Fig 1.
Schematic representation of experimental protocol and configuration.
(A) Sitting posture of the subject during the neurophysiological recording (B) The timeline points to the temporal reference for various tasks initiated with a ‘relax’ state that started at 0s, “+” visual cue at 10s for the subject to be ‘alert’, at 15s ‘ Reach’ cue indicated the subject to reach for the object placed in the front of the subject, and at 20s ‘Object’ cue appeared to indicate the subject to grasp the object, followed by “arrow” cue at 25s to lift the bottle, consequently followed by another ‘arrow’ cue at 30s that suggested the direction in which the object was to be moved and a ‘down arrow’ cue at 35s that suggested to place the grasped object back at rest. (C) EEG Data processing analysis workflow involved the filtering of raw signal, epoch extraction, feature extraction and building a machine learning model based on processed features.
Fig 2.
Feature ranking of surface EEG signals from central electrodes C3 and C4 showed accuracy depended on α sub-band 8.62 Hz and β sub-bands 14, 15, 19, 20, 21, 22 Hz while classifying movement (gray) against premovement (light grey/white) class labels (Class 0 is premovement, Class 1 is grasped movement).
Fig 3.
Temporal correlations across MRCPs from EEG electrode regions differentiate movement tasks.
(A) Correlation measures for central regions (C3-C4) electrode pair has indicated higher correlation (r = 1) for movement and ‘alert’ condition tasks whereas for a lower correlation measure (r) of 0.3 was estimated for the ‘relax’ task., P4-F4 electrode pair has indicated a measure of 0.5 for premovement and relax tasks and 0.6 for movement task. The electrode combination of C3-C4 for movement and “alert” condition had higher correlation measure compared to P4-C4, P4-F4, P4-C3, C4-F4, C4-F3 combinations. (Blue circle–“relax task”, Red square–“movement task”, Green triangle–“alert/premovement” task (B)Correlation measure of various electrode pair combinations was statistically compared for the tasks using t-test. and C3-C4 electrode combination were significantly different for “relax” and movement tasks indicating central region electrodes could be decisive in differentiating “relax” and grasped movement tasks. (C) potential amplitude decreases in 296% from premovement to movement in the central electrode regions (D) Parietal regions has shown 164% decreased in amplitude (E) Frontal regions has shown 133% decrease and (F) Occipital regions has shown 230% decrease in potential amplitude before 500ms to onset of movement. (Green line–“premovement task” and Red Line indicates “movement” task).
Fig 4.
Increased post movement activity by rebound β and γ oscillations.
(A) α/μ oscillations show 26% decrease from initiation to grasp movement 29% decrease from relax to grasp movement and 16% decrease from grasp movement to post movement in the central electrode regions. 14% and 10% decrease in beta and gamma oscillations from initiation to grasp movement and rebound increment of 14% beta and 20% gamma for post grasp movement. (B) Frontal region has shown 7% increase of alpha oscillations from grasp to grasped movement and 8% increase post movement (C)Parietal region electrodes has shown 21% and 20% decrease from initiation to grasp movement and rebound increment of 4% and 12% post movement. (For inter subject variability see S3 Fig in S1 File).
Fig 5.
Significant left and right movement in male and female subjects in the central region electrodes among β & γ oscillations.
(A, B, C) Variability between the male and female subjects for the tasks of premovement (PM) left movement (LM) and right movement (RM). (A) α oscillations for premovement task of male subjects (2.609 ± 2.025) female subjects (3.091 ± 2.245) have not shown any statistical significance similarly for left movement and right movement (p value >0.9999), (B) β and (C) γ oscillations have shown significant differences were presented with p value < 0.0001 (12 sample trials of Male subjects, 12 sample trials of female subjects).
Fig 6.
Machine learning-based model performance.
(A) Training accuracies for central regions on using SVM had outperformed MLP and DT for left and right hand movement (SVM: Support Vector machine; SVM-(P3): support vector machine polynomial degree 3, SVM (rbf): Support vector machine—radial basis function, MLP: Multilayer Perceptron) (B) Testing accuracy performance with central regions SVMs has performed similarly with 50% accuracy for premovement & movement, and 80% accuracy for left and right hand movement classification DT has performed moderately for left vs right hand movement.