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Logo for the Journal of Rehab R&D
Development Vol. 35 No. 3, July 1998
Pages 294-304


Automatic tuning of myoelectric prostheses

Claudio Bonivento, Prof; Angelo Davalli; Cesare Fantuzzi, PhD; Rinaldo Sacchetti; S. Terenzi

DEIS-LAR, University of Bologna, 40136 Bologna, Italy; Centro per la Sperimentazione ed Applicazione di Protesi e Presidi Ortopedici, INAIL, Vigorso (Bologna), Italy; University of Ferrara, Department of Engineering, 44100 Ferrara, Italy

Abstract — 

This paper is concerned with the development of a software package for the automatic tuning of myoelectric prostheses. The package core consists of Fuzzy Logic Expert Systems (FLES) that embody skilled operator heuristics in the tuning of prosthesis control parameters.
The prosthesis system is an artificial arm-hand system developed at the National Institute of Accidents at Work (INAIL) laboratories. The prosthesis is powered by an electric motor that is controlled by a microprocessor using myoelectric signals acquired from skin-surface electrodes placed on a muscle in the residual limb of the subject. The software package, Microprocessor Controlled Arm (MCA) Auto Tuning, is a tool for aiding both INAIL expert operators and unskilled persons in the controller parameter tuning procedure.
Prosthesis control parameter setup and subsequent recurrent adjustments are fundamental for the correct working of the prosthesis, especially when we consider that myoelectric parameters may vary greatly with environmental modifications. The parameter adjustment requires the end-user to go to the manufacturers' laboratory for the control parameters setup because, generally, he/she does not have the necessary knowledge and instruments to do this at home. However, this procedure is not very practical and involves a waste of time for the technicians and uneasiness for the clients.
The idea behind the MCA Auto Tuning package consists in translating technician expertise into an FLES knowledge database. The software interacts through a user-friendly graphic interface with an unskilled user, who is guided through a step-by-step procedure in the prosthesis parameter tuning that emulates the traditional expert-aided procedure.
The adoption of this program on a large scale may yield considerable economic benefits and improve the service quality supplied to the users of prostheses. In fact, the time required to set the prosthesis parameters are remarkably reduced, as is the technicians' working time. This is interpreted as minor costs for prostheses manufacturers and suppliers.

Key words: fuzzy logic, human-machine interface, prosthetics.


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