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This study aims to compare brain activity differences under the motor imagery-brain-computer interface (MI-BCI), motor imagery (MI), and resting (REST) paradigms through EEG microstate and functional connectivity (FC) analysis, providing a theoretical basis for applying MI-BCI in the rehabilitation of children with cerebral palsy (CP). This study included 30 subjects aged 4-6 years with GMFCS II-III grade, diagnosed with CP and classified as spastic diplegia. They sequentially completed EEG signal acquisition under REST, MI, and MI-BCI conditions. Clustering analysis was used to analyze EEG microstates and extract EEG microstate temporal parameters. Additionally, the strength of brain FC in different frequency bands was analyzed to compare the differences under various conditions. Four microstate classes (A-D) were identified to best explain the datasets of three groups. Compared to REST, the average duration and coverage rate of microstate D under MI and MI-BCI significantly increased (P < 0.05), while their frequency and the coverage rate and frequency of microstate A decreased. Compared to MI, the average duration of microstate C under MI-BCI significantly decreased (P < 0.05), while the frequency of microstate B significantly increased (P < 0.05). Additionally, the transition probability results showed that other microstates under REST had a higher transition probability to microstate A, while under MI and MI-BCI, other microstates had a higher transition probability to microstate D. The brain network results revealed significant differences in brain network connectivity among REST, MI, and MI-BCI across different frequency bands. No FC differences were found between REST, MI, and MI-BCI in the α2 frequency band. In the δ and γ frequency bands, MI and MI-BCI both had greater inter-electrode connectivity strength than REST. In the θ frequency band, REST had greater inter-electrode connectivity strength than MI-BCI, while MI-BCI had greater inter-electrode connectivity strength than both REST and MI. In the α1 frequency band, MI-BCI had greater inter-electrode connectivity strength than REST, and in the β frequency band, MI-BCI had greater inter-electrode connectivity strength than MI. MI-BCI can significantly alter the brain activity patterns of children with CP, particularly by enhancing the activity intensity of EEG microstates related to attention, motor planning, and execution, as well as the brain FC strength in different frequency bands. It holds high application value in the lower limb motor rehabilitation of children with CP.
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http://dx.doi.org/10.1038/s41598-025-96946-z | DOI Listing |
Sci Rep
April 2025
Department of Rehabilitation Medicine, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
This study aims to compare brain activity differences under the motor imagery-brain-computer interface (MI-BCI), motor imagery (MI), and resting (REST) paradigms through EEG microstate and functional connectivity (FC) analysis, providing a theoretical basis for applying MI-BCI in the rehabilitation of children with cerebral palsy (CP). This study included 30 subjects aged 4-6 years with GMFCS II-III grade, diagnosed with CP and classified as spastic diplegia. They sequentially completed EEG signal acquisition under REST, MI, and MI-BCI conditions.
View Article and Find Full Text PDFISA Trans
September 2024
Department of Civil Engineering, Faculty of Engineering, Bursa Uludag University, Bursa, Turkey. Electronic address:
Spatially resolved capacitance-based stress self-sensing in unmodified concrete has been demonstrated. The spatial resolution is 45 mm in one dimension, which is in the direction of the capacitance measurement. Parallel coplanar component electrodes (aluminum, 5-mm wide), attached to the concrete using double-sided adhesive tape) separated by 45 mm are used to measure the in-plane capacitance in the direction perpendicular to the length of the electrodes.
View Article and Find Full Text PDFJ Neurosci Methods
April 2024
School of Information Science and Technology, Fudan University, Shanghai 200433, China; State Key Laboratory of Integrated Chips and Systems, Fudan University, Shanghai 201203, China; Greater Bay Area Institute of Precision Medicine, Guangzhou 511400, China. Electronic address:
Implantable neural stimulation is becoming increasingly popular for treating neurologically impaired patients, restoring neural functions which would otherwise be lost due to diseases or injuries. The charge balance of the stimulus pulses is of paramount importance for the long-term safety of the electrode-tissue interface. This paper presents a novel neurostimulator integrated circuit in which two novel charge balancing schemes are proposed.
View Article and Find Full Text PDFPhysiol Meas
October 2022
Laboratory for Engineering of the Neuromuscular System (LISiN), Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy.
. Recently, the use of EMG biofeedback to make subjects aware of the stabilizer activation associated with scapular retraction during exercise has been of interest, and challenges related to EMG detection have been addressed. Whether there is an optimal bipolar positioning that discriminates the stabilizer activation with retraction from a neutral scapular position during resistance exercises is an open issue that we address here by simultaneously mapping different positions using high-density surface electromyography (HD-sEMG).
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
July 2022
In functional electric stimulation, variables such as electrode size, shape, and inter-electrodes distance can produce different neural and functional responses. In this work, a computational model combining FEM and MRG axon models is implemented to replicate two experimental studies that compare the effect of changing inter-electrode distance when applying FES to induce knee flexion. One work affirms that the stronger torque happens for greater distances, while the other obtain its maximum at lower distances.
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