Silent speech interfaces (SSI) provide ways capture silently spoken human speech. In electromyography (EMG) based SSIs, surface electrodes attached to the user’s face record electric signals, which are used to infer speech. It is an important goal to increase wearing comfort and decrease system setup time by reducing the number of devices attached to the user’s face. By using multi-electrode ar...

BACKGROUND Entropy is an anaesthetic EEG monitoring method, calculating two numerical parameters: State Entropy (SE, range 0-91) and Response Entropy (RE, range 0-100). Low Entropy numbers indicate unconsciousness. SE uses the frequency range 0.8-32 Hz, representing predominantly the EEG activity. RE is calculated at 0.8-47 Hz, consisting of both EEG and facial EMG. RE-SE difference (RE-SE) can...

BACKGROUND/AIMS This work focuses on recording, processing and interpretation of multichannel surface EMG detected from the external anal sphincter muscle. The aim is to describe the information that can be extracted from signals recorded with such a technique. METHODS The recording of many signals from different locations on a muscle allows the extraction of additional information on muscle ...

Objective: The aim of this study was to investigate the potential of surface electromyography (EMG) for assessing neuromuscular efficiency and localized muscle fatigue in the lumbar extensors, in individuals with scoliosis. Methods: Twenty individuals participated in this study, divided equally into two groups: (1) Scoliosis Group and (2) Control Group. These subjects underwent a fatigue induct...

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,...

Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpos...

Decomposition of electromyograms (EMG) is a key approach to investigating motor unit plasticity. Various signal processing techniques have been developed for high density surface EMG decomposition, among which the convolution kernel compensation (CKC) has achieved high decomposition yield with extensive validation. Very recently, a progressive FastICA peel-off (PFP) framework has also been deve...

Background/Aims: This work focuses on recording, processing and interpretation of multi-channel surface EMG detected from the external anal sphincter muscle. The aim is to describe the information that can be extracted from signals recorded with such a technique. Methods: The recording of many signals from different locations on a muscle allows the extraction of additional information on muscle...