With the ever increasing role of computerized machines in society, Human Computer Interaction (HCI) system has become an increasingly important part of our daily lives. HCI determines the effective utilization of the available information flow of the computing, communication, and display technologies. In recent years, there has been a tremendous interest in introducing intuitive interfaces that...

BACKGROUND Multi-channel recording of surface electromyographyic (EMG) signals is very likely to be contaminated by electrocardiographic (ECG) interference, specifically when the surface electrode is placed on muscles close to the heart. METHODS A novel fast independent component analysis (FastICA) based peel-off method is presented to remove ECG interference contaminating multi-channel surfa...

TO THE EDITOR: The electromyogram (EMG) as an indirect measure of motor unit activity has proved invaluable in motor control studies. Increasingly, the application of frequency domain techniques to EMG signals has provided important insight into the structure and function of the human motor system. In a recent publication Neto and Christou (2010) claimed that rectification of the EMG impairs id...

The different techniques to measure and analyze surface EMG are summarized with an emphasis on the clinician's point of view. The application of surface EMG in neurological disease is hampered by many inherent problems, especially the difficulties in extracting features of single motor units. However, the evolution of surface EMG from single bipolar recordings via a linear array of multiple ele...

The decomposition of surface electromyogram data sets (s-EMG) is studied using blind source separation techniques based on sparseness; namely independent component analysis, sparse nonnegative matrix factorization, and sparse component analysis. When applied to artificial signals we find noticeable differences of algorithm performance depending on the source assumptions. In particular, sparse n...

We have adopted an analysis that produces a post hoc prediction of the time course of electromyogram (EMG) activity from the discharge of ensembles of neurons recorded sequentially from the primary motor cortex (M1) of a monkey. Over several recording sessions, we collected data from 50 M1 neurons and several distal forelimb muscles during a stereotyped precision grip task. Ensemble averages we...

We have adopted an analysis which produces a post hoc prediction of the time course of EMG activity from the discharge of ensembles of neurons recorded sequentially from the primary motor cortex (M1) of a monkey. Over several recording sessions, we collected data from 50 M1 neurons and several distal forelimb muscles during a stereotyped precision grip task. Ensemble averages were constructed f...

Surface electromyography (EMG) has emerged as a promising clisnical decision support system, enabling the extraction of muscles' electrical activity through non-invasive devices placed on body. This study focuses application machine learning (ML) techniques to preprocess and analyze EMG signals for detection muscle abnormalities. Notably, state-of-the-art ML algorithms, including Support Vector...

We examined the activity pattern of low-threshold motor units in the human trapezius muscle during contractions of 10 min duration. Three procedures were applied in sequence: 1) static contraction controlled by maintaining a constant low level of the surface electromyogram (EMG)-detected root-mean-square signal, 2) a manipulation task with mental concentration, and 3) copying a text on a word p...

There are numerous scenarios in which it would be preferred or necessary to manipulate the screen cursor of a computer’s graphic user interface (GUI). Some specialized operators, such as pilots or surgeons may need to interact with computer-based equipment while their hands are committed to tasks with higher priorities. For individuals with severe motor disabilities, who may not be able to perf...