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Man-Machine Interface System for Neuromuscular Training and Evaluation Based on EMG and MMG Signals
Laboratory of Electronics and Bioengineering, ETSI de Telecomunicacion, Universidad de Valladolid, Campus Miguel Delibes, Paseo Belén, 15. 47011 Valladolid, Spain
Optical Communications Group, ETSI de Telecomunicacion, Universidad de Valladolid, Campus Miguel Delibes, Paseo Belen, 15. 47011 Valladolid, Spain
* Author to whom correspondence should be addressed.
Received: 19 October 2010; in revised form: 22 November 2010 / Accepted: 25 November 2010 / Published: 7 December 2010
Abstract: This paper presents the UVa-NTS (University of Valladolid Neuromuscular Training System), a multifunction and portable Neuromuscular Training System. The UVa-NTS is designed to analyze the voluntary control of severe neuromotor handicapped patients, their interactive response, and their adaptation to neuromuscular interface systems, such as neural prostheses or domotic applications. Thus, it is an excellent tool to evaluate the residual muscle capabilities in the handicapped. The UVa-NTS is composed of a custom signal conditioning front-end and a computer. The front-end electronics is described thoroughly as well as the overall features of the custom software implementation. The software system is composed of a set of graphical training tools and a processing core. The UVa-NTS works with two classes of neuromuscular signals: the classic myoelectric signals (MES) and, as a novelty, the myomechanic signals (MMS). In order to evaluate the performance of the processing core, a complete analysis has been done to classify its efficiency and to check that it fulfils with the real-time constraints. Tests were performed both with healthy and selected impaired subjects. The adaptation was achieved rapidly, applying a predefined protocol for the UVa-NTS set of training tools. Fine voluntary control was demonstrated to be reached with the myoelectric signals. And the UVa-NTS demonstrated to provide a satisfactory voluntary control when applying the myomechanic signals.
Keywords: biological control systems; training; pattern classification; electromyography; mechanomyography; real-time systems; sensors
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De la Rosa, R.; Alonso, A.; Carrera, A.; Durán, R.; Fernández, P. Man-Machine Interface System for Neuromuscular Training and Evaluation Based on EMG and MMG Signals. Sensors 2010, 10, 11100-11125.
De la Rosa R, Alonso A, Carrera A, Durán R, Fernández P. Man-Machine Interface System for Neuromuscular Training and Evaluation Based on EMG and MMG Signals. Sensors. 2010; 10(12):11100-11125.
De la Rosa, Ramon; Alonso, Alonso; Carrera, Albano; Durán, Ramon; Fernández, Patricia. 2010. "Man-Machine Interface System for Neuromuscular Training and Evaluation Based on EMG and MMG Signals." Sensors 10, no. 12: 11100-11125.