In this paper a software package that uses a Fuzzy Logic Expert System (FLES) to compute myoelectric prosthesis control parameter values is presented and the experimental results from its preliminary practical application are discussed. The prosthesis system is the INAIL artificial arm powered by an electrical motor controlled by a microprocessor using myoelectric signals acquired from skin-surface electrodes placed on the patient muscle stump. The software package here presented, named MCA (Microprocessor Controlled Arm) Auto Tuning, is a software tool for a step-by-step controller parameters tuning procedure, useful for expert operators as well as unskilled amputee patients. The control parameters set-up and subsequent recurrent adjustment are necessary for the prosthesis correct working. These tasks are usually performed by skilled operator together with the patient in the prosthesis-maker laboratory, however this is quite unpractical and involves technicians' waste of time and patients' uneasiness. The MCA Auto Tuning package embodies technician expertize in control parameters set-up in a FLES module. The unskilled patient interacts with the graphical interface of the software, and is guided by the programme to tune the controller parameters in a step-by-step procedure that emulates the traditional expert-aided tuning procedure. The adoption of this program on a large scale may yield considerable economic benefits and improve the service quality supplied to the prosthesis users. In fact the time required to set the prosthesis parameters is remarkably reduced and, consequently, working time of technicians is reduced too, decreasing costs of prostheses makers and providers. Moreover, by using MCA Auto Tuning package the present troubles and outlays for the patient can be dramatically lowered since any artificial arm resetting requires only a few easy adjustment staying at home
Automatic tuning of myoelectric prostheses / C., Bonivento; A., Davalli; Fantuzzi, Cesare; S., Terenzi. - In: JOURNAL OF REHABILITATION RESEARCH AND DEVELOPMENT. - ISSN 0748-7711. - STAMPA. - 35:3(2001), pp. 294-304.
Automatic tuning of myoelectric prostheses
FANTUZZI, Cesare;
2001
Abstract
In this paper a software package that uses a Fuzzy Logic Expert System (FLES) to compute myoelectric prosthesis control parameter values is presented and the experimental results from its preliminary practical application are discussed. The prosthesis system is the INAIL artificial arm powered by an electrical motor controlled by a microprocessor using myoelectric signals acquired from skin-surface electrodes placed on the patient muscle stump. The software package here presented, named MCA (Microprocessor Controlled Arm) Auto Tuning, is a software tool for a step-by-step controller parameters tuning procedure, useful for expert operators as well as unskilled amputee patients. The control parameters set-up and subsequent recurrent adjustment are necessary for the prosthesis correct working. These tasks are usually performed by skilled operator together with the patient in the prosthesis-maker laboratory, however this is quite unpractical and involves technicians' waste of time and patients' uneasiness. The MCA Auto Tuning package embodies technician expertize in control parameters set-up in a FLES module. The unskilled patient interacts with the graphical interface of the software, and is guided by the programme to tune the controller parameters in a step-by-step procedure that emulates the traditional expert-aided tuning procedure. The adoption of this program on a large scale may yield considerable economic benefits and improve the service quality supplied to the prosthesis users. In fact the time required to set the prosthesis parameters is remarkably reduced and, consequently, working time of technicians is reduced too, decreasing costs of prostheses makers and providers. Moreover, by using MCA Auto Tuning package the present troubles and outlays for the patient can be dramatically lowered since any artificial arm resetting requires only a few easy adjustment staying at homePubblicazioni consigliate
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris