AIMC Topic: Upper Extremity

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Vein segmentation and visualization of upper and lower extremities using convolution neural network.

Biomedizinische Technik. Biomedical engineering
OBJECTIVES: The study focused on developing a reliable real-time venous localization, identification, and visualization framework based upon deep learning (DL) self-parametrized Convolution Neural Network (CNN) algorithm for segmentation of the venou...

Multivariate analysis of the kinematics of an upper limb rehabilitation robot.

Acta of bioengineering and biomechanics
The purpose of this work is to present a multivariate analysis of the kinematics of an upper limb rehabilitation robot. Comparing multiple concepts of kinematic chains makes it possible to identify advantages and disadvantages and, as a consequence,...

Upper extremity contact pressure measurement in robot-assisted pelvic surgery.

Journal of robotic surgery
Upper extremity complications are often a problem in robot-assisted pelvic surgery (RAPS) with the lithotomy-Trendelenburg position (LT-position). This study focused on upper extremity contact pressure (UEP) and examined the relationship between UEP ...

Portable robots for upper-limb rehabilitation after stroke: a systematic review and meta-analysis.

Annals of medicine
BACKGROUND: Robot-assisted upper-limb rehabilitation has been studied for many years, with many randomised controlled trials (RCTs) investigating the effects of robotic-assisted training on affected limbs. The current trend directs towards end-effect...

ATST-Net: A method to identify early symptoms in the upper and lower extremities of PD.

Medical engineering & physics
Bradykinesia, a core symptom of motor disorders in Parkinson's disease (PD), is a major criterion for screening early PD patients in clinical practice. Currently, many studies have proposed automatic assessment schemes for bradykinesia in PD. However...

Socially Assistive Robot for Stroke Rehabilitation: A Long-Term in-the-Wild Pilot Randomized Controlled Trial.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Socially assistive robots (SARs) have been suggested as a platform for post-stroke training. It is not yet known whether long-term interaction with a SAR can lead to an improvement in the functional ability of individuals post-stroke. The aim of this...

The limitations of automatically generated curricula for continual learning.

PloS one
In many applications, artificial neural networks are best trained for a task by following a curriculum, in which simpler concepts are learned before more complex ones. This curriculum can be hand-crafted by the engineer or optimised like other hyperp...

Unsupervised robot-assisted rehabilitation after stroke: feasibility, effect on therapy dose, and user experience.

Journal of neuroengineering and rehabilitation
BACKGROUND: Unsupervised robot-assisted rehabilitation is a promising approach to increase the dose of therapy after stroke, which may help promote sensorimotor recovery without requiring significant additional resources and manpower. However, the un...

Patient's Healthy-Limb Motion Characteristic-Based Assist-As-Needed Control Strategy for Upper-Limb Rehabilitation Robots.

Sensors (Basel, Switzerland)
The implementation of a progressive rehabilitation training model to promote patients' motivation efforts can greatly restore damaged central nervous system function in patients. Patients' active engagement can be effectively stimulated by assist-as-...

Within-Session Reliability of fNIRS in Robot-Assisted Upper-Limb Training.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Functional near-infrared spectroscopy (fNIRS) seems opportune for neurofeedback in robot-assisted rehabilitation training due to its noninvasive, less physical restriction, and no electromagnetic disturbance. Previous research has proved the cross-se...