Stefano Sibille
Quantitative assessment of lower limb bradykinesia in Parkinson's disease patients using smartphone sensors.
Rel. Gabriella Olmo, Monica Visintin. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2018
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Abstract
In a perspective of evidence-based medicine, data from measurement systems, processed by data mining techniques, can provide quantitative measures that can make more objective the available clinical information and be an important aid for clinical decision making. This is the leitmotif of this project. In this Master Thesis work the focus is on motor symptoms of Parkinson's disease, in particular on bradykinesia (slowness of movement). The motivation is found in the need to have quantitative methods for the motor assessment of patients, in order to be able to monitor the daily fluctuations of the motor symptoms (alternate of phase ON and phase OFF).
In fact, the most used clinical evaluation scale, the MDS-UPDRS, in which the clinician is asked to assign a score between 0 and 4 according to the severity of the considered symptom, does not meet requirements of objectivity and repeatability
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