2004 | OriginalPaper | Buchkapitel
Classifying the State of Parkinsonism by Using Electronic Force Platform Measures of Balance
verfasst von : Nicholas I. Bohnen, Marius G. Buliga, Gregory M. Constantine
Erschienen in: Classification, Clustering, and Data Mining Applications
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Several measures of balance obtained from quiet stance on an electronic force platform are described. These measures were found to discriminate patients with Parkinson’s disease (PD) from normal control subjects. First-degree relatives of patients with PD show greater variability on these measures. A primary goal is to develop sensitive measures that would be capable of identifying impaired balance in early stages of non-clinical PD. We developed a trinomial logistic model that classifies a subject as either normal, pre-parkinsonian, or parkinsonian taking as input the measures developed from the platform data.