Area of research
Biomedical Engineering · Cognitive Neuroscience
Research interest
Research interests include Muscle activation and electromyography studies, EEG and Brain-Computer Interfaces, Neuroscience and Neural Engineering, and Advanced Sensor and Energy Harvesting Materials.
Time-Frequency distributions of heart sound signals: A Comparative study using convolutional neural networks
The Effect of Signal Duration on the Classification of Heart Sounds: A Deep Learning Approach
On the Applications of EMG Sensors and Signals
Determination of Optimum Segmentation Schemes for Pattern Recognition-Based Myoelectric Control: A Multi-Dataset Investigation
Chronic high-dose beetroot juice supplementation improves time trial performance of well-trained cyclists in normoxia and hypoxia
Multiday EMG-Based Classification of Hand Motions with Deep Learning Techniques
Multiday Evaluation of Techniques for EMG-Based Classification of Hand Motions
Online mapping of EMG signals into kinematics by autoencoding
Stacked Sparse Autoencoders for EMG-Based Classification of Hand Motions: A Comparative Multi Day Analyses between Surface and Intramuscular EMG
The effect of arm position on classification of hand gestures with intramuscular EMG
Effect of threshold values on the combination of EMG time domain features: Surface versus intramuscular EMG
The effect of time on EMG classification of hand motions in able-bodied and transradial amputees
Distinct patterns of variation in the distribution of knee pain
Psychophysical Evaluation of Subdermal Electrical Stimulation in Relation to Prosthesis Sensory Feedback
On the robustness of real-time myoelectric control investigations: a multiday Fitts’ law approach