AIMC Topic: Motor Activity
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Effects of device-assisted practice of activities of daily living in a close-to-normal pattern on upper extremity motor recovery in individuals with moderate to severe stroke: study protocol of a randomized control trial.
Trials
Jul 4, 2025
BACKGROUND: The majority of individuals with chronic stroke have residual upper extremity (UE) disability which they cite as their greatest barrier to recovery. Using orthoses, robotic devices, and functional electrical stimulation (FES) represent re...
Treatment Outcome
Recovery of Function
Robotics
Disability Evaluation
Double-Blind Method
Humans
Research Design
Severity of Illness Index
Time Factors
Motor Activity
Upper Extremity
Electric Stimulation Therapy
Stroke Rehabilitation
Clinical Protocols
Equipment Design
Stroke
Activities of Daily Living
Orthotic Devices
Paresis
Research on the evaluation and rehabilitation training system of upper limb motor function for poststroke patients based on artificial intelligence: a study protocol for a randomized controlled trial.
Trials
Jun 13, 2025
BACKGROUND: Stroke-induced upper limb dysfunction requires functional assessment and rehabilitation. The intelligent rehabilitation assessment and virtual reality training system for upper limb motor function in stroke can accurately and objectively ...
Machine learning and confirmatory factor analysis show that buprenorphine alters motor and anxiety-like behaviors in male, female, and obese C57BL/6J mice.
Journal of neurophysiology
Dec 30, 2024
Buprenorphine is an opioid approved for medication-assisted treatment of opioid use disorder. Used off-label, buprenorphine has been reported to contribute to the clinical management of anxiety. Although human anxiety is a highly prevalent disorder, ...
The effect of robot-assisted versus standard training on motor function following subacute rehabilitation after ischemic stroke - protocol for a randomised controlled trial nested in a prospective cohort (RoboRehab).
BMC neurology
Jul 4, 2024
BACKGROUND: Body weight unloaded treadmill training has shown limited efficacy in further improving functional capacity after subacute rehabilitation of ischemic stroke patients. Dynamic robot assisted bodyweight unloading is a novel technology that ...
A single-joint multi-task motor imagery EEG signal recognition method based on Empirical Wavelet and Multi-Kernel Extreme Learning Machine.
Journal of neuroscience methods
Apr 19, 2024
BACKGROUND: In the pursuit of finer Brain-Computer Interface commands, research focus has shifted towards classifying EEG signals for multiple tasks. While single-joint multitasking motor imagery provides support, distinguishing between EEG signals f...
Neonatal brain inflammation enhances methamphetamine-induced reinstated behavioral sensitization in adult rats analyzed with explainable machine learning.
Neurochemistry international
Apr 17, 2024
Neonatal brain inflammation produced by intraperitoneal (i.p.) injection of lipopolysaccharide (LPS) results in long-lasting brain dopaminergic injury and motor disturbances in adult rats. The goal of the present work is to investigate the effect of ...
DeepEthogram, a machine learning pipeline for supervised behavior classification from raw pixels.
eLife
Sep 2, 2021
Videos of animal behavior are used to quantify researcher-defined behaviors of interest to study neural function, gene mutations, and pharmacological therapies. Behaviors of interest are often scored manually, which is time-consuming, limited to few ...
Skilled reach training enhances robotic gait training to restore overground locomotion following spinal cord injury in rats.
Behavioural brain research
Aug 3, 2021
Rehabilitative training has been shown to improve motor function following spinal cord injury (SCI). Unfortunately, these gains are primarily task specific; where reach training only improves reaching, step training only improves stepping and stand t...
The CPGs for Limbed Locomotion-Facts and Fiction.
International journal of molecular sciences
May 30, 2021
The neuronal networks that generate locomotion are well understood in swimming animals such as the lamprey, zebrafish and tadpole. The networks controlling locomotion in tetrapods remain, however, still enigmatic with an intricate motor pattern requi...
Prediction of Motor Function in Stroke Patients Using Machine Learning Algorithm: Development of Practical Models.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
May 19, 2021
BACKGROUND: Machine learning (ML) techniques are being increasingly adopted in the medical field.
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