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Found 5 papers, 2 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.
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.
Systematic Comparison of the Influence of Different Data Preprocessing Methods on the Performance of Gait Classifications Using Machine Learning
Therefore, the aim of this analysis is to compare different combinations of commonly applied data preprocessing steps and test their effects on the classification performance of gait patterns.
Explaining the Unique Nature of Individual Gait Patterns with Deep Learning
Machine learning (ML) techniques such as (deep) artificial neural networks (DNN) are solving very successfully a plethora of tasks and provide new predictive models for complex physical, chemical, biological and social systems.
