Incremental evolution of a signal classification hardware architecture for prosthetic hand control

Issue title: Adaptive Hardwarel / Evolvable Hardware

Guest editors: M.Gh. Negoitax and T. Arslany

Article type: Research Article

Authors: Torresen, Jim

Affiliations: Department of Informatics, University of Oslo, P.O. Box 1080 Blindern, N-0316 Oslo, Norway. E-mail: jimtoer@ifi.uio.no | [x] KES International, 2nd Floor, 145-157 St John Street, London, EC1V 4PY, UK | [y] School of Engineering & Electronics, The University of Edinburgh, Faraday Building, The King's Buildings, Mayfield Road, Edinburgh, EH9 3JL, UK

Abstract: Evolvable Hardware (EHW) is a new method for designing electronic circuits. However, there are several problems to solve for making high performance systems. One is the limited scalability of the ordinary approach. To reduce this problem, a novel digital signal classification architecture has been developed that allows for incremental evolution. This is based on initially evolving subcircuits for each category to be detected. The architecture is applied for classifying sensor data in a prosthetic hand controller. By applying the proposed method, the best performance achieved is substantially better than that obtained by more ordinary approaches. Analysis of the best circuit shows the importance of having an architecture containing some gates with random connections. Results of the analysis can also be used to collect better training data from users in the future.

DOI: 10.3233/KES-2008-12302

Journal: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 12, no. 3, pp. 187-199, 2008