EEG Characteristic Comparison of Motor Imagery Between Supernumerary and Inherent Limb: Sixth-Finger MI Enhances the ERD Pattern and Classification Performance

Adding supernumerary robotic limbs (SRLs) to humans and controlling them directly through the brain are main goals for movement augmentation. However, it remains uncertain whether neural patterns different from the traditional inherent limbs motor imagery (MI) can be extracted, which is essential for high-dimensional control of external devices. In this work, we established a MI neo-framework consisting of novel supernumerary robotic sixth-finger MI (SRF-MI) and traditional right-hand MI (RH-MI) paradigms and validated the distinctness of EEG response patterns between two MI tasks for the first time. Twenty-four subjects were recruited for this experiment involving three mental tasks. Event-related spectral perturbation was adopted to supply details about event-related desynchronization (ERD). Activation region, intensity and response time (RT) of ERD were compared between SRF-MI and RH-MI tasks. Three classical classification algorithms were utilized to verify the separability between different mental tasks. And genetic algorithm aims to select optimal combination of channels for neo-framework. A bilateral sensorimotor and prefrontal modulation was found during the SRF-MI task, whereas in RH-MI only contralateral sensorimotor modulation was exhibited. The novel SRF-MI paradigm enhanced ERD intensity by a maximum of 117% in prefrontal area and 188% in the ipsilateral somatosensory-association cortex. And, a global decrease of RT was exhibited during SRF-MI tasks compared to RH-MI. Classification results indicate well separable performance among different mental tasks (88.1% maximum for 2-class and 88.2% maximum for 3-class). This work demonstrated the difference between the SRF-MI and RH-MI paradigms, widening the control bandwidth of the BCI system.

Authors

Institutions

Publication Details

Journal
IEEE Journal of Biomedical and Health Informatics
Published
2024-09-02
DOI
https://doi.org/10.1109/jbhi.2024.3452701
Citations
7
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
2.40

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

EEG Characteristic Comparison of Motor Imagery Between Supernumerary and Inherent Limb: Sixth-Finger MI Enhances the ERD Pattern and Classification Performance

Yujian Zhang, Shuaifei Huang, Dong Ming, Xingwei An et al.
7 citations
IEEE Journal of Biomedical and Health Informatics
EEG and Brain-Computer Interfaces
2.40
article

EEG Characteristic Comparison of Motor Imagery Between Supernumerary and Inherent Limb: Sixth-Finger MI Enhances the ERD Pattern and Classification Performance

Yujian Zhang, Shuaifei Huang, Dong Ming, Xingwei An, Zhuang Wang, Shiyin Qiu, Yuan Liu, Huimin Huang
article en
7 citations

Abstract

Adding supernumerary robotic limbs (SRLs) to humans and controlling them directly through the brain are main goals for movement augmentation. However, it remains uncertain whether neural patterns different from the traditional inherent limbs motor imagery (MI) can be extracted, which is essential for high-dimensional control of external devices. In this work, we established a MI neo-framework consisting of novel supernumerary robotic sixth-finger MI (SRF-MI) and traditional right-hand MI (RH-MI) paradigms and validated the distinctness of EEG response patterns between two MI tasks for the first time. Twenty-four subjects were recruited for this experiment involving three mental tasks. Event-related spectral perturbation was adopted to supply details about event-related desynchronization (ERD). Activation region, intensity and response time (RT) of ERD were compared between SRF-MI and RH-MI tasks. Three classical classification algorithms were utilized to verify the separability between different mental tasks. And genetic algorithm aims to select optimal combination of channels for neo-framework. A bilateral sensorimotor and prefrontal modulation was found during the SRF-MI task, whereas in RH-MI only contralateral sensorimotor modulation was exhibited. The novel SRF-MI paradigm enhanced ERD intensity by a maximum of 117% in prefrontal area and 188% in the ipsilateral somatosensory-association cortex. And, a global decrease of RT was exhibited during SRF-MI tasks compared to RH-MI. Classification results indicate well separable performance among different mental tasks (88.1% maximum for 2-class and 88.2% maximum for 3-class). This work demonstrated the difference between the SRF-MI and RH-MI paradigms, widening the control bandwidth of the BCI system.

IEEE Journal of Biomedical and Health InformaticsVol. 28(12)
Tianjin University of Sport (CN), Tianjin University (CN), Tianjin Medical University (CN)
National Natural Science Foundation of China, State Key Laboratory of Mechanical System and Vibration
Openalex Percentile: Top 11%
EEG and Brain-Computer Interfaces
2.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.