Physics-Informed Deep Learning for Musculoskeletal Modeling: Predicting Muscle Forces and Joint Kinematics from Surface EMG

Engineering, Electrical Engineering, Information Science, Computer Science, Automation, Artificial Intelligence, Medicine, Orthopedics, Medical Laboratory Science, Medical Imaging, Life Sciences, Bioengineering,
physics-informed   deep learning   musculoskeletal modeling   EMG   muscle forces   joint kinematics  

Musculoskeletal models have been widely used in biomechanical analysis because they can estimate motion variables that are difficult to measure directly in living organisms, such as muscle forces and joint moments. Traditional physics-driven computational musculoskeletal models can explain the dynamic interactions between neural inputs to muscles, ...

Uncovering the Neural Mechanisms of Inter-Hemispheric Balance Restoration in Chronic Stroke through EMG-Driven Robot Hand Training: Insights from Dynamic Causal Modeling

Uncovering the Neural Mechanisms of Inter-Hemispheric Balance Restoration in Chronic Stroke through EMG-Driven Robot Hand Training: Insights from Dynamic Causal Modeling

Engineering, Electrical Engineering, Information Science, Automation, Medicine, Basic Medical Sciences, Neurology, Medical Imaging, Life Sciences, Bioengineering,
EMG-driven   robot hand training   stroke rehabilitation   neural networks   dynamic causal modeling   upper limb function recovery  

Revealing the Neuromechanism of Interhemispheric Balance Restoration in Chronic Stroke Patients through EMG-driven Robot Hand Training: Insights from Dynamic Causal Modeling Stroke is a common cause of disability, with most stroke survivors suffering from upper limb paralysis. The consequences of upper limb functional impairment can persist for ove...

Wavelet-Based Temporal-Spectral-Attention Correlation Coefficient for Motor Imagery EEG Classification

Engineering, Electrical Engineering, Information Science, Computer Science, Artificial Intelligence, Medicine, Basic Medical Sciences, Neurology, Medical Imaging, Life Sciences, Bioengineering,
brain-computer interface   motor imagery   EEG channel attention   temporal-spectral attention   wavelet transform   correlation coefficient  

Brain-Computer Interface (BCI) technology has rapidly developed in recent years and is considered a cutting-edge technology that allows external devices to be controlled directly by the brain without the need for peripheral nerves and muscles. Particularly in the application of Motor Imagery Electroencephalography (MI-EEG), BCI technology has shown...

Magnetoencephalography-Derived Oscillatory Microstate Patterns Across Lifespan: The Cambridge Centre for Ageing and Neuroscience Cohort

Medicine, Psychiatry, Geriatrics, Neurology, Medical Imaging, Life Sciences, Biophysics,
machine learning   microstates   healthy aging   alpha  

Application of Magnetoencephalography (MEG) to Analyze Changes in Whole-Brain Oscillatory Microstate Patterns Across the Lifespan: Cambridge Centre for Aging and Neuroscience Cohort Study Research Background With the increasing seriousness of the aging population problem, understanding the neurophysiological changes during the aging process becomes...

The Cortical Neurophysiological Signature of Amyotrophic Lateral Sclerosis

Medicine, Neurology, Medical Imaging, Life Sciences, Immunology, Biophysics,
Amyotrophic Lateral Sclerosis   Motor Neuron Disease   GABAergic Interneuronal Circuits   Frequency Band Analysis   Electromagnetic Neuroimaging  

Analysis of Cortical Neurophysiological Characteristics of ALS and Its Potential as a Biomarker Background Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease that affects adults, characterized by a gradual loss of the integrity of the brain, spinal cord, and peripheral motor system. Although clinical and genetic studies have reveale...