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Embedded Controller for Artificial Limbs

Enzo Mastinu (Institutionen för signaler och system, Medicinska signaler och system)
Gothenburg : Chalmers University of Technology, 2017.
[Licentiatavhandling]

Promising developments are currently ongoing worldwide in the field of neuroprosthetics and artificial limb control. It is now possible to chronically connect a robotic limb to bone, nerves and muscles of a human being, and use the signals sourced from these connections to enable movements in the artificial limb. It is also possible to surgically redirect a nerve, deprived from its original target muscle due to amputation, to a new target in order to restore the original motor functionality. Intelligent signal processing algorithms can now utilize the bioelectric signals gathered from remaining muscles on the stump to decode the motor intention of the amputee, providing an intuitive control interface. Unfortunately for patients, clinical implementations still lag behind the advancements of research, and the conventional solutions for amputees remained basically unchanged since decades. More efforts are therefore needed from researchers to close the gap between scientific publications and hospital practices.

The ultimate focus of this thesis is set on the intuitive control of a prosthetic upper limb. It was developed an embedded system capable of prosthetic control via the processing of bioelectric signals and pattern recognition algorithms. It includes 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 amputee subjects in daily life. It also constitutes a research platform to monitor prosthesis usage and training, machine learning based control algorithms, and neural stimulation paradigms.

Nyckelord: Prosthetic Controller, Osseointegration.,Electromyography (EMG), Osseointegrated Human-Machine Gateway (OHMG), Sensory Feedback, Pattern Recognition



Denna post skapades 2017-09-08. Senast ändrad 2017-09-08.
CPL Pubid: 251770

 

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Institutioner (Chalmers)

Institutionen för signaler och system, Medicinska signaler och system (2005-2017)

Ämnesområden

Reglerteknik
Signalbehandling
Inbäddad systemteknik
Annan medicinteknik
Neurovetenskaper
Biomedicinsk laboratorievetenskap/teknologi

Chalmers infrastruktur

Relaterade publikationer

Inkluderade delarbeten:


Analog Front-Ends comparison: on the way to a portable, lowpower and low-cost EMG controller based on Pattern Recognition


Low-cost, open source bioelectric signal acquisition system


Embedded System for Prosthetic Control Using Implanted Neuromuscular Interfaces Accessed Via an Osseointegrated Implant


Examination

Datum: 2017-09-11
Tid: 10:00
Lokal: Room EF
Opponent: Associate Prof. Massimo Barbaro, Microelectronics and Bioengineering Lab., (EOLAB), Universita’ degli Studi di Cagliari, Italy