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Performance of a Deep-Learning Neural Network Model in Assessing Skeletal Maturity on Pediatric Hand Radiographs.

Radiology
Purpose To compare the performance of a deep-learning bone age assessment model based on hand radiographs with that of expert radiologists and that of existing automated models. Materials and Methods The institutional review board approved the study....

Hand Rehabilitation Robotics on Poststroke Motor Recovery.

Behavioural neurology
The recovery of hand function is one of the most challenging topics in stroke rehabilitation. Although the robot-assisted therapy has got some good results in the latest decades, the development of hand rehabilitation robotics is left behind. Existin...

EMG-Based Estimation of Limb Movement Using Deep Learning With Recurrent Convolutional Neural Networks.

Artificial organs
A novel model based on deep learning is proposed to estimate kinematic information for myoelectric control from multi-channel electromyogram (EMG) signals. The neural information of limb movement is embedded in EMG signals that are influenced by all ...

Home-based hand rehabilitation with a robotic glove in hemiplegic patients after stroke: a pilot feasibility study.

Topics in stroke rehabilitation
OBJECTIVE: To evaluate the feasibility and safety of home rehabilitation of the hand using a robotic glove, and, in addition, its effectiveness, in hemiplegic patients after stroke.

Pronation and supination analysis based on biomechanical signals from Parkinson's disease patients.

Artificial intelligence in medicine
In this work, a fuzzy inference model to evaluate hands pronation/supination exercises during the MDS-UPDRS motor examination is proposed to analyze different extracted features from the bio-mechanical signals acquired from patients with Parkinson's ...

A new hand-eye calibration approach for fracture reduction robot.

Computer assisted surgery (Abingdon, England)
OBJECTIVE: The hand-eye calibration is used to determine the transformation between the end-effector and the camera marker of the robot. But the robot movement in traditional method would be time-consuming, inaccurate and even unavailable in some con...

The Combined Effects of Adaptive Control and Virtual Reality on Robot-Assisted Fine Hand Motion Rehabilitation in Chronic Stroke Patients: A Case Study.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Robot-assisted therapy is regarded as an effective and reliable method for the delivery of highly repetitive training that is needed to trigger neuroplasticity following a stroke. However, the lack of fully adaptive assist-as-needed control of the ro...

Context-dependent adaptation improves robustness of myoelectric control for upper-limb prostheses.

Journal of neural engineering
OBJECTIVE: Dexterous upper-limb prostheses are available today to restore grasping, but an effective and reliable feed-forward control is still missing. The aim of this work was to improve the robustness and reliability of myoelectric control by usin...

Usability testing of a developed assistive robotic system with virtual assistance for individuals with cerebral palsy: a case study.

Disability and rehabilitation. Assistive technology
This paper presents a novel application of an assistive robotic system with virtual assistance to enhance manual performance of individuals with cerebral palsy. Cerebral palsy affects one's voluntary motor movements resulting in limited opportunities...

Bayesian geodesic path for human motor control.

Neural networks : the official journal of the International Neural Network Society
Despite a near-infinite number of possible movement trajectories, our body movements exhibit certain invariant features across individuals; for example, when grasping a cup, individuals choose an approximately linear path from the hand to the cup. Ba...