AIMC Topic: Gait

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Classification of knee osteoarthritis severity using markerless motion capture and long short-term memory fully convolutional network.

Computers in biology and medicine
This study explored the integration of markerless motion capture and deep learning to classify knee osteoarthritis severity based on gait kinematics, providing an alternative to traditional assessment methods. We employed a Long Short-Term Memory Ful...

Your turn: At home turning angle estimation for Parkinson's disease severity assessment.

Artificial intelligence in medicine
People with Parkinson's Disease (PD) often experience progressively worsening gait, including changes in how they turn around, as the disease progresses. Existing clinical rating tools are not capable of capturing hour-by-hour variations of PD sympto...

Neural mechanisms underlying the improvement of gait disturbances in stroke patients through robot-assisted gait training based on QEEG and fNIRS: a randomized controlled study.

Journal of neuroengineering and rehabilitation
BACKGROUND: Robot-assisted gait training is more effective in improving lower limb function and walking ability in stroke patients compared to conventional rehabilitation, but the neural mechanisms remain unclear. This study aims to explore the effec...

Unsupervised learning reveals rapid gait adaptation after leg loss and regrowth in spiders.

The Journal of experimental biology
Many invertebrates voluntarily lose (autotomize) limbs during antagonistic encounters, and some regenerate functional replacements. Because limb loss can have severe consequences on individual fitness, it is likely subject to significant selective pr...

Prediction of future aging-related slow gait and its determinants with deep learning and logistic regression.

PloS one
BACKGROUND: Identification of accelerated aging and its biomarkers can lead to more timely therapeutic interventions and decision-making. Therefore, we sought to predict aging-related slow gait, a known predictor of accelerated aging, and its determi...

Study on the structural function and motion performance of pneumatic flexible tree-climbing robot.

PloS one
To enhance the adaptability of tree-climbing robots to changes in tree diameter and load capacity, an "I-shaped" pneumatic flexible tree - climbing robot was designed using self-developed pneumatic flexible joints and retractable needle anchors. The ...

O-GEST: Overground gait events detector using b-spline-based geometric models for marker-based and markerless analysis.

Journal of biomechanics
Accurate gait events detection is imperative for reliable assessment of normal and pathological gaits. However, this detection becomes challenging in the absence of force plates. Hence, this research introduces two geometric models integrated into an...

Development of machine learning models for gait-based classification of incomplete spinal cord injuries and cauda equina syndrome.

Scientific reports
Incomplete tetraplegia, incomplete paraplegia, and cauda equina syndrome are major neurological disorders that significantly reduce patients' quality of life, primarily due to impaired motor function and gait instability. Although conventional neurol...

Encoding flexible gait strategies in stick insects through data-driven inverse reinforcement learning.

Bioinspiration & biomimetics
Stick insects exhibit remarkable adaptive walking capabilities across diverse environments; however, the mechanisms underlying their gait transitions remain poorly understood. Although reinforcement learning (RL) has been employed to generate insect-...

A comparative study of ANN-based forward dynamics and inverse dynamics in human gait analysis.

Journal of biomechanics
This study investigates the similarities and differences in the analysis of human walking motion between the traditional inverse dynamics method and the forward dynamics method that employs an Artificial Neural Network (ANN)-based controller. Nine he...