AIMC Topic: Movement

Clear Filters Showing 871 to 880 of 1059 articles

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...

Analysis of In-Home Movement Patterns for Depression Assessment in Older Adults - A Feasibility Study.

Studies in health technology and informatics
Depression significantly impacts the wellbeing of older Australians, posing considerable challenges to their overall quality of life. This study aimed to detect in-home movement patterns of participants that could be indicative of depressive states. ...

Attention-Aware Non-Rigid Image Registration for Accelerated MR Imaging.

IEEE transactions on medical imaging
Accurate motion estimation at high acceleration factors enables rapid motion-compensated reconstruction in Magnetic Resonance Imaging (MRI) without compromising the diagnostic image quality. In this work, we introduce an attention-aware deep learning...

[Voluntary and Adaptive Control Strategy for Ankle Rehabilitation Robot].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
The control strategy of rehabilitation robots should not only adapt to patients with different levels of motor function but also encourage patients to participate voluntarily in rehabilitation training. However, existing control strategies usually co...

Real-time Classification of Diverse Reaching Motions Using RMS and Discrete Wavelet Transform Energy Values from EMG Signals for Human Assistive Robots.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
With advancing technology, human assistive robots have been developed to enhance daily efficiency for users. Focusing on the reaching motions of the upper limb, this study aims to propose a motion classification method based on electromyographic (EMG...