AI Medical Compendium Journal:
Gait & posture

Showing 1 to 10 of 49 articles

A machine learning approach to real-time calculation of joint angles during walking and running using self-placed inertial measurement units.

Gait & posture
BACKGROUND: Inter-segment joint angles can be obtained from inertial measurement units (IMUs); however, accurate 3D joint motion measurement, which requires sensor fusion and signal processing, sensor alignment with segments and joint axis calibratio...

Predicting lower body joint moments and electromyography signals using ground reaction forces during walking and running: An artificial neural network approach.

Gait & posture
BACKGROUND: This study leverages Artificial Neural Networks (ANNs) to predict lower limb joint moments and electromyography (EMG) signals from Ground Reaction Forces (GRF), providing a novel perspective on human gait analysis. This approach aims to e...

Two-dimensional identification of lower limb gait features based on the variational modal decomposition of sEMG signal and convolutional neural network.

Gait & posture
BACKGROUND: Gait feature recognition is crucial to improve the efficiency and coordination of exoskeleton assistance. The recognition methods based on surface electromyographic (sEMG) signals are popular. However, the recognition accuracy of these me...

Distinguishing the activity of flexor digitorum brevis and soleus across standing postures with deep learning models.

Gait & posture
BACKGROUND: Electromyographic (EMG) recordings indicate that both the flexor digitorum brevis and soleus muscles contribute significantly to the control of standing balance, However, less is known about the adjustments in EMG activity of these two mu...

Machine learning model identifies patient gait speed throughout the episode of care, generating notifications for clinician evaluation.

Gait & posture
INTRODUCTION: The advent of digital and mobile health innovations, especially use of wearables for passive data collection, allows remote monitoring and creates an abundance of data. For this information to be interpretable, machine learning (ML) pro...

Improving trunk posture control in children with CP through a cable-driven robotic hippotherapy: A randomized controlled feasibility study.

Gait & posture
BACKGROUND: Many children with cerebral palsy (CP) show impairments in trunk posture control, one crucial factor contributing to impairments in gait and arm manipulation.

Machine learning applied to gait analysis data in cerebral palsy and stroke: A systematic review.

Gait & posture
BACKGROUND: Among neurological pathologies, cerebral palsy and stroke are the main contributors to walking disorders. Machine learning methods have been proposed in the recent literature to analyze gait data from these patients. However, machine lear...

The effects of Robot-assisted gait training and virtual reality on balance and gait in stroke survivors: A randomized controlled trial.

Gait & posture
BACKGROUND: Stroke survivors often experience balance and gait problems, which can affect their quality of life and independence in daily living activities. Robot-assisted gait training, such as Lokomat with virtual reality, has been found to be effe...

Assessment of a novel deep learning-based marker-less motion capture system for gait study.

Gait & posture
BACKGROUND: Marker-less systems based on digital video cameras and deep learning for gait analysis could have a deep impact in clinical routine. A recently developed system has shown promising results in terms of joint center position but has not bee...

Diagnostic value of a vision-based intelligent gait analyzer in screening for gait abnormalities.

Gait & posture
BACKGROUND: Early detection of gait abnormalities is critical for preventing severe injuries in future falls. The timed up and go (TUG) test is a commonly used clinical gait screening test; however, the interpretation of its results is limited to the...