AI Medical Compendium Topic:
Movement

Clear Filters Showing 571 to 580 of 999 articles

The ideal couch tracking system-Requirements and evaluation of current systems.

Journal of applied clinical medical physics
INTRODUCTION: Intrafractional motion can cause substantial uncertainty in precision radiotherapy. Traditionally, the target volume is defined to be sufficiently large to cover the tumor in every position. With the robotic treatment couch, a real-time...

Neuromuscular actuation of biohybrid motile bots.

Proceedings of the National Academy of Sciences of the United States of America
The integration of muscle cells with soft robotics in recent years has led to the development of biohybrid machines capable of untethered locomotion. A major frontier that currently remains unexplored is neuronal actuation and control of such muscle-...

2D ultrasound imaging based intra-fraction respiratory motion tracking for abdominal radiation therapy using machine learning.

Physics in medicine and biology
We have previously developed a robotic ultrasound imaging system for motion monitoring in abdominal radiation therapy. Owing to the slow speed of ultrasound image processing, our previous system could only track abdominal motions under breath-hold. T...

Multi optimized SVM classifiers for motor imagery left and right hand movement identification.

Australasian physical & engineering sciences in medicine
EEG signal can be a good alternative for disabled persons who cannot perform actions or perform them improperly. Brain computer interface (BCI) is an attractive technology which permits control and interaction with a computer or a machine using EEG s...

A Multi-Branch 3D Convolutional Neural Network for EEG-Based Motor Imagery Classification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
One of the challenges in motor imagery (MI) classification tasks is finding an easy-handled electroencephalogram (EEG) representation method which can preserve not only temporal features but also spatial ones. To fully utilize the features on various...

A Multi-Mode Rehabilitation Robot With Magnetorheological Actuators Based on Human Motion Intention Estimation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Lower extremity paralysis has become common in recent years, and robots have been developed to help patients recover from it. This paper presents such a robotic system that allows for two working modes, the robot-active mode and human-active mode. Th...

Feedback delays can enhance anticipatory synchronization in human-machine interaction.

PloS one
Research investigating the dynamics of coupled physical systems has demonstrated that small feedback delays can allow a dynamic response system to anticipate chaotic behavior. This counterintuitive phenomenon, termed anticipatory synchronization, has...

A Natural-language-based Visual Query Approach of Uncertain Human Trajectories.

IEEE transactions on visualization and computer graphics
Visual querying is essential for interactively exploring massive trajectory data. However, the data uncertainty imposes profound challenges to fulfill advanced analytics requirements. On the one hand, many underlying data does not contain accurate ge...

An automatic behavior recognition system classifies animal behaviors using movements and their temporal context.

Journal of neuroscience methods
Animals can perform complex and purposeful behaviors by executing simpler movements in flexible sequences. It is particularly challenging to analyze behavior sequences when they are highly variable, as is the case in language production, certain type...

Clustering Neural Patterns in Kernel Reinforcement Learning Assists Fast Brain Control in Brain-Machine Interfaces.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Neuroprosthesis enables the brain control on the external devices purely using neural activity for paralyzed people. Supervised learning decoders recalibrate or re-fit the discrepancy between the desired target and decoder's output, where the correct...