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Digital health technology for non-motor symptoms in people with Parkinson's disease: Futile or future?

Lookup NU author(s): Professor Camille CarrollORCiD


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© 2021 The Author(s). Introduction: There is an ongoing digital revolution in the field of Parkinson's disease (PD) for the objective measurement of motor aspects, to be used in clinical trials and possibly support therapeutic choices. The focus of remote technologies is now also slowly shifting towards the broad but more “hidden” spectrum of non-motor symptoms (NMS). Methods: A narrative review of digital health technologies for measuring NMS in people with PD was conducted. These digital technologies were defined as assessment tools for NMS offered remotely in the form of a wearable, downloadable as a mobile app, or any other objective measurement of NMS in PD that did not require a hospital visit and could be performed remotely. Searches were performed using peer-reviewed literature indexed databases (MEDLINE, Embase, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane CENTRAL Register of Controlled Trials), as well as Google and Google Scholar. Results: Eighteen studies deploying digital health technology in PD were identified, for example for the measurement of sleep disorders, cognitive dysfunction and orthostatic hypotension. In addition, we describe promising developments in other conditions that could be translated for use in PD. Conclusion: Unlike motor symptoms, non-motor features of PD are difficult to measure directly using remote digital technologies. Nonetheless, it is currently possible to reliably measure several NMS and further digital technology developments are underway to offer further capture of often under-reported and under-recognised NMS.

Publication metadata

Author(s): van Wamelen DJ, Sringean J, Trivedi D, Carroll CB, Schrag AE, Odin P, Antonini A, Bloem BR, Bhidayasiri R, Chaudhuri KR

Publication type: Review

Publication status: Published

Journal: Parkinsonism and Related Disorders

Year: 2021

Volume: 89

Pages: 186-194

Print publication date: 01/08/2021

Online publication date: 31/07/2021

Acceptance date: 28/07/2021

ISSN (print): 1353-8020

ISSN (electronic): 1873-5126

Publisher: Elsevier Ltd


DOI: 10.1016/j.parkreldis.2021.07.032

PubMed id: 34362670