Menozzi, E. and Jha, A. and Oyekan, R. and Schreglmann, S. and Latorre, A. and Mulroy, E. and Roussos, George and Stamate, C. and Daskalopoulos, I. and Rothwell, J. (2019) Smartphone software for home monitoring of motor symptoms in Parkinson's disease: the CloudUPDRS smartphone software in Parkinson's (CUSSP) study. In: MDS International Congress, 23rd September 2019, Nice, France. (Unpublished)
Abstract
Objective: To determine the validity of smartphone software for objective monitoring of motor symptoms in patients with Parkinson’s disease (PD). Background: Although the MDS-Unified Parkinson’s Disease Rating Scale (UPDRS) scale part III remains the most commonly used framework with which to assess motor impairment in Parkinson’s disease in clinical practice and research [1], it remains subjective and is usually performed infrequently due to the clinical effort required to complete it. Markedly confounded by the day-to-day motor fluctuations many patients face, unitary UPDRS scores poorly reflect individual patient symptoms and reduce power in interventional trials. A number of wearable, smartphone and sensor-based solutions have been proposed that allow patients to monitor symptoms either continuously or at high-frequency without the need for clinical input but the validity of these tools remains untested within well-designed prospective clinical trials. In this study, we validate CloudUPDRS smartphone measures [2] against clinical UPDRS assessment. Method: The CloudUPDRS Smartphone Software in Parkinson’s (CUSSP) study is a pre-registered pilot multi-site, randomised study. Inclusion criteria were: diagnosis of idiopathic Parkinson’s disease according to Brain Bank criteria, age over 18 years, and Montreal Cognitive Assessment score over 20/30. Sixty patients (females, n = 20) were included so far. Each patient underwent a video-recorded MDS-UPDRS part III clinical examination, and a simultaneous range of UPDRS-style smartphone-based assessments. Objective smartphone measures were used to predict the mean clinical UPDRS rating of 3 neurologists based on video assessment, blinded to the patient’s medication state. Results: Mean (+/- sd) age was 68 (± 9.5) years. Mean disease duration was 5 (± 4.7) years, with mean Hoehn and Yahr stage of 2. The primary outcome was the predictive accuracy of the smartphone score for the blinded MDS-UPDRS rating score at baseline assessment. Comprehensive analyses are ongoing and will be presented. Conclusion: The current study is ongoing. We suggest that objective smartphone assessments may allow high-frequency at-home assessment of motor symptoms in PD, and that such a granular picture may be empowering to patients and beneficial to their medical teams and clinical researchers alike.
Metadata
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
| Depositing User: | George Roussos |
| Date Deposited: | 09 May 2022 18:58 |
| Last Modified: | 09 Aug 2023 12:52 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/47089 |
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