An ICA-EBM-Based sEMG Classifier for Recognizing Lower Limb Movements in Individuals With and Without Knee Pathology

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 26; no. 3; pp. 675 - 686
• Main Authors: Naik, Ganesh R., Selvan, S. Easter, Arjunan, Sridhar P., Acharyya, Amit, Kumar, Dinesh K., Ramanujam, Arvind, Nguyen, Hung T.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.03.2018
• Subjects: Algorithms; Biomechanical Phenomena; Discriminant Analysis; Electromyography; Electromyography - classification; Electromyography - statistics & numerical data; Entropy; Fisher score; Healthy Volunteers; Humans; independent component analysis; Knee; Knee Injuries - physiopathology; knee pathology; linear discriminant analysis; Lower Extremity - physiology; Lower Extremity - physiopathology; Male; Movement - physiology; Muscle, Skeletal - physiology; Muscles; Pathology; Pattern recognition; surface electromyography; Walking - physiology; Young Adult

Surface electromyography (sEMG) data acquired during lower limb movements has the potential for investigating knee pathology. Nevertheless, a major challenge encountered with sEMG signals generated by lower limb movements is the intersubject variability, because the signals recorded from the leg or...