Abstract
Telemonitoring of Parkinson’s Disease (PD) has attracted considerable research interest because of its potential to make a lasting, positive impact on the life of patients and their carers. Purpose-built devices have been developed that record various signals which can be associated with average PD symptom severity, as quantified on standard clinical metrics such as the Unified Parkinson’s Disease Rating Scale (UPDRS). Speech signals are particularly promising in this regard, because they can be easily recorded without the use of expensive, dedicated hardware. Previous studies have demonstrated replication of UPDRS to within less than 2 points of a clinical raters’ assessment of symptom severity, using high-quality speech signals collected using dedicated telemonitoring hardware. Here, we investigate the potential of using the standard voice-over-GSM (2G) or UMTS (3G) cellular mobile telephone networks for PD telemonitoring, networks that, together, have greater than 5 billion subscribers worldwide. We test the robustness of this approach using a simulated noisy mobile communication network over which speech signals are transmitted, and approximately 6000 recordings from 42 PD subjects. We show that UPDRS can be estimated to within less than 3.5 points difference from the clinical raters’ assessment, which is clinically useful given that the inter-rater variability for UPDRS can be as high as 4–5 UPDRS points. This provides compelling evidence that the existing voice telephone network has potential towards facilitating inexpensive, mass-scale PD symptom telemonitoring applications.
Highlights
Parkinson’s Disease (PD) is a chronic neurodegenerative disorder characterized by the progressive deterioration of motor function as well as the emergence of considerable non-motor problems [1]
We clarify that we used all weekly Unified Parkinson’s Disease Rating Scale (UPDRS) estimates derived using linear interpolation to present here because these are subsequently used as the ground truth for training and testing the statistical learners
The results in these two tables illustrate the changes in the univariate statistical association of the features with UPDRS and implicitly demonstrate the effect the noise and the data transmission channel have in terms of using speech signals to replicate PD symptom severity
Summary
Parkinson’s Disease (PD) is a chronic neurodegenerative disorder characterized by the progressive deterioration of motor function as well as the emergence of considerable non-motor problems [1]. The PD incidence rate is approximately 20/100,000 [2] and the prevalence rate exceeds 100/100,000 [3]; it is believed that an additional 20% of people with Parkinson’s (PWP) might be undiagnosed [4]. PWP are typically followed up by expert clinical staff at relatively sparse (six to twelve month) intervals. This contemporary triage of symptom management likely underestimates the true fluctuation of
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