학술논문

Criteria for event-related (de)synchronization detection and feature consistency for motor imagery-based neuromodulation
Document Type
Conference
Source
2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE) BIBE Bioinformatics and Bioengineering (BIBE), 2020 IEEE 20th International Conference on. :588-595 Oct, 2020
Subject
Bioengineering
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Electrodes
Pediatrics
Area measurement
Feature extraction
Electroencephalography
Indexes
Task analysis
motor imagery
feature selection
neuromodulation
event-related desynchronization
electroencephalography
Language
ISSN
2471-7819
Abstract
Self-modulation of brain signals related to motor imagery (MI) activity has been increasingly indicated to be beneficial for motor rehabilitation protocols. Appropriately incorporating the MI strategy requires ensuring the active involvement of the central nervous system. Under this context, seeking MIrelated features to be easily modulated by the user and that are recurrent between distinct MI sessions is a necessary and challenging task. This paper proposes a criterion to maximize the consistency of features from the electroencephalography signal between recording sessions performed at different days. To achieve this, we explore three distinct approaches to rank features related to MI’s underlying mental patterns - the event-related desynchronization (ERD) score, the ERD occurrence (EO) and the Fisher ratio- applied to a database of 3 healthy adults and 4 children with cerebral palsy. Overall, the healthy adults presented more consistent features for F-, FC- and C-labeled electrodes and the lower frequency bands for the EO and ERD score, and higher ranges for the Fisher ratio. For the children, results showed more variability but emphasis on specific spectral and spatial locations could also be observed individually. Hence, we claim that distinct ranking metrics may reflect different aspects of MI, but each one may be best for specific types of applications and subjects.