Article
Engineering, Electrical & Electronic
Shiqi Yang, Min Li, Jiale Wang
Summary: This article proposes a multimodal fusion strategy of EEG and sEMG based on graph theory to improve the accuracy and robustness of hand motion recognition. By considering the temporal signals of EEG and sEMG as the features of nodes and the functional connectivity as the weights of edges, the proposed approach achieves significantly higher accuracy than parallel fusion and single-modality models under abnormal states such as muscular fatigue and weakness.
IEEE SENSORS JOURNAL
(2022)
Article
Engineering, Biomedical
Jingyao Sun, Tianyu Jia, Zhibin Li, Chong Li, Linhong Ji
Summary: In this study, the concept of spatial-temporal CMC (STCMC) is proposed to improve the accuracy of corticomuscular coupling analysis. By combining delay compensation and spatial optimization, STCMC enhances the coherence significantly between brain and muscle signals and produces higher classification accuracy. Furthermore, STCMC provides more detailed brain topographical patterns, emphasizing the different roles between the contralateral and ipsilateral hemisphere.
JOURNAL OF NEURAL ENGINEERING
(2023)
Article
Engineering, Biomedical
Jinbiao Liu, Gansheng Tan, Yixuan Sheng, Yina Wei, Honghai Liu
Summary: This study developed a novel delay estimation method, RVC, to detect time delay between coupled neurophysiological signals. The results showed that RVC method was superior in estimating different time delays and had better optimization effect on MSC image compared to the CMCTL method. The RVC-based delay compensation also significantly optimized the MSC of specific regions.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
(2022)
Article
Biology
Binish Fatimah, Amit Singhal, Pushpendra Singh
Summary: Healthy sleep is crucial for the body's rejuvenation and overall health. Automated assessment of sleep disorders using EEG and other signals can improve classification accuracy. The proposed method allows for real-time and cost-effective continuous patient monitoring and feedback.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Neurosciences
Meaghan E. Spedden, Mikkel M. Beck, Timothy O. West, Simon F. Farmer, Jens B. Nielsen, Jesper Lundbye-Jensen
Summary: This study investigates the cortical mechanisms underlying visually guided steps and highlights the role of oscillatory communication in the parieto-frontal and corticomuscular network. The findings suggest that the brain utilizes coherence to flexibly fine-tune inter-regional communication during human stepping, contributing to the precision control of large-scale movements.
Article
Mathematics, Interdisciplinary Applications
Mirra Soundirarajan, Ondrej Krejcar, Hamidreza Namazi
Summary: This paper studies the coupling between brain and facial muscle activities through complexity-based analysis in auditory stimulation. The results indicate a strong correlation between the alterations of signal complexities and music, suggesting a coupling between the brain and facial muscle activities.
FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY
(2022)
Article
Clinical Neurology
Amina Coffey, Saroj Bista, Antonio Fasano, Teresa Buxo, Matthew Mitchell, Eileen Rose Giglia, Stefan Dukic, Matthew Fenech, Megan Barry, Andrew Wade, Mark Heverin, Muthuraman Muthuraman, Richard G. Carson, Madeleine Lowery, Orla Hardiman, Bahman Nasseroleslami
Summary: The study investigated the motor network connectivity in adult survivors of polio by analyzing the corticomuscular coherence during a pincer grip task. The results showed significant coherence in low gamma frequency bands in the frontal and parietal regions of polio survivors, suggesting a disease-related functional reorganisation of the cortical motor network, which has implications for other LMN conditions like SMA.
CLINICAL NEUROPHYSIOLOGY
(2021)
Article
Chemistry, Analytical
Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh, Ebrahim Ghaderpour
Summary: This paper proposes a novel method to remove muscle artifacts from EEG signals without distorting the information contained in them. It achieves better reconstruction quality and is fully automatic compared to other denoising techniques.
Article
Psychology, Biological
F. Zambolin, P. Duro Ocana, R. Goulding, A. Sanderson, M. Venturelli, G. Wood, J. McPhee, J. V. V. Parr
Summary: In this study, the corticomuscular mechanisms underlying blood flow occlusion (BFO) were investigated. The results showed that occlusion of non-exercising musculature suppressed electroencephalographic (EEG) alpha activity in the prefrontal cortex. On the other hand, occlusion of exercising musculature suppressed EEG alpha activity in central and posterior cortical regions and impaired brain-muscle communication and neuromuscular activation.
Article
Neurosciences
Johnny V. V. Parr, Liis Uiga, Ben Marshall, Greg Wood
Summary: The study examines the immediate effects of soccer heading on brain function and brain-muscle communication. The findings suggest that a short bout of soccer heading impairs cognitive function and disrupts neural processes associated with motor skill proficiency. Additionally, soccer heading induces corticomuscular hyperconnectivity, potentially indicating inefficient allocation of neuromuscular resources.
FRONTIERS IN HUMAN NEUROSCIENCE
(2023)
Article
Biotechnology & Applied Microbiology
Md Shafayet Hossain, Sakib Mahmud, Amith Khandakar, Nasser Al-Emadi, Farhana Ahmed Chowdhury, Zaid Bin Mahbub, Mamun Bin Ibne Reaz, Muhammad E. H. Chowdhury
Summary: This paper proposes a novel one-dimensional convolutional neural network (1D-CNN) called MultiResUNet3+ to remove physiological artifacts from electroencephalogram (EEG) signals. A publicly available dataset is used to train, validate, and test the proposed model along with four other 1D-CNN models. The results show that MultiResUNet3+ achieves the highest reduction in EOG and EMG artifacts compared to the other models.
BIOENGINEERING-BASEL
(2023)
Article
Biophysics
Ji-Soo Jeong, Mi Yu, Tae-Kyu Kwon
Summary: Lower limb exercise combined with whole body vibration stimulation improved postural stability, lower limb muscle activation, and brain activation in healthy elderly individuals. The squat posture group showed greater improvements in the TUG test and muscle activation analysis compared to the upright stance group, although there were no significant changes in the MMSE-DS results. EEG measurements indicated increased activity in certain brain regions for both groups, suggesting enhanced cognitive function.
JOURNAL OF MECHANICS IN MEDICINE AND BIOLOGY
(2021)
Article
Engineering, Biomedical
Ting Wang, Jianpeng Tang, Chenghao Wang, Donghui Yang, Jingqi Li, Wanzeng Kong, Xugang Xi
Summary: Music is widely used in neurorehabilitation for the recovery of motor function and emotional regulation. This study explores the effects of music stimuli on brain functional connectivity and corticomuscular coupling through physiological electrical signal analysis.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Instruments & Instrumentation
Yue Zhang, Weihai Chen, Chun-Liang Lin, Zhongcai Pei, Jianer Chen, Daming Wang
Summary: The study aims to describe the coupling relationship between EEG and sEMG through various analysis methods. By collecting data from healthy subjects and stroke patients, and using modified EEG algorithm and wavelet coherence analysis, the coherence between EEG and sEMG has been demonstrated. The results of this study have important theoretical implications for neurorehabilitation training and functional state evaluation of movement.
REVIEW OF SCIENTIFIC INSTRUMENTS
(2022)
Article
Neurosciences
Xugang Xi, Shaojun Pi, Yun-Bo Zhao, Huijiao Wang, Zhizeng Luo
Summary: This study reveals the interaction between the cortex and muscle during muscle fatigue through EEG and EMG signals, establishing an effective cortical-muscle network using graph theory and symbolic transfer entropy. Results show a series of dynamic changes in the cortical-muscle system during muscle fatigue.