Exploring the relationship between everyday speech and motor symptoms of Parkinson's disease as prerequisite analysis for tool development

Statistical methods to correlate multiple variables has long been applied in many fields of research. This paper applies such techniques to Unified Parkinson's Disease Rating Scale (UPDRS) data to examine relationships between speech and movement variables. This data analysis uses select speech and motor variables to explore Parkinson's Disease (PD) symptom correlations. The analysis is a prerequisite study of speech and movement symptoms prior to collecting data from everyday living in PD patients using Body Sensor Networks (BSN) and AI methods for analyzing speech and movement. This data analysis is a first level examination of the current gold standards for measuring speech and movement in PD patients. © 2013 IEEE.