Decoding EEG Rhythms During Action Observation, Motor Imagery, and Execution for Standing and Sitting
Autor: | Suppakorn Tammajarung, Nopparada Mingchinda, Subhas Chandra Mukhopadhyay, Pitshaporn Leelaarporn, Poramate Manoonpong, Phairot Autthasan, Theerawit Wilaiprasitporn, Rattanaphon Chaisaen, Narin Kunaseth |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
Signal Processing (eess.SP)
FOS: Computer and information sciences Computer science Speech recognition medicine.medical_treatment Computer Science - Human-Computer Interaction Electromyography Electroencephalography action observation Sitting 01 natural sciences Human-Computer Interaction (cs.HC) Motor imagery motor imagery FOS: Electrical engineering electronic engineering information engineering medicine Electrical and Electronic Engineering Electrical Engineering and Systems Science - Signal Processing movement-related cortical potentials Instrumentation Brain–computer interface Rehabilitation medicine.diagnostic_test 010401 analytical chemistry Electrooculography 0104 chemical sciences event-related desynchronization and synchronization Sensorimotor rhythm Brain-computer interfaces |
Zdroj: | Chaisaen, R, Autthasan, P, Mingchinda, N, Leelaarporn, P, Kunaseth, N, Tammajarung, S, Manoonpong, P, Mukhopadhyay, S C & Wilaiprasitporn, T 2020, ' Decoding EEG Rhythms during Action Observation, Motor Imagery, and Execution for Standing and Sitting ', I E E E Sensors Journal, vol. 20, no. 22, pp. 13776-13786 . https://doi.org/10.1109/JSEN.2020.3005968 |
DOI: | 10.1109/JSEN.2020.3005968 |
Popis: | Event-related desynchronization and synchronization (ERD/S) and movement-related cortical potential (MRCP) play an important role in brain-computer interfaces (BCI) for lower limb rehabilitation, particularly in standing and sitting. However, little is known about the differences in the cortical activation between standing and sitting, especially how the brain's intention modulates the pre-movement sensorimotor rhythm as they do for switching movements. In this study, we aim to investigate the decoding of continuous EEG rhythms during action observation (AO), motor imagery (MI), and motor execution (ME) for the actions of standing and sitting. We developed a behavioral task in which participants were instructed to perform both AO and MI/ME in regard to the transitioning actions of sit-to-stand and stand-to-sit. Our results demonstrated that the ERD was prominent during AO, whereas ERS was typical during MI at the alpha band across the sensorimotor area. A combination of the filter bank common spatial pattern (FBCSP) and support vector machine (SVM) for classification was used for both offline and classifier testing analyses. The offline analysis indicated the classification of AO and MI providing the highest mean accuracy at 82.73$\pm$2.54\% in the stand-to-sit transition. By applying the classifier testing analysis, we demonstrated the higher performance of decoding neural intentions from the MI paradigm in comparison to the ME paradigm. These observations led us to the promising aspect of using our developed tasks based on the integration of both AO and MI to build future exoskeleton-based rehabilitation systems. in press |
Databáze: | OpenAIRE |
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