi:10.1007/s00542-023-05588-6 · Cited by 2 · see citing works
Optimised LNA for wireless link in brain machine interface applications
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Tathireddy, P., Solzbacher, F., Hitchcock, R., & Hoffmann, K. (2011) · Springer eBooks · doi:10.1007/978-3-540-74658-4_40 · Cited by 2 · see citing works
Rapoport, B. I. (2007) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 2 · see citing works
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Gosselin, B. J. (2011) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2011.6091448 · Cited by 1 · see citing works
Channel characterization for implant to body surface communication
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Iniewski, K. K. (2015) · Cambridge University Press eBooks · doi:10.1017/cbo9781139629539.027 · Cited by 1 · see citing works
Intracranial epilepsy monitoring using wireless neural recording systems
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Wireless Transfer of Power and Data Via a Single Resonant Inductive Link
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Introduction to Biomedical Signals and Their Applications
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Bladder Volume Decoding from Afferent Neural Activity
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Design Considerations of Low‐Power Digital Integrated Systems for Implantable Medical Applications
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Brain Activity Measurement with Implantable Microchip
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Efficient Neural Recording Amplifier for Brain Machine Interface
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Self-citationConstruction of flexible transistors enabled by transfer printing
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Design of a noise efficient bio-amplifier using CCFVF OTA for neurological signal acquisition
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Design and Analysis of Low-Power, Low-Noise OTA for Biomedical Application
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- Authors
- Sarpeshkar, R., Wattanapanitch, W., Arfin, S. K., Rapoport, B. I., Mandal, S., Baker, M. W., Fee, M. S., Musallam, S., & Andersen, R. A.
- Affiliations
- Massachusetts Institute of Technology (US)
- Harvard University (US)
- McGovern Institute for Brain Research (US)
- California Institute of Technology (US)
- ORCID
- Venue
- IEEE Transactions on Biomedical Circuits and Systems
- Published
- 2008-09
- Volume
- 2
- Issue
- 3
- Pages
- 173-183
- ISSN
- 1932-4545 (ISSN-L)
- 1940-9990
- OpenAlex
- W2040750693
- Cited by
- 91
- References
- 36
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 3 · 2023: 2 · 2022: 1 · 2021: 3 · 2020: 4 · 2019: 1 · 2018: 3 · 2017: 3 · 2016: 3 · 2015: 8 · 2014: 5 · 2013: 8 · 2012: 10
- FWCI
- 7.29
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Biomedical Circuits and Systems (publishedVersion)
- PubMed (publishedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- Funders
- McGovern Institute for Brain Research, Massachusetts Institute of Technology
- 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 › Biomedical Engineering › Wireless Body Area Networks
- Keywords
- brain-computer interface, ultra-low-power circuits, neural amplifier, microelectrode arrays, neural decoding, data compression, radio telemetry, wireless power transfer, mixed-signal integration, wireless neural stimulation, sleep mode, epilepsy, Parkinson's disease
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