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The scientists utilized AI versions based upon the existing semantic networks (RNN) to review as well as precisely translate the amputee’s intent of relocating specific fingers from outer nerve tasks. The AI designs are released on an NVIDIA Jetson Nano as a mobile, self-supporting device. With this AI-powered nerve user interface, the amputee can regulate a neuroprosthetic hand with life-like mastery as well as intuition.
1. Nguyen & Drealan et al. (2021) A Portable, Self-Contained Neuroprosthetic Hand with Deep Learning-Based Finger Control: https://arxiv.org/abs/2103.13452
2. Luu & Nguyen et al. (2021) Deep Learning-Based Approaches for Decoding Motor Intent from Peripheral Nerve Signals: https://www.researchgate.net/publication/349448928_Deep_Learning-Based_Approaches_for_Decoding_Motor_Intent_from_Peripheral_Nerve_Signals
3. Nguyen et al. (2021) Redundant Crossfire: A Technique to Achieve Super-Resolution in Neurostimulator Design by Exploiting Transistor Mismatch: https://experts.umn.edu/en/publications/redundant-crossfire-a-technique-to-achieve-super-resolution-in-ne
4. Nguyen & Xu et al. (2020) A Bioelectric Neural Interface Towards Intuitive Prosthetic Control for Amputees: https://www.biorxiv.org/content/10.1101/2020.09.17.301663v1.full
5. Writers’ internet site with video clips as well as photos: https://sites.google.com/view/jules-anhtuannguyen/gallery?authuser=0
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