The aim of BSF’s Parkinson’s Disease (PD) study is to improve the early detection of vestibular and cognitive changes in patients at risk for PD and potentially other neurodegenerative disorders. Shifting the focus of early detection to measurements of global cognitive functions during everyday life provides a direct match with the symptoms that define this disease.
BSF is currently conducting a study to validate a non-invasive medical diagnostic methodology for detection. We are collaborating with our European partners to validate an early detection multimodal sensor system that combines Body Sensor Networks (BSN) and speech analysis to collect simultaneous data streams for movement and cognitive states of PD. The validation of this BSN technology for Parkinson’s Disease will enable future research in monitoring movement, speech, and possibly other biomarkers for effective early detection. Data collection and analysis of cognitive mind states through linguistic output may yield potential new biomarkers for the detection of PD as well.
The study protocol uses a multiple task paradigm (standing, moving, speaking) to observe attentional demands of balance, joint stability and arm trajectory in PD patients and healthy controls. Our experimental design will allow the collection of multiple data streams simultaneously from tasks that are commonly found in everyday life. The study observes the effect of Parkinson’s on vestibular capacity to allocate attention to standing joint stability, balance and postural controls, which are sensitive measures for predicting an onset of the disease.