AIMC Topic: Movement
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An EEG-EMG dataset from a standardized reaching task for biomarker research in upper limb assessment.
Scientific data
May 20, 2025
This work describes a dataset containing high-density EEG (hd-EEG) and surface electromiography (sEMG) to capture neuromechanical responses during a reaching task with and without the assistance of an upper-limb exoskeleton. It was designed to explor...
Reinforcement Learning-Driven Path Generation for Ankle Rehabilitation Robot Using Musculoskeletal-Informed Energy Optimization.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 12, 2025
In rehabilitation robotics, optimizing energy consumption and high interaction forces is essential to prevent unnecessary muscle fatigue and excessive joint loading as they often cause an inefficient trajectory planning and disrupt natural movement p...
Continuous Joint Kinematics Prediction Using GAT-LSTM Framework Based on Muscle Synergy and Sparse sEMG.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 8, 2025
sEMG signals hold significant potential for motion prediction, with promising applications in areas such as rehabilitation, sports training, and human-computer interaction. However, achieving robust prediction accuracy remains a critical challenge, a...
A Novel 3D Approach with a CNN and Swin Transformer for Decoding EEG-Based Motor Imagery Classification.
Sensors (Basel, Switzerland)
May 5, 2025
Motor imagery (MI) is a crucial research field within the brain-computer interface (BCI) domain. It enables patients with muscle or neural damage to control external devices and achieve movement functions by simply imagining bodily motions. Despite t...
Conditional Generative Models for Simulation of EMG During Naturalistic Movements.
IEEE transactions on neural networks and learning systems
May 2, 2025
Numerical models of electromyography (EMG) signals have provided a huge contribution to our fundamental understanding of human neurophysiology and remain a central pillar of motor neuroscience and the development of human-machine interfaces. However,...
SMANet: A Model Combining SincNet, Multi-Branch Spatial-Temporal CNN, and Attention Mechanism for Motor Imagery BCI.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Apr 29, 2025
Building a brain-computer interface (BCI) based on motor imagery (MI) requires accurately decoding MI tasks, which poses a significant challenge due to individual discrepancy among subjects and low signal-to-noise ratio of EEG signals. We propose an ...
Machine learning-based analysis of defensive strategies in basketball using player movement data.
Scientific reports
Apr 22, 2025
The analysis of basketball strategies has traditionally relied on manual observation and limited data. As tracking technology progresses, there is potential for applying Artificial Intelligence specifically to strategy, delivering insights into defen...
Review of sEMG for Exoskeleton Robots: Motion Intention Recognition Techniques and Applications.
Sensors (Basel, Switzerland)
Apr 13, 2025
The global aging trend is becoming increasingly severe, and the demand for life assistance and medical rehabilitation for frail and disabled elderly people is growing. As the best solution for assisting limb movement, guiding limb rehabilitation, and...
Automatic video analysis of countermovement jump performance using a single uncalibrated camera.
Journal of biomechanics
Apr 12, 2025
The countermovement jump (CMJ) assessment is widely employed for monitoring sports performance, traditionally relying on heavy and expensive force plates to extract performance variables like jump height and peak force. Inertial measurement unit (IMU...
Learning-based 3D human kinematics estimation using behavioral constraints from activity classification.
Nature communications
Apr 11, 2025
Inertial measurement units offer a cost-effective, portable alternative to lab-based motion capture systems. However, measuring joint angles and movement trajectories with inertial measurement units is challenging due to signal drift errors caused by...
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