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Machine learning for identifying patterns in human gait: Classification of age and clinical groups

Classification of Neurological Patients to Identify Fallers Based on Spatial-Temporal Gait Characteristics Measured by a Wearable Device

Gait Analysis with Wearables Can Accurately Classify Fallers from Non-Fallers: A Step toward Better Management of Neurological Disorders

Long-term unsupervised mobility assessment in movement disorders

The detection of age groups by dynamic gait outcomes using machine learning approaches

The use of machine learning to identify gait patterns for aging

Automatic recognition of age-related gait patterns with machine learning

Automatic recognition of gait patterns with machine learning

Gait analysis and adaptations: using new ideas to tackle old problems in gait classification and training

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