This study is concerned with the impact of speaking mode variabilities on speech recognition by surface electromyography (EMG). In EMG-based speech recognition, we capture the electric potentials of the human articulatory muscles by surface electrodes, so that the resulting signal can be used for speech processing. This enables the user to communicate silently, without uttering any sound. Previ...

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...

The proposed EMG signals analysis relies on the frequency domain where features of healthy EMG signal and myopathic EMG signals are analyzed and compared. Methodology described the relationship between the EMG signals and the properties of a contracting & myopathic muscle by analysing its power density spectrum. Periodogram Mean-Square Spectrum Estimate (PMSSE) of EMG Signal and the Power spect...

The analysis and classification of electromyography (EMG) signals are very important in order to detect some symptoms of diseases, prosthetic arm/leg control, and so on. In this study, an EMG signal was analyzed using bispectrum, which belongs to a family of higher-order spectra. An EMG signal is the electrical potential difference of muscle cells. The EMG signals used in the present study are ...

background: this paper proposes a new emotional stress assessment system using multi-modal bio-signals. electroencephalogram (eeg) is the reflection of brain activity and is widely used in clinical diagnosis and biomedical research. methods: we design an efficient acquisition protocol to acquire the eeg signals in five channels (fp1, fp2, t3, t4 and pz) and peripheral signals such as blood volu...

in current years, the application of biopotential signals has received a lot of attention in literature. one of these signals is an electromyogram (emg) generated by active muscles. surface emg (semg) signal is recorded over the skin, as the representative of the muscle activity. since its amplitude can be as low as 50 µv, it is sensitive to undesirable noise signals such as power‑line interfer...

BACKGROUND Ensemble Empirical Mode Decomposition (EEMD) has been popularised for single-channel Electromyography (EMG) signal processing as it can effectively extract the temporal information of the EMG time series. However, few papers examine the temporal and spatial characteristics across multiple muscle groups in relation to multichannel EMG signals. EXPERIMENT The experimental data was ob...

Electromyography (EMG) signals are becoming increasingly important in many applications, including clinical/biomedical, prosthesis or rehabilitation devices, human machine interactions, and more. However, noisy EMG signals are the major hurdles to be overcome in order to achieve improved performance in the above applications. Detection, processing and classification analysis in electromyography...