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Motor Skills

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Effects of robotically modulating kinematic variability on motor skill learning and motivation.

Journal of neurophysiology
It is unclear how the variability of kinematic errors experienced during motor training affects skill retention and motivation. We used force fields produced by a haptic robot to modulate the kinematic errors of 30 healthy adults during a period of p...

Evaluation of HEXORR Tone Assistance Mode Against Spring Assistance.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Robots are a promising tool for rehabilitation, and research suggests combining assistance with subject participation to maintain motivation and engagement. In this study, we compare two different types of robotic assistance for hand rehabilitation: ...

Sub-processes of motor learning revealed by a robotic manipulandum for rodents.

Behavioural brain research
Rodent models are widely used to investigate neural changes in response to motor learning. Usually, the behavioral readout of motor learning tasks used for this purpose is restricted to a binary measure of performance (i.e. "successful" movement vs. ...

Toward biologically realistic models of the motor system.

Neuron
In this issue of Neuron, Chiappa et al. describe how neural networks can be trained to perform complex hand motor skills. A key to their approach is curriculum learning, breaking learning into stages, leading to good control.

Substituting some unassisted practice with robotic guidance: Assessing the feasibility of auditory-cued mixed practice for music-based interventions.

NeuroRehabilitation
BACKGROUND: There is equivocal evidence regarding the effectiveness of robotic guidance on the (re)learning of voluntary motor skills. Robotic guidance can improve the performance of continuous/ tracking skills, although being seldom more effective t...

Co-designing hardware and control for robot hands.

Science robotics
Policy gradient methods can be used for mechanical and computational co-design of robot manipulators.

A 10-item Fugl-Meyer Motor Scale Based on Machine Learning.

Physical therapy
OBJECTIVE: The Fugl-Meyer motor scale (FM) is a well-validated measure for assessing upper extremity and lower extremity motor functions in people with stroke. The FM contains numerous items (50), which reduces its clinical usability. The purpose of ...

A Machine Learning Approach to Assess Injury Risk in Elite Youth Football Players.

Medicine and science in sports and exercise
PURPOSE: To assess injury risk in elite-level youth football (soccer) players based on anthropometric, motor coordination and physical performance measures with a machine learning model.

Characterizing Individual Differences in a Dynamic Stabilization Task Using Machine Learning.

Aerospace medicine and human performance
: Being able to identify individual differences in skilled motor learning during disorienting conditions is important for spaceflight, military aviation, and rehabilitation.: Blindfolded subjects ( = 34) were strapped into a device that behaved like ...

Effect of robot-assisted gait training on motor functions in adolescent and young adult patients with bilateral spastic cerebral palsy: A randomized controlled trial.

NeuroRehabilitation
BACKGROUND: Robot-assisted gait training (RAGT) allows an intensive gait training in patients with cerebral palsy (CP). There are few evidences on the effectiveness of RAGT in adults with CP.