Challenges and Opportunities of Edge AI for Next-Generation Implantable BMIs
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Abstract (arXiv)
Neuroscience and neurotechnology are currently being revolutionized by artificial intelligence (AI) and machine learning. AI is widely used to study and interpret neural signals (analytical applications), assist people with disabilities (prosthetic applications), and treat underlying neurological symptoms (therapeutic applications). In this brief, we will review the emerging opportunities of on-chip AI for the next-generation implantable brain-machine interfaces (BMIs), with a focus on state-of-the-art prosthetic BMIs. Major technological challenges for the effectiveness of AI models will be discussed. Finally, we will present algorithmic and IC design solutions to enable a new generation of AI-enhanced and high-channel-count BMIs.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 4 of its 22 references that are in the map. First posted on arXiv 4 Apr 2022.
Builds on
4 of 22 references.
References · 4
- 2017Machine learning for neural decodingcited by 45
- 2020ResOT: Resource-Efficient Oblique Trees for Neural Signal Classificationcited by 12
- 2015A 128 channel Extreme Learning Machine based Neural Decoder for Brain Machine Interfacescited by 8
- 2021Closed-Loop Neural Prostheses with On-Chip Intelligence: A Review and A Low-Latency Machine Learning Model for Brain State Detectioncited by 6
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Citing papers per year: 2023: 1; 2024: 2; 2025: 2.
5 papers.
- 2024Intelligent and Miniaturized Neural Interfaces: An Emerging Era in Neurotechnologycited by 5
- 2023Combining SNNs with Filtering for Efficient Neural Decoding in Implantable Brain-Machine Interfacescited by 3
- 2024Hardware-Efficient EMG Decoding for Next-Generation Hand Prosthesescited by 0
- 2025Machine-Learning-Powered Neural Interfaces for Smart Prosthetics and Diagnosticscited by 0
- 2025BiND: A Neural Discriminator-Decoder for Accurate Bimanual Trajectory Prediction in Brain-Computer Interfacescited by 0
- 2025BiND: A Neural Discriminator-Decoder for Accurate Bimanual Trajectory Prediction in Brain-Computer Interfaces19 Aug 2025
- 2025Machine-Learning-Powered Neural Interfaces for Smart Prosthetics and Diagnostics5 May 2025
- 2024Hardware-Efficient EMG Decoding for Next-Generation Hand Prostheses30 May 2024
- 2024Intelligent and Miniaturized Neural Interfaces: An Emerging Era in Neurotechnology13 May 2024
- 2023Combining SNNs with Filtering for Efficient Neural Decoding in Implantable Brain-Machine Interfaces26 Dec 2023