Implantable brain machine interfaces: first-in-human studies, technology challenges and trends
Open accessAbstract
Implantable brain machine interfaces (BMIs) are now on a trajectory to go mainstream, wherein what was once considered last resort will progressively become elective at earlier stages in disease treatment. First-in-human successes have demonstrated the ability to decode highly dexterous motor skills such as handwriting, and speech from human cortical activity. These have been used for cursor and prosthesis control, direct-to-text communication and speech synthesis. Along with these breakthrough studies, technology advancements have enabled the observation of more channels of neural activity through new concepts for centralised/distributed implant architectures. This is complemented by research in flexible substrates, packaging, surgical workflows and data processing. New regulatory guidance and funding has galvanised the field. This culmination of resource, efforts and capability is now attracting significant investment for BMI commercialisation. This paper reviews recent developments and describes the paradigm shift in BMI development that is leading to new innovations, insights and BMI translation.
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Brain-computer interfaces are subject to federal and international guidelines that cap their power usage at 15-40 mW, with the exact limit varying based on the implant's depth within the brain tissue.
“For example, brain-computer interfaces (BCIs) are subject to federal and international guidelines that cap their power usage at 15–40 mW, with the exact limit varying based on the implant’s depth within the brain tissue (Rapeaux and Constandinou, 2021; Yale Engineering Magazine, 2021).”
From Comparative analysis of energy transfer mechanisms for neural implants (2024) · cites this paper as Rapeaux and Constandinou, 2021
To mitigate thermal damage, neural implants must limit temperature increases in surrounding tissues to less than 0.5°C while maintaining sufficient power output.
“To mitigate the risk of thermal damage, these devices must strictly limit temperature increases in surrounding tissues to less than 0.5°C, all while maintaining sufficient power output for device functionality (Wolf, 2008; Nurmikko, 2020; Rapeaux and Constandinou, 2021).”
From Comparative analysis of energy transfer mechanisms for neural implants (2024) · cites this paper as Rapeaux and Constandinou, 2021
Batteries can occupy up to 90% of an implant's volume and 60% of its weight.
“Batteries, for instance, can occupy up to 90% of an implant’s volume and 60% of its weight (Won et al., 2021), with space and thermal output being major constraints (Rapeaux and Constandinou, 2021).”
From Comparative analysis of energy transfer mechanisms for neural implants (2024) · cites this paper as Rapeaux and Constandinou, 2021
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References 74 · Cited by 119
- Authors
- Rapeaux, A. B., & Constandinou, T. G.
- Affiliations
- University of Surrey (GB)
- Venue
- Current Opinion in Biotechnology
- Publisher
- Elsevier BV
- Published
- 2021-12
- Volume
- 72
- Pages
- 102-111
- ISSN
- 0958-1669 (ISSN-L)
- OpenAlex
- W3212769229
- Cited by
- 119
- References
- 74
- Citations by year
- 2026: 17 · 2025: 26 · 2024: 24 · 2023: 37 · 2022: 13 · 2021: 1
- FWCI
- 2.84
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Current Opinion in Biotechnology (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- UK Dementia Research Institute
- EPSRC
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Undergraduate Neuroscience Education and Research
- Keywords
- neural decoding, motor control, speech decoding, flexible substrates, surgical workflow, regulatory guidelines, technology translation
- MeSH terms
- Humans, Technology, Prostheses and Implants, Brain-Computer Interfaces
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