Neuromechanical biomarkers for robotic neurorehabilitation
One of the current challenges for translational rehabilitation research is to develop the
strategies to deliver accurate evaluation, prediction, patient selection, and decision-making …
strategies to deliver accurate evaluation, prediction, patient selection, and decision-making …
Analysis of fluctuation patterns in emotional states using electrodermal activity signals and improved symbolic aggregate approximation
YR Veeranki, N Ganapathy… - Fluctuation and Noise …, 2022 - World Scientific
Analysis of fluctuations in electrodermal activity (EDA) signals is widely preferred for emotion
recognition. In this work, an attempt has been made to determine the patterns of fluctuations …
recognition. In this work, an attempt has been made to determine the patterns of fluctuations …
Muscle fatigue analysis by visualization of dynamic surface EMG signals using Markov transition field
D Sasidharan, G Venugopal… - 2022 44th Annual …, 2022 - ieeexplore.ieee.org
Muscle fatigue analysis is important in the diagnosis of neuromuscular diseases. Analysis of
surface electromyography (sEMG) signals by non-linear probabilistic approach is useful in …
surface electromyography (sEMG) signals by non-linear probabilistic approach is useful in …
Estimation of the continuous pronation–supination movement by using multichannel EMG signal features and Kalman filter: Application to control an exoskeleton
L Zhang, J Long, RG Zhao, H Cao… - … in bioengineering and …, 2022 - frontiersin.org
The Hill muscle model can be used to estimate the human joint angles during continuous
movement. However, adopting this model requires the knowledge of many parameters, such …
movement. However, adopting this model requires the knowledge of many parameters, such …
A proposal to analyze muscle dynamics under fatiguing contractions using surface Electromyography signals and fuzzy recurrence network features
D Sasidharan, V Gopinath… - Fluctuation and Noise …, 2023 - World Scientific
The analysis of surface electromyography (sEMG) signals is significant in the detection of
muscle fatigue. These signals exhibit a great degree of complexity, nonlinearity, and chaos …
muscle fatigue. These signals exhibit a great degree of complexity, nonlinearity, and chaos …
Complexity analysis of surface Electromyography signals under fatigue using Hjorth parameters and bubble entropy
D SASIDHARAN, G Venugopal… - Journal of Mechanics in …, 2023 - World Scientific
This work aims to analyze the complexity of surface electromyography (sEMG) signals under
muscle fatigue conditions using Hjorth parameters and bubble entropy (BE). Signals are …
muscle fatigue conditions using Hjorth parameters and bubble entropy (BE). Signals are …
Analysis of induced dynamic biceps EMG signal complexity using Markov transition networks
G Venugopal, D Sasidharan… - Biomedical Engineering …, 2024 - Springer
Purpose Surface electromyography (sEMG) is a non-invasive technique to characterize
muscle electrical activity. The analysis of sEMG signals under muscle fatigue play a crucial …
muscle electrical activity. The analysis of sEMG signals under muscle fatigue play a crucial …
[HTML][HTML] A new fractional fuzzy dispersion entropy and its application in muscle fatigue detection
B Hu, Y Wang, J Mu - Mathematical Biosciences and Engineering, 2024 - aimspress.com
Recently, fuzzy dispersion entropy (DispEn) has attracted much attention as a new nonlinear
dynamics method that combines the advantages of both DispEn and fuzzy entropy …
dynamics method that combines the advantages of both DispEn and fuzzy entropy …
Binary Classification of Mammograms Using Horizontal Visibility Graph
Breast carcinoma, the most common cancer in women across the world now accounts for
almost of new malignant tumor cases. Despite the high incidence rate, breast cancer …
almost of new malignant tumor cases. Despite the high incidence rate, breast cancer …