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

van Wamelen, Daniel J. ; Sringean, Jirada ; Trivedi, Dhaval ; Carroll, Camille B. ; Schrag, Anette E. ; Odin, Per LU orcid ; Antonini, Angelo ; Bloem, Bastiaan R. ; Bhidayasiri, Roongroj and Chaudhuri, K. Ray (2021) In Parkinsonism and Related Disorders 89. p.186-194
Abstract

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... (More)

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.

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author collaboration
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Accelerometer, Non-motor symptoms, Parkinson's disease, Sensor, Wearable
in
Parkinsonism and Related Disorders
volume
89
pages
186 - 194
publisher
Elsevier
external identifiers
  • scopus:85111925272
  • pmid:34362670
ISSN
1353-8020
DOI
10.1016/j.parkreldis.2021.07.032
language
English
LU publication?
yes
id
85277432-7a9b-476e-99be-fbe25fa52b48
date added to LUP
2021-09-02 16:43:43
date last changed
2025-01-13 12:30:33
@article{85277432-7a9b-476e-99be-fbe25fa52b48,
  abstract     = {{<p>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.</p>}},
  author       = {{van Wamelen, Daniel J. and Sringean, Jirada and Trivedi, Dhaval and Carroll, Camille B. and Schrag, Anette E. and Odin, Per and Antonini, Angelo and Bloem, Bastiaan R. and Bhidayasiri, Roongroj and Chaudhuri, K. Ray}},
  issn         = {{1353-8020}},
  keywords     = {{Accelerometer; Non-motor symptoms; Parkinson's disease; Sensor; Wearable}},
  language     = {{eng}},
  pages        = {{186--194}},
  publisher    = {{Elsevier}},
  series       = {{Parkinsonism and Related Disorders}},
  title        = {{Digital health technology for non-motor symptoms in people with Parkinson's disease : Futile or future?}},
  url          = {{http://dx.doi.org/10.1016/j.parkreldis.2021.07.032}},
  doi          = {{10.1016/j.parkreldis.2021.07.032}},
  volume       = {{89}},
  year         = {{2021}},
}