Bio-robotics research for non-invasive myoelectric neural interfaces for upper-limb prosthetic control: a 10-year perspective review

A decade ago, a group of researchers from academia and industry identified a dichotomy between the industrial and academic state-of-the-art in upper-limb prosthesis control, a widely used bio-robotics application. They proposed that four key technical challenges, if addressed, could bridge this gap and translate academic research into clinically and commercially viable products. These challenges are unintuitive control schemes, lack of sensory feedback, poor robustness and single sensor modality. Here, we provide a perspective review on the research effort that occurred in the last decade, aiming at addressing these challenges. In addition, we discuss three research areas essential to the recent development in upper-limb prosthetic control research but were not envisioned in the review 10 years ago: deep learning methods, surface electromyogram decomposition and open-source databases. To conclude the review, we provide an outlook into the near future of the research and development in upper-limb prosthetic control and beyond. This is a perspective review of the last ten years of translational research and development efforts in non-invasive neural interfaces and robotics for practical and clinical applications of upper-limb prosthetics.

Automated summary

A decade ago, researchers identified challenges in upper-limb prosthesis control and proposed four key technical challenges that could bridge the gap between academic and industrial state-of-the-art. This review examines the research efforts made in the past decade to address these challenges, as well as recent developments in deep learning methods, surface electromyogram decomposition, and open-source databases. The review also provides an outlook into the future of upper-limb prosthetic control research and development.