Surface electromyography (sEMG) is an important measurement technique used in biomechanical, rehabilitation and sport environments. In this article the design, development and testing of a low-cost wearable sEMG system are described. The hardware architecture consists of a two-cascade small-sized bioamplifier with a total gain of 2,000 and band-pass of 3 to 500 Hz. The sampling frequency of the...

An accurate and computationally efficient means of classifying electromyographic (EMG) signal patterns has been the subject of considerable research effort in recent years. Quantitative analysis of EMG signals provides an important source of information for the diagnosis of neuromuscular disorders. Following the recent development of computer-aided EMG equipment, different methodologies in the ...

Neuromuscular actions of the brain generate electrical signals for muscles are Electromyograpic signals (EMG). It is dependent on the structure, composition of muscle, a peripheral nervous system and method of detection. Due to the nonstationary and the random nature of the EMG signal, it is difficult to differentiate different muscle conditions (neuropathy, myopathy and normal) only with EMG. ...

Hand movement classification based on Electromyo-graphy (EMG) signals has been extensively investigated in the past decades as a promising approach used for controlling upper prosthetics or robotics. Topological data analysis is relatively new and increasingly popular tool science that uses mathematical techniques from topology to analyze understand complex sets. This paper proposes method clas...

An efficient analytical method for electromyogram (EMG) signals is of great significance to research the inherent mechanism of a motor-control system. In this paper, we proposed an improved approach named wavelet-packet-based local band spectral entropy (WP-LBSE) by introducing the concept of frequency band local-energy (ELF) into the wavelet packet entropy, in order to characterize the time-va...

Nawab SH, Wotiz RP, De Luca CJ. Decomposition of indwelling EMG signals. J Appl Physiol 105: 700–710, 2008. First published May 15, 2008; doi:10.1152/japplphysiol.00170.2007.—Decomposition of indwelling electromyographic (EMG) signals is challenging in view of the complex and often unpredictable behaviors and interactions of the action potential trains of different motor units that constitute t...

Purpose: An appropriate activity of the knee agonist -antagonist muscles is important to resist against abnormal abduction-adduction moments loads around knee joint and reduce the risk of knee injuries. Exercise training has been commonly used as an intervention to improve neuromuscular activity within the synergic and/or agonist-antagonist muscles. However, maximizing the effectiveness of exer...

This chapter describes a control method for a multi-joint robotic manipulator using Electromyogram (EMG) signals for operating a glovebox. The system uses a Probabilistic Neural Network (PNN) to estimate the user’s intended motion from EMG patterns, and generates a control command for the glovebox and robotic manipulator corresponding to the estimated motions. The user can therefore control the...

We are developing a multi-channel/multifunction prosthetic hand/arm controller system capable of receiving and processing signals from up to sixteen Implanted MyoElectric Sensors (IMES). The appeal of implanted sensors for myoelectric control is that EMG signals can be measured at their source providing relatively cross-talk free signals that can be treated as independent control sites. Therefo...

− The present paper proposes a human interface regulating the viscoelastic characteristics of the robot manipulator by the EMG signals picked up from the subject. The desired trajectory intended by the subject is generated through the bilinear internal arm model with the EMG input signals, and then the viscoelastic coefficients of robot manipulator are regulated corresponding to the sum of the ...