A survey of human gait-based artificial intelligence applications
We performed an electronic database search of published works from 2012 to mid-2021 that
focus on human gait studies and apply machine learning techniques. We identified six key …
focus on human gait studies and apply machine learning techniques. We identified six key …
Interpretability of input representations for gait classification in patients after total hip arthroplasty
Many machine learning models show black box characteristics and, therefore, a lack of
transparency, interpretability, and trustworthiness. This strongly limits their practical …
transparency, interpretability, and trustworthiness. This strongly limits their practical …
GaitRec, a large-scale ground reaction force dataset of healthy and impaired gait
The quantification of ground reaction forces (GRF) is a standard tool for clinicians to quantify
and analyze human locomotion. Such recordings produce a vast amount of complex data …
and analyze human locomotion. Such recordings produce a vast amount of complex data …
A sco** review of applications of artificial intelligence in kinematics and kinetics of ankle sprains-current state-of-the-art and future prospects
Background Despite the existence of evidence-based rehabilitation strategies that address
biomechanical deficits, the persistence of recurrent ankle problems in 70% of patients with …
biomechanical deficits, the persistence of recurrent ankle problems in 70% of patients with …
Deep learning-based multimodal abnormal gait classification using a 3D skeleton and plantar foot pressure
Classification of pathological gaits has an important role in finding a weakened body part
and diagnosing a disease. Many machine learning-based approaches have been proposed …
and diagnosing a disease. Many machine learning-based approaches have been proposed …
Systematic comparison of the influence of different data preprocessing methods on the performance of gait classifications using machine learning
Human movements are characterized by highly non-linear and multi-dimensional
interactions within the motor system. Therefore, the future of human movement analysis …
interactions within the motor system. Therefore, the future of human movement analysis …
Explainable machine learning in human gait analysis: A study on children with cerebral palsy
This work investigates the effectiveness of various machine learning (ML) methods in
classifying human gait patterns associated with cerebral palsy (CP) and examines the …
classifying human gait patterns associated with cerebral palsy (CP) and examines the …
Explaining machine learning models for clinical gait analysis
Machine Learning (ML) is increasingly used to support decision-making in the healthcare
sector. While ML approaches provide promising results with regard to their classification …
sector. While ML approaches provide promising results with regard to their classification …
Real-world measurements of ground reaction forces of normal gait of young adults wearing various footwear
For years, researchers have been recognizing patterns in gait for purposes of medical
diagnostics, rehabilitation, and biometrics. A method for observing gait is to measure ground …
diagnostics, rehabilitation, and biometrics. A method for observing gait is to measure ground …
Hybrid Deep Neural Network Framework Combining Skeleton and Gait Features for Pathological Gait Recognition
Human skeleton data obtained using a depth camera have been used for pathological gait
recognition to support doctor or physician diagnosis decisions. Most studies for skeleton …
recognition to support doctor or physician diagnosis decisions. Most studies for skeleton …