Important Factors in surface EMG measurement

1µm-thickness 64-channel surface electromyogram measurement sheet with 2V organic transistors for prosthetic hand control

A surface electromyogram (EMG), which measures a voltage waveform produced by skeletal muscles on skin, is an important tool for applications detecting the human will of motion, such as for prosthetic hands and prosthetic legs. In the application to a prosthetic hand, a multipoint EMG measurement is required to precisely control the hand [1, 2]. Conventional multipoint measurements with a passi...

Quantitative Assessment of Muscle Fatigue for FES Research Studies

Background: Muscle fatigue is an important issue in neuromuscular rehabilitation. Better control of this phenomenon would result in better prevention of its consequent physiological damages.Objective: To provide a mathematical representation of muscle fatigue as a function of time.Methods: We conducted this study by combining the EMG-based estimation methods of muscle activation with the availa...

Complexity Analysis of Surface EMG for Overcoming ECG Interference toward Proportional Myoelectric Control

Electromyographic (EMG) signals from muscles in the body torso are often contaminated by electrocardiography (ECG) interferences, which consequently compromise EMG intensity estimation. The ECG interference has become a barrier to proportional control of myoelectric prosthesis using a neural machine interface called targeted muscle reinnervation (TMR), which involves transferring the residual a...

An Android Application for Estimating Muscle Onset Latency using Surface EMG Signal

Background: Electromyography (EMG) signal processing and Muscle Onset Latency (MOL) are widely used in rehabilitation sciences and nerve conduction studies. The majority of existing software packages provided for estimating MOL via analyzing EMG signal are computerized, desktop based and not portable; therefore, experiments and signal analyzes using them should be completed locally. Moreover, a...

Corrigendum to: “Removing ECG Artifact from the Surface EMG Signal Using Adaptive Subtraction Technique” published in J Biomed Phys Eng 2014; 4(1):31-38