Fractal features of Surface Electromyogram: A new measure for low level muscle activation
نویسنده
چکیده
Identifying finger and wrist flexion based actions using single channel surface electromyogram have a number of rehabilitation, defence and human computer interface applications. These applications are currently infeasible because of unreliability in classification of sEMG when the level of muscle contraction is low and when there are multiple active muscles. The presence of noise and cross-talk from closely located and simultaneously active muscles is exaggerated when muscles are weakly active such as during maintained wrist and finger flexion. It has been established in literature that surface electromyogram (sEMG) and other such biosignals are fractal signals. Some researchers have determined that fractal dimension (FD) is related to strength of muscle contraction. On careful analysis of fractal properties of sEMG, this research work has established that FD is related to the muscle size and complexity and not to the strength of muscle
منابع مشابه
Removing ECG Artifact from the Surface EMG Signal Using Adaptive Subtraction Technique
Background: The electrocardiogram artifact is a major contamination in the electromyogram signals when electromyogram signal is recorded from upper trunk muscles and because of that the contaminated electromyogram is not useful.Objective: Removing electrocardiogram contamination from electromyogram signals.Methods: In this paper, the clean electromyogram signal, electrocardiogram artifact and e...
متن کاملA COMPARATIVE ANALYSIS OF WAVELET-BASED FEMG SIGNAL DENOISING WITH THRESHOLD FUNCTIONS AND FACIAL EXPRESSION CLASSIFICATION USING SVM AND LSSVM
This work presents a technique for the analysis of Facial Electromyogram signal activities to classify five different facial expressions for Computer-Muscle Interfacing applications. Facial Electromyogram (FEMG) is a technique for recording the asynchronous activation of neuronal inside the face muscles with non-invasive electrodes. FEMG pattern recognition is a difficult task for the researche...
متن کاملInvited Review HIGHLIGHTED TOPIC Neural Control of Movement The extraction of neural strategies from the surface EMG
Farina, Dario, Roberto Merletti, and Roger M. Enoka. The extraction of neural strategies from the surface EMG. J Appl Physiol 96: 1486–1495, 2004; 10.1152/japplphysiol.01070.2003.—This brief review examines some of the methods used to infer central control strategies from surface electromyogram (EMG) recordings. Among the many uses of the surface EMG in studying the neural control of movement, ...
متن کاملThe extraction of neural strategies from the surface EMG.
This brief review examines some of the methods used to infer central control strategies from surface electromyogram (EMG) recordings. Among the many uses of the surface EMG in studying the neural control of movement, the review critically evaluates only some of the applications. The focus is on the relations between global features of the surface EMG and the underlying physiological processes. ...
متن کاملDetection of Mo geochemical anomaly in depth using a new scenario based on spectrum–area fractal analysis
Detection of deep and hidden mineralization using the surface geochemical data is a challenging subject in the mineral exploration. In this work, a novel scenario based on the spectrum–area fractal analysis (SAFA) and the principal component analysis (PCA) has been applied to distinguish and delineate the blind and deep Mo anomaly in the Dalli Cu–Au porphyry mineralization area. The Dalli miner...
متن کامل