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Motion

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Performance of a Novel Muscle Synergy Approach for Continuous Motion Estimation on Untrained Motion.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
When applying continuous motion estimation (CME) model based on sEMG to human-robot system, it is inevitable to encounter scenarios in which the motions performed by the user are different from the motions in the training stage of the model. It has b...

Improving Image Quality and Diagnostic Performance of CCTA in Patients with Challenging Heart Rate Conditions using a Deep Learning-based Motion Correction Algorithm.

Current medical imaging
OBJECTIVE: Challenging HR conditions, such as elevated Heart Rate (HR) and Heart Rate Variability (HRV), are major contributors to motion artifacts in Coronary Computed Tomography Angiography (CCTA). This study aims to assess the impact of a deep lea...

Magnetic motors in interphases: Motion control and integration in soft robots.

Biointerphases
Magnetic motors are a class of out-of-equilibrium particles that exhibit controlled and fast motion overcoming Brownian fluctuations by harnessing external magnetic fields. The advances in this field resulted in motors that have been used for differe...

Trajectory Analysis in Single-Particle Tracking: From Mean Squared Displacement to Machine Learning Approaches.

International journal of molecular sciences
Single-particle tracking is a powerful technique to investigate the motion of molecules or particles. Here, we review the methods for analyzing the reconstructed trajectories, a fundamental step for deciphering the underlying mechanisms driving the m...

Comprehensive modeling of corkscrew motion in micro-/nano-robots with general helical structures.

Nature communications
Micro-/nano-robots (MNRs) have impressive potential in minimally invasive targeted therapeutics through blood vessels, which has disruptive impact to improving human health. However, the clinical use of MNRs has yet to happen due to intrinsic limitat...

Deep learning applications for quantitative and qualitative PET in PET/MR: technical and clinical unmet needs.

Magma (New York, N.Y.)
We aim to provide an overview of technical and clinical unmet needs in deep learning (DL) applications for quantitative and qualitative PET in PET/MR, with a focus on attenuation correction, image enhancement, motion correction, kinetic modeling, and...

Conceptualization of Cloud-Based Motion Analysis and Navigation for Wearable Robotic Applications.

Sensors (Basel, Switzerland)
The behavior of pedestrians in a non-constrained environment is difficult to predict. In wearable robotics, this poses a challenge, since devices like lower-limb exoskeletons and active orthoses need to support different walking activities, including...

Visually guided swarm motion coordination via insect-inspired small target motion reactions.

Bioinspiration & biomimetics
Despite progress developing experimentally-consistent models of insect in-flight sensing and feedback for individual agents, a lack of systematic understanding of the multi-agent and group performance of the resulting bio-inspired sensing and feedbac...

MR Cranial Bone Imaging: Evaluation of Both Motion-Corrected and Automated Deep Learning Pseudo-CT Estimated MR Images.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: CT imaging exposes patients to ionizing radiation. MR imaging is radiation free but previously has not been able to produce diagnostic-quality images of bone on a timeline suitable for clinical use. We developed automated moti...

SISMIK for Brain MRI: Deep-Learning-Based Motion Estimation and Model-Based Motion Correction in k-Space.

IEEE transactions on medical imaging
MRI, a widespread non-invasive medical imaging modality, is highly sensitive to patient motion. Despite many attempts over the years, motion correction remains a difficult problem and there is no general method applicable to all situations. We propos...