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Found 5 papers, 1 papers with code
Explaining machine learning models for age classification in human gait analysis
Machine learning (ML) models have proven effective in classifying gait analysis data, e. g., binary classification of young vs. older adults.
Explaining automated gender classification of human gait
State-of-the-art machine learning (ML) models are highly effective in classifying gait analysis data, however, they lack in providing explanations for their predictions.
Trustworthy Visual Analytics in Clinical Gait Analysis: A Case Study for Patients with Cerebral Palsy
Three-dimensional clinical gait analysis is essential for selecting optimal treatment interventions for patients with cerebral palsy (CP), but generates a large amount of time series data.
On the Explanation of Machine Learning Predictions in Clinical Gait Analysis
Machine learning (ML) is increasingly used to support decision-making in the healthcare sector.
Automatic Classification of Functional Gait Disorders
The aim of the study is twofold: (1) to investigate the suitability of stateof-the-art GRF parameterization techniques (representations) for the discrimination of functional gait disorders; and (2) to provide a first performance baseline for the automated classification of functional gait disorders for a large-scale dataset.
