Towards computerized diagnosis of neurological stance disorders: data mining and machine learning of posturography and sway

• Published in: Journal of neurology Vol. 266; no. Suppl 1; pp. 108 - 117
• Main Authors: Ahmadi, Seyed-Ahmad, Vivar, Gerome, Frei, Johann, Nowoshilow, Sergej, Bardins, Stanislav, Brandt, Thomas, Krafczyk, Siegbert
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2019; Springer Nature B.V
• Subjects: Adult; Artificial intelligence; Atrophy; Cerebellum; Classification; Cohort Studies; Data Mining - methods; Data processing; Diagnosis, Computer-Assisted - methods; Embedding; Female; Humans; Learning algorithms; Machine Learning; Male; Mapping; Medicine; Medicine & Public Health; Movement disorders; Nervous System Diseases - diagnosis; Nervous System Diseases - physiopathology; Neurodegenerative diseases; Neurological diseases; Neurology; Neuroradiology; Neurosciences; Nystagmus; Original Communication; Parkinson's disease; Polyneuropathy; Postural Balance - physiology; Rubber; Tremor; Vertigo; Visualization; Static posturography; Body sway; Neurological stance and gait disorders; Machine learning

We perform classification, ranking and mapping of body sway parameters from static posturography data of patients using recent machine-learning and data-mining techniques. Body sway is measured in 293 individuals with the clinical diagnoses of acute unilateral vestibulopathy (AVS, n  = 49), distal s...