AIMC Topic: Gait Disorders, Neurologic

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Effect of Wearable Robot-Assisted Gait Training on Balance and Walking Ability in Subacute Stroke Patients.

American journal of physical medicine & rehabilitation
OBJECTIVE: This study investigated the effectiveness of wearable robot-assisted gait training compared to treadmill gait training for improving balance and walking ability in stroke patients.

Effects of robot-assisted gait training within 1 week after stroke onset on degree of gait independence in individuals with hemiparesis: a propensity score-matched analysis in a single-center cohort study.

Journal of neuroengineering and rehabilitation
BACKGROUND: Robot-assisted gait training (RAGT) is an effective method for treating gait disorders in individuals with stroke. However, no previous studies have demonstrated the effectiveness of RAGT in individuals with acute stroke. This study aimed...

Robot-Assisted Gait Training in Older Patients with Comorbid Conditions: A Pilot Study.

Experimental aging research
PURPOSE: This study aimed to evaluate the efficacy of robot-assisted gait training (RAGT) in older patients with neurological gait disorder accompanied by various comorbidities.

Can muscle synergies shed light on the mechanisms underlying motor gains in response to robot-assisted gait training in children with cerebral palsy?

Journal of neuroengineering and rehabilitation
BACKGROUND: Children with cerebral palsy (CP) often experience gait impairments. Robot-assisted gait training (RGT) has been shown to have beneficial effects in this patient population. However, clinical outcomes of RGT vary substantially from patien...

Machine learning techniques for independent gait recovery prediction in acute anterior circulation ischemic stroke.

Journal of neuroengineering and rehabilitation
OBJECTIVE: This study aimed to develop and validate a machine learning-based predictive model for gait recovery in patients with acute anterior circulation ischemic stroke.

Gait Video-Based Prediction of Severity of Cerebellar Ataxia Using Deep Neural Networks.

Movement disorders : official journal of the Movement Disorder Society
BACKGROUND: Pose estimation algorithms applied to two-dimensional videos evaluate gait disturbances; however, a few studies have used this method to evaluate ataxic gait.

A Deep Learning-Based Framework Oriented to Pathological Gait Recognition with Inertial Sensors.

Sensors (Basel, Switzerland)
Abnormal locomotor patterns may occur in case of either motor damages or neurological conditions, thus potentially jeopardizing an individual's safety. Pathological gait recognition (PGR) is a research field that aims to discriminate among different ...

Computer model for gait assessments in Parkinson's patients using a fuzzy inference model and inertial sensors.

Artificial intelligence in medicine
Patients with Parkinson's disease (PD) in the moderate and severe stages can present several walk alterations. They can show slow movements and difficulty initiating, varying, or interrupting their gait; freezing; short steps; speed changes; shufflin...

Real-Time Freezing of Gait Prediction and Detection in Parkinson's Disease.

Sensors (Basel, Switzerland)
Freezing of gait (FOG) is a walking disturbance that can lead to postural instability, falling, and decreased mobility in people with Parkinson's disease. This research used machine learning to predict and detect FOG episodes from plantar-pressure da...