AIMC Topic: Cerebral Palsy
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A randomized, cross-over trial comparing the effect of innovative robotic gait training and functional clinical therapy in children with cerebral palsy; a protocol to test feasibility.
Contemporary clinical trials
Jan 17, 2023
PURPOSE: Robotic gait training is relatively new in the world of pediatric rehabilitation. Preliminary feasibility studies and case reports include stationary robot-assisted treadmill training. Mobile robotic gait trainers hold greater promise for in...
Use of Robot-Assisted Gait Training in Pediatric Patients with Cerebral Palsy in an Inpatient Setting-A Randomized Controlled Trial.
Sensors (Basel, Switzerland)
Dec 16, 2022
Robot-assisted gait training (RAGT) provides a task-based support of walking using exoskeletons. Evidence shows moderate, but positive effects in the therapy of patients with cerebral palsy (CP). This study investigates the impact of RAGT on walking ...
Efficacy of Robot-Assisted Gait Therapy Compared to Conventional Therapy or Treadmill Training in Children with Cerebral Palsy: A Systematic Review with Meta-Analysis.
Sensors (Basel, Switzerland)
Dec 16, 2022
BACKGROUND: Motor, gait and balance disorders reduce functional capabilities for activities of daily living in children with cerebral palsy (CP). Robot-assisted gait therapy (RAGT) is being used to complement conventional therapy (CT) or treadmill th...
A deep-learning approach for automatically detecting gait-events based on foot-marker kinematics in children with cerebral palsy-Which markers work best for which gait patterns?
PloS one
Oct 13, 2022
Neuromotor pathologies often cause motor deficits and deviations from typical locomotion, reducing the quality of life. Clinical gait analysis is used to effectively classify these motor deficits to gain deeper insights into resulting walking behavio...
Development and Validation of a Deep Learning Method to Predict Cerebral Palsy From Spontaneous Movements in Infants at High Risk.
JAMA network open
Jul 1, 2022
IMPORTANCE: Early identification of cerebral palsy (CP) is important for early intervention, yet expert-based assessments do not permit widespread use, and conventional machine learning alternatives lack validity.
The effect of robotic rehabilitation on posture and trunk control in non-ambulatory cerebral palsy.
Assistive technology : the official journal of RESNA
May 5, 2022
The purpose of this study was to investigate the effects of a combined robot-assisted gait training (RAGT) with standard physiotherapy (PT) on trunk control and posture in non-ambulatory children with cerebral palsy (CP). This nonrandomized, controll...
Performance of Deep Learning Models in Forecasting Gait Trajectories of Children with Neurological Disorders.
Sensors (Basel, Switzerland)
Apr 13, 2022
Forecasted gait trajectories of children could be used as feedforward input to control lower limb robotic devices, such as exoskeletons and actuated orthotic devices (e.g., Powered Ankle Foot Orthosis-PAFO). Several studies have forecasted healthy ga...
Humanoid Robot Based Platform to Evaluate the Efficacy of Using Inertial Sensors for Spasticity Assessment in Cerebral Palsy.
IEEE journal of biomedical and health informatics
Jan 17, 2022
Spasticity is commonly present in individuals with cerebral palsy (CP) and manifests itself as shaky movements, muscle tightness and joint stiffness. Accurate and objective measurement of spasticity is investigated using inertial measurement unit (IM...
The Effects of Over-Ground Robot-Assisted Gait Training for Children with Ataxic Cerebral Palsy: A Case Report.
Sensors (Basel, Switzerland)
Nov 26, 2021
Poor balance and ataxic gait are major impediments to independent living in ataxic cerebral palsy (CP). Robot assisted-gait training (RAGT) has been shown to improve the postural balance and gait function in children with CP. However, there is no rep...
Computer-Aided Diagnosis of Children with Cerebral Palsy under Deep Learning Convolutional Neural Network Image Segmentation Model Combined with Three-Dimensional Cranial Magnetic Resonance Imaging.
Journal of healthcare engineering
Nov 10, 2021
In this paper, we analyzed the application value and effect of deep learn-based image segmentation model of convolutional neural network (CNN) algorithm combined with 3D brain magnetic resonance imaging (MRI) in diagnosis of cerebral palsy in childre...
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