Towards clinically viable neuromuscular control of bone-anchored prosthetic arms with sensory feedback
Doctoral thesis, 2019
This thesis ultimately focuses on the intuitive control of a prosthetic upper limb. In the first part of this doctoral project, an embedded system capable of prosthetic control via the processing of bioelectric signals and pattern recognition algorithms was developed. The design included a neurostimulator to provide direct neural feedback modulated by sensory information from artificial sensors. The system was designed towards clinical implementation and its functionality was proven by its use by amputee subjects in daily life. This system was then used during the second part of the doctoral project as a research platform to monitor prosthesis usage and training, machine learning based control algorithms, and neural stimulation paradigms for tactile sensory feedback. Within this work, a novel method for interfacing a multi-grip prosthetic hand to facilitate posture selection via pattern recognition was proposed. Moreover, the need for tactile sensory feedback was investigated in order to restore natural grasping behavior in amputees. Notably, the benefit for motor coordination of somatotopic tactile feedback achieved via direct neural stimulation was demonstrated. The findings and the technology developed during this project open to the clinical use of a new class of prosthetic arms that are directly connected to the neuromusculoskeletal system, intuitively controlled and capable of tactile sensory feedback.
Electromyography
prosthetics
sensory feedback
closed-loop
osseointegration
embedded system
pattern recognition
neurostimulation
Author
Enzo Mastinu
Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering
Embedded System for Prosthetic Control Using Implanted Neuromuscular Interfaces Accessed Via an Osseointegrated Implant
IEEE Transactions on Biomedical Circuits and Systems,;Vol. 11(2017)p. 867-877
Journal article
An Alternative Myoelectric Pattern Recognition Approach for the Control of Hand Prostheses: A Case Study of Use in Daily Life by a Dysmelia Subject
IEEE Journal of Translational Engineering in Health and Medicine,;Vol. 6(2018)
Journal article
Myoelectric signals and pattern recognition from implanted electrodes in two TMR subjects with an osseointegrated communication interface
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS,;Vol. 2018-July(2018)p. 5174-5177
Paper in proceeding
Grip control and motor coordination with implanted and surface electrodes while grasping with an osseointegrated prosthetic hand
Journal of NeuroEngineering and Rehabilitation,;Vol. 16(2019)
Journal article
Motor coordination in closed-loop control of osseo-neuromuscular upper limb prostheses
Unfortunately, robotic arms as seen in science-fiction are still far from reality. Clinical implementations lag behind the advancements in research, and the conventional solutions for amputees have remained basically unchanged since decades. More efforts are needed to close the gap between research findings within the lab and actual hospital practice. This thesis sets its efforts toward this direction.
This thesis ultimately focuses on the intuitive control of a prosthetic arm. An embedded system capable of prosthetic control by processing of bioelectric signals and pattern recognition algorithms was developed in the first part of this doctoral project. It includes a neurostimulator to provide tactile feedback modulated by sensory information from artificial sensors. The system functionality was proven by its successful use by amputee subjects outside the laboratory in daily life. Said system was then used during the second part of the doctoral project as a research platform to monitor prosthesis usage and training, machine learning based control algorithms, and neural stimulation paradigms for tactile sensory feedback. Within this work, a novel method for interfacing a multi-grip prosthetic hand to facilitate posture selection via pattern recognition was proposed. Moreover, the need for tactile sensory feedback to restore natural grasping behavior in amputees was investigated. In particular, the benefit for motor coordination of somatotopic tactile feedback achieved via direct neural stimulation was demonstrated. The findings and the technology developed during this project open to the clinical use of a new class of prosthetic arms which are directly connected to the neuromusculoskeletal system, intuitively controlled and capable of tactile sensory feedback.
Subject Categories
Medical Engineering
Software Engineering
Embedded Systems
Signal Processing
ISBN
978-91-7905-120-4
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4587
Publisher
Chalmers
Room EE, Hörsalsvägen 11
Opponent: Associate Professor Levi Hargrove, Northwestern University, USA