Analysis of Facial Electromyography Signals Using Linear and Non-Linear Features for Human-Machine Interface.

In this work, an attempt has been made to analyze the facial electromyography (facial EMG) signals using linear and non-linear features for the human-machine interface. Facial EMG signals are obtained from the publicly available, widely used DEAP dataset. Thirty-two healthy subjects volunteered for the establishment of this dataset.

Analysis of Heart Rate Variability in Normal and Diabetic ECG signals using Fragmentation Approach.

In this work, an attempt is made to quantify the dynamics of the heart rate variability timeseries in normal and diabetic population using fragmentation metrics. ECG signals recorded during deep breathing and head tilt up experiments are utilized for this study. The QRS-wave of ECG is extracted using the Pan Tompkins Algorithm.

Analysis of biceps brachii sEMG signal using Multiscale Fuzzy Approximate Entropy.

In this work, an attempt has been made to differentiate sEMG signals under muscle fatigue and non-fatigue conditions using multiscale features. Signals are recorded from biceps brachii muscle of 50 normal adults during repetitive dynamic contractions. After preprocessing, the signal is divided into six segments, out of which first and last segments are considered for this analysis.

Analysis Of SEMG Signal Complexity Associated with Fatigue Conditions in Biceps Brachii Muscle using Multiscale Approximate Entropy.

Muscle fatigue is a neuromuscular condition which causes a decline in muscle performance. Surface electromyography (sEMG) signals are widely used to evaluate muscle fatigue and these signals are highly complex in nature. To address this, advanced signal processing techniques are necessary.

Multiscale feature based analysis of surface EMG signals under fatigue and non-fatigue conditions.

In this work, an attempt has been made to differentiate sEMG signals under muscle fatigue and non-fatigue conditions using multiscale features. Signals are recorded from biceps brachii muscle of 50 normal adults during repetitive dynamic contractions. After prescribed preprocessing, each signal is divided into six segments out of which first and last segments are considered in this analysis.