A Portable, Self-Contained Neuroprosthetic Hand with Deep Learning-Based Finger Control [preprint]

Preprint date

March 24, 2021

Authors

Anh Tuan Nguyen, Markus W Drealan, Diu Khue Luu, Ming Jiang (postdoctoral associate), Jian Xu, Jonathan Cheng, Qi Zhao (assistant professor), Edward W Keefer, Zhi Yang

Abstract

Objective: Deep learning-based neural decoders have emerged as the prominent approach to enable dexterous and intuitive control of neuroprosthetic hands. Yet few studies have materialized the use of deep learning in clinical settings due to its high computational requirements.

Methods: Recent advancements of edge computing devices bring the potential to alleviate this problem. Here we present the implementation of a neuroprosthetic hand with embedded deep learning-based control. The neural decoder is designed based on the recurrent neural network (RNN) architecture and deployed on the NVIDIA Jetson Nano - a compacted yet powerful edge computing platform for deep learning inference. This enables the implementation of the neuroprosthetic hand as a portable and self-contained unit with real-time control of individual finger movements.

Results: The proposed system is evaluated on a transradial amputee using peripheral nerve signals (ENG) with implanted intrafascicular microelectrodes. The experiment results demonstrate the system's capabilities of providing robust, high-accuracy (95-99%) and low-latency (50-120 msec) control of individual finger movements in various laboratory and real-world environments.

Conclusion: Modern edge computing platforms enable the effective use of deep learning-based neural decoders for neuroprosthesis control as an autonomous system. Significance: This work helps pioneer the deployment of deep neural networks in clinical applications underlying a new class of wearable biomedical devices with embedded artificial intelligence.

Link to full paper

A Portable, Self-Contained Neuroprosthetic Hand with Deep Learning-Based Finger Control

Keywords

deep learning, robotics, artificial intelligence

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