AI Medical Compendium Topic:
Gait

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Artificial Intelligence-Assisted motion capture for medical applications: a comparative study between markerless and passive marker motion capture.

Computer methods in biomechanics and biomedical engineering
We aimed to determine whether artificial intelligence (AI)-assisted markerless motion capture software is useful in the clinical medicine and rehabilitation fields. Currently, it is unclear whether the AI-assisted markerless method can be applied to ...

Effect of the Hybrid Assistive Limb on the Gait Pattern for Cerebral Palsy.

Medicina (Kaunas, Lithuania)
Cerebral palsy (CP) is the most frequent childhood motor disability. Achieving ambulation or standing in children with CP has been a major goal of physical therapy. Recently, robot-assisted gait training using the Hybrid Assistive Limb (HAL) has bee...

Locomotor and robotic assistive gait training for children with cerebral palsy.

Developmental medicine and child neurology
AIM: To determine if robotic assisted gait training (RAGT) using surface muscle electrical stimulation and locomotor training enhances mobility outcomes when compared to locomotor training alone in children with cerebral palsy (CP).

Predicting gait events from tibial acceleration in rearfoot running: A structured machine learning approach.

Gait & posture
BACKGROUND: Gait event detection of the initial contact and toe off is essential for running gait analysis, allowing the derivation of parameters such as stance time. Heuristic-based methods exist to estimate these key gait events from tibial acceler...

A Random Forest Machine Learning Framework to Reduce Running Injuries in Young Triathletes.

Sensors (Basel, Switzerland)
BACKGROUND: The running segment of a triathlon produces 70% of the lower limb injuries. Previous research has shown a clear association between kinematic patterns and specific injuries during running.

Breaking the ice to improve motor outcomes in patients with chronic stroke: a retrospective clinical study on neuromodulation plus robotics.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
BACKGROUND: Stroke is one of the main causes of impairment affecting daily activities and quality of life. There is a growing effort to potentiate the recovery of functional gait and to enable stroke patients to walk independently.

Wearable hip-assist robot modulates cortical activation during gait in stroke patients: a functional near-infrared spectroscopy study.

Journal of neuroengineering and rehabilitation
BACKGROUND: Gait dysfunction is common in post-stroke patients as a result of impairment in cerebral gait mechanism. Powered robotic exoskeletons are promising tools to maximize neural recovery by delivering repetitive walking practice.

Electromechanical-assisted training for walking after stroke.

The Cochrane database of systematic reviews
BACKGROUND: Electromechanical- and robot-assisted gait-training devices are used in rehabilitation and might help to improve walking after stroke. This is an update of a Cochrane Review first published in 2007 and previously updated in 2017.

Spiking neural state machine for gait frequency entrainment in a flexible modular robot.

PloS one
We propose a modular architecture for neuromorphic closed-loop control based on bistable relaxation oscillator modules consisting of three spiking neurons each. Like its biological prototypes, this basic component is robust to parameter variation but...