AI Medical Compendium Topic:
Movement

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Deep learning-based detection of bacterial swarm motion using a single image.

Gut microbes
Motility is a fundamental characteristic of bacteria. Distinguishing between swarming and swimming, the two principal forms of bacterial movement, holds significant conceptual and clinical relevance. Conventionally, the detection of bacterial swarmin...

Passive ankle and hindfoot kinematics within a robot-driven tibial movement envelope.

Journal of biomechanics
Accurate description of individual bone kinematics is essential for understanding individual foot and ankle joint function and interactions. While invasive and noninvasive techniques, including robotic simulators, have advanced the direct measurement...

Neuroadaptive Admittance Control for Human-Robot Interaction With Human Motion Intention Estimation and Output Error Constraint.

IEEE transactions on cybernetics
Human-robot interaction (HRI) is a crucial component in the field of robotics, and enabling faster response, higher accuracy, as well as smaller human effort, is essential to improve the efficiency, robustness, and applicability of HRI-driven tasks. ...

The analysis of motion recognition model for badminton player movements using machine learning.

Scientific reports
This study aims to comprehensively analyze and classify the badminton players' swing actions by combining the theoretical frameworks of quantum mechanics and machine learning. A badminton stroke recognition method based on Quantum Convolutional Neura...

GCN-Transformer: Graph Convolutional Network and Transformer for Multi-Person Pose Forecasting Using Sensor-Based Motion Data.

Sensors (Basel, Switzerland)
Multi-person pose forecasting involves predicting the future body poses of multiple individuals over time, involving complex movement dynamics and interaction dependencies. Its relevance spans various fields, including computer vision, robotics, huma...

Ethnic dance movement instruction guided by artificial intelligence and 3D convolutional neural networks.

Scientific reports
This study aims to explore the potential application of artificial intelligence in ethnic dance action instruction and achieve movement recognition by utilizing the three-dimensional convolutional neural networks (3D-CNNs). In this study, the 3D-CNNs...

Reducing Upper-Limb Muscle Effort with Model-Based Gravity Compensation During Robot-Assisted Movement.

Sensors (Basel, Switzerland)
Clinical research has demonstrated that stroke patients benefit from active participation during robot-assisted training. However, the weight of the arm impedes the execution of tasks and movements due to the functional disability. The purpose of thi...

AI-based human whole-body posture-prediction in continuous load reaching/leaving activities.

Journal of biomechanics
Determining worker's body posture during load handling activities is the first step toward assessing and managing occupational risk of musculoskeletal injuries. Traditional approaches for the measurement of body posture are impractical in real work s...

A machine learning approach to real-time calculation of joint angles during walking and running using self-placed inertial measurement units.

Gait & posture
BACKGROUND: Inter-segment joint angles can be obtained from inertial measurement units (IMUs); however, accurate 3D joint motion measurement, which requires sensor fusion and signal processing, sensor alignment with segments and joint axis calibratio...

Conditional Generative Models for Simulation of EMG During Naturalistic Movements.

IEEE transactions on neural networks and learning systems
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,...