Research Repository

Decoding information from neural signals recorded using intraneural electrodes: Toward the development of a neurocontrolled hand prosthesis

Micera, S and Citi, L and Rigosa, J and Carpaneto, J and Raspopovic, S and Di Pino, G and Rossini, L and Yoshida, K and Denaro, L and Dario, P and Rossini, PM (2010) 'Decoding information from neural signals recorded using intraneural electrodes: Toward the development of a neurocontrolled hand prosthesis.' Proceedings of the IEEE, 98 (3). 407 - 417. ISSN 0018-9219

[img]
Preview
Text
Micera2010DecodingFromIntraneuralElect.pdf

Download (958kB) | Preview

Abstract

The possibility of controlling dexterous hand prostheses by using a direct connection with the nervous system is particularly interesting for the significant improvement of the quality of life of patients, which can derive from this achievement. Among the various approaches, peripheral nerve based intrafascicular electrodes are excellent neural interface candidates, representing an excellent compromise between high selectivity and relatively low invasiveness. Moreover, this approach has undergone preliminary testing in human volunteers and has shown promise. In this paper, we investigate whether the use of intrafascicular electrodes can be used to decode multiple sensory and motor information channels with the aim to develop a finite state algorithm that may be employed to control neuroprostheses and neurocontrolled hand prostheses. The results achieved both in animal and human experiments show that the combination of multiple sites recordings and advanced signal processing techniques (such as wavelet denoising and spike sorting algorithms) can be used to identify both sensory stimuli (in animal models) and motor commands (in a human volunteer). These findings have interesting implications, which should be investigated in future experiments. © 2006 IEEE.

Item Type: Article
Subjects: R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 11 Feb 2013 16:43
Last Modified: 05 Feb 2019 19:15
URI: http://repository.essex.ac.uk/id/eprint/5486

Actions (login required)

View Item View Item