The aim of this research program is to develop and validate a smartphone app-based digital
measurement concept that:
Objectively quantifies the severity of Parkinson's Disease (PD) related vocal and speech
Accurately and sensitively identifies vocal and speech abnormalities associated with the
prodromal stage of PD.
Although multiple approaches to this problem have been proposed in addition to commercially
available speech analytics platforms, there is currently no established measure which
incorporates the disparate aspects of affected speech to fully characterize Parkinson's
symptom progression, particularly in the prodromal phase.
The measurement concept being evaluated in the present study utilizes a custom
smartphone-based speech assessment tool to extract multiple hypothesis-driven acoustic
features from patient speech in a real-life environment. The resultant features will be used
to train a pair of supervised machine learning models to predict clinical PD symptom severity
scores, and to distinguish prodromal PD patients from both healthy matched controls and PD
patients in more advanced phases of disease progression.
If you are confirmed eligible after full screening, you will be required to understand and sign the informed consent if you decide to enroll in the study. Once enrolled you may be asked to make scheduled visits over a period of time.
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