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Mhealth for remote monitoring and management of Parkinson’s disease: determinants of compliance and validation of a tremor evaluation method

Gatsios, D., Antonini, A., Gentile, G., Marcante, A., Pellicano, C., Macchiusi, L., Assogna, F., Spalletta, G., Gage, H., Touray, M. , Timotijevic, L., Hodgkins, C., Chondrogiorgi, M., Rigas, G., Fotiadis, D.I. and Konitsiotis, S. (2020) Mhealth for remote monitoring and management of Parkinson’s disease: determinants of compliance and validation of a tremor evaluation method JMIR mHealth and uHealth.

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Abstract

Background: mhealth, predominantly wearable technology and mobile apps, have been considered in Parkinson’s Disease to provide valuable ecological data between face to face visits and improve monitoring of motor symptoms remotely.

Objective: In this study we explore the feasibility of using a technology based mhealth platform comprising a smartphone in combination with a smartwatch and a pair of smart insoles, described in the present study as the PD_manager system, to collect clinically meaningful data. We also explore outcomes and disease related factors which are important determinants to establish feasibility. Finally, we further validate a tremor evaluation method with data collected while patients perform their daily activities.

Methods: PD_manager trial was an open label parallel group randomized study. The mheath platform consists of a wristband, a pair of sensor insoles, a smartphone (with dedicated mobile Android apps and a knowledge platform) serving as the cloud backend. The compliance was assessed with statistical analysis and the factors affecting it using appropriate regression analysis. The correlation of the scores of our previous algorithm for tremor evaluation and the respective UPDRS estimations by clinicians were explored.

Results: There were 65 of the 75 study participants (87%) who completed the protocol. They used the PD_manager system for a median 11.57 days (Std. dev. 3.15). The regression analysis suggests that the main factor associated with high usage was caregivers’ burden. Motor Aspects of Experiences of Daily Living and patients’ self-rated health status also influence the system’s usage. Our algorithm provided clinically meaningful data for the detection and evaluation of tremor.

Conclusions: We found that PD patients, regardless of their demographics and disease characteristics, used the system for 11-14 days. The study further supports that mhealth can be an effective tool for the ecologically valid, passive, unobtrusive monitoring and evaluation of symptoms. Future studies will be required to demonstrate that an mhealth platform can improve disease management and care.

Item Type: Article
Divisions : Faculty of Health and Medical Sciences > School of Psychology
Authors :
NameEmailORCID
Gatsios, D.
Antonini, A.
Gentile, G.
Marcante, A.
Pellicano, C.
Macchiusi, L.
Assogna, F.
Spalletta, G.
Gage, H.H.Gage@surrey.ac.uk
Touray, M.m.touray@surrey.ac.uk
Timotijevic, L.L.Timotijevic@surrey.ac.uk
Hodgkins, C.C.Hodgkins@surrey.ac.uk
Chondrogiorgi, M.
Rigas, G.g.p.rigas@surrey.ac.uk
Fotiadis, D.I.
Konitsiotis, S.
Date : 2020
Funders : European Union's Horizon 2020
Related URLs :
Depositing User : Clive Harris
Date Deposited : 11 May 2020 16:49
Last Modified : 13 May 2020 14:01
URI: http://epubs.surrey.ac.uk/id/eprint/856376

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