In spite of availability of various approaches, the control of prosthetic limb would be more effective if it is based on Electromyogram (EMG) signals from remnant muscles and Electroencephalogram (EEG). The analysis of these signals depends on various factors such as amplitude, time and frequency domain properties. EEG signals are obtained from the experiments conducted in Biomedical laboratory...

This paper discusses the speech related information in the facial EMG for applications such as human computer interface. The primary objective of this work is to investigate the use of facial EMG as a voiceless communication medium or to drive computer based equipment by people who are unable to speak. Subjects were asked to pronounce the five English vowels with no acoustic output (voiceless)....

Surface Electromyography (EMG) is a standard method used in clinical practice and research to assess motor function in order to help with the diagnosis of neuromuscular pathology in human and animal models. EMG recorded from trunk muscles involved in the activity of breathing can be used as a direct measure of respiratory motor function in patients with spinal cord injury (SCI) or other disorde...

In this work, the signal-force relation is investigated by analyzing the EMG signals measured from the muscles under the effect of forces. Surface EMG signals are recorded during the isometric and anisometric contraction of four muscles with different levels of forces applied to the arm. Higher order frequency moments calculated from the power spectrum of signals are used as characterizing feat...

The motor unit action potentials (MUPs) in an electromyographic (EMG) signal provide a significant source of information for the assessment of neuromuscular disorders. Since recently there were different types of developments in computer-aided EMG equipment, different methodologies in the time domain and frequency domain has been followed for quantitative analysis of EMG signals. In this study,...

This paper presents the work on a technology for Real time EMG acquisition and recognition of head movement. EMG signal detection and analysis is useful in various clinical and biomedical applications such as generation of control signal for prosthetic tool, but better solutions for detecting noise free EMG signals need to be developed. In this paper a simple and cost effective method for estim...

Abstract Electromyography (EMG) is the superposition of motor unit action potential (MUAP) in many muscle fibers time and space. In real measurement, EMG signals will contaminate signals, therefore they bring great difficulties to qualified analysis interpretation EEG it a momentous step remove artifacts from signals. recent years, new methods were developed for removal such as Multivariate Emp...

This paper proposes a real-time emotion recognition system that utilizes photoplethysmography (PPG) and electromyography (EMG) physiological signals. The proposed approach employs complex-valued neural network to extract common features from the signals, enabling successful without interference. comprises three stages: single-pulse extraction, coherence feature module, module. experimental resu...

Electromyogram (EMG) signals can be measured from human muscles and can be used to anticipate movements. In fact, many researchers have tried to use these signals as an interface tool for a prosthetic hand. However, most of these studies focused on the discrimination performance of the EMG signals, and only discussed the control method for the prosthetic hand. Evaluation of the operating perfor...

This study aims at proposing an efficient method for automated electrocardiography (ECG) artifact removal from surface electromyography (EMG) signals recorded from upper trunk muscles. Wavelet transform is applied to the simulated data set of corrupted surface EMG signals to create multidimensional signal. Afterward, independent component analysis (ICA) is used to separate ECG artifact componen...