Abstract

CAMACHO NAVARRO, JHONATAN; LEON-VARGAS, FABIAN  and  BARRERO PEREZ, JAIME. EMG-BASED SYSTEM FOR BASIC HAND MOVEMENT RECOGNITION. Dyna rev.fac.nac.minas [online]. 2012, vol.79, n.171, pp.41-49. ISSN 0012-7353.

This paper presents a system for the automatic identification of six basic hand movements in healthy subjects based on a steady-state of electromyographic signals. The following basic hand motions were detected: opening, closing, flexion, extension, pronation, and supination, as well as the rest condition. A modular approach of pattern recognition with discrete wavelet transform, principal component analysis, and support vector machines was used to discriminate each movement. Identification was completed off-line every 256 ms with a hardware-software interface composed of a signal acquisition system with two electromyographic differential channels using Matlab® and LabVIEW® software. The system was trained and tested using five subjects of different gender, age, and physical complexion, with identification rates of up to 99.25 %.

Keywords : Electromyography; hand-prosthesis; pattern recognition; principal component analysis; discrete wavelet transform; support vector machines.

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