ANALYSIS OF ELECTROMYOGRAPHY (EMG) SIGNAL PROCESSING ATTRIBUTES

Electromyography (EMG) is a study of the muscular activity through analysis of electrical activity produced from muscles. This electrical activity is present as a raw signal as a signal is the result of neuromuscular activation that linked with muscle contraction. The most frequent techniques of signal recording are using surface and needle or wire electrode. The needle or wire electrode usually used by clinicians in clinical electromyography. This paper will concentrate on surface electromyography (SEMG) signal or also known as kinesiological signal. During recording and storing EMG data, several problems had to be encountered such as noise, motion artifacts and signal instability. Therefore, various filtering signal processing have been implemented to improve reliable signal for analysis. The purpose of this paper is to illustrate the best filtering methods that can be used for an EMG signal analysis. Then, the correlation between thermal images and EMG devices is implemented.