Quantification of Balance Deficits in Neurological Disorders using Wearable Sensors

This thesis discusses the challenges in assessing ataxia, a neurological disorder affecting voluntary movement. It introduces a novel approach combining supervised machine learning with inertial measurement units for diagnosis, extends cloud-based assessments through federated learning with deep learning, and proposes unsupervised machine learning for severity estimation.