AIMC Topic: Motion

Clear Filters Showing 121 to 130 of 879 articles

High-Stroke, High-Output-Force, Fabric-Lattice Artificial Muscles for Soft Robots.

Advanced materials (Deerfield Beach, Fla.)
Artificial muscles, providing safe and close interaction between humans and machines, are essential in soft robotics. However, their insufficient deformation, output force, or configurability usually limits their applications. Herein, this work prese...

Use of deep learning to segment bolus during videofluoroscopic swallow studies.

Biomedical physics & engineering express
Anatomical segmentations generated using artificial intelligence (AI) have the potential to significantly improve video fluoroscopic swallow study (VFS) analysis. AI segments allow for various metrics to be determined without additional time constrai...

Variable stiffness soft robotic gripper: design, development, and prospects.

Bioinspiration & biomimetics
The advent of variable stiffness soft robotic grippers furnishes a conduit for exploration and manipulation within uncharted, non-structured environments. The paper provides a comprehensive review of the necessary technologies for the configuration d...

Controlled synchronization of a vibrating screen driven by two motors based on improved sliding mode controlling method.

PloS one
With a requirement of miniaturization in modern vibrating screens, the vibration synchronization method can no longer meet the process demand, so the controlled synchronization method is introduced in the vibrating screen to achieve zero phase error ...

Joint Reconfiguration after Failure for Performing Emblematic Gestures in Humanoid Receptionist Robot.

Sensors (Basel, Switzerland)
This study proposed a strategy for a quick fault recovery response when an actuator failure problem occurred while a humanoid robot with 7-DOF anthropomorphic arms was performing a task with upper body motion. The objective of this study was to devel...

Low-variance Forward Gradients using Direct Feedback Alignment and momentum.

Neural networks : the official journal of the International Neural Network Society
Supervised learning in deep neural networks is commonly performed using error backpropagation. However, the sequential propagation of errors during the backward pass limits its scalability and applicability to low-powered neuromorphic hardware. There...

Evaluation of functional tests performance using a camera-based and machine learning approach.

PloS one
The objective of this study is to evaluate the performance of functional tests using a camera-based system and machine learning techniques. Specifically, we investigate whether OpenPose and any standard camera can be used to assess the quality of the...

AdaSAM: Boosting sharpness-aware minimization with adaptive learning rate and momentum for training deep neural networks.

Neural networks : the official journal of the International Neural Network Society
Sharpness aware minimization (SAM) optimizer has been extensively explored as it can generalize better for training deep neural networks via introducing extra perturbation steps to flatten the landscape of deep learning models. Integrating SAM with a...

Real-time motion management in MRI-guided radiotherapy: Current status and AI-enabled prospects.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
MRI-guided radiotherapy (MRIgRT) is a highly complex treatment modality, allowing adaptation to anatomical changes occurring from one treatment day to the other (inter-fractional), but also to motion occurring during a treatment fraction (intra-fract...

Monitoring Active Patient Participation During Robotic Rehabilitation: Comparison Between a Robot-Based Metric and an EMG-Based Metric.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
While rehabilitation robots present a much-needed solution to improving early mobilization therapy in demanding clinical settings, they also present new challenges and opportunities in patient monitoring. Aside from the fundamental challenge of quant...