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. 2021 Jul 21;21(15):4972.
doi: 10.3390/s21154972.

Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson's Disease

Raquel Bouça-Machado  1   2 , Filipa Pona-Ferreira  2 , Mariana Leitão  2 , Ana Clemente  3 , Diogo Vila-Viçosa  3 , Linda Azevedo Kauppila  2 , Rui M Costa  4   5 , Ricardo Matias  4   6   7 , Joaquim J Ferreira  1   2   8
Affiliations

Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson's Disease

Raquel Bouça-Machado et al. Sensors (Basel). .

Abstract

Mobile health (mHealth) has emerged as a potential solution to providing valuable ecological information about the severity and burden of Parkinson's disease (PD) symptoms in real-life conditions. Objective: The objective of our study was to explore the feasibility and usability of an mHealth system for continuous and objective real-life measures of patients' health and functional mobility, in unsupervised settings. Methods: Patients with a clinical diagnosis of PD, who were able to walk unassisted, and had an Android smartphone were included. Patients were asked to answer a daily survey, to perform three weekly active tests, and to perform a monthly in-person clinical assessment. Feasibility and usability were explored as primary and secondary outcomes. An exploratory analysis was performed to investigate the correlation between data from the mKinetikos app and clinical assessments. Results: Seventeen participants (85%) completed the study. Sixteen participants (94.1%) showed a medium-to-high level of compliance with the mKinetikos system. A 6-point drop in the total score of the Post-Study System Usability Questionnaire was observed. Conclusions: Our results support the feasibility of the mKinetikos system for continuous and objective real-life measures of a patient's health and functional mobility. The observed correlations of mKinetikos metrics with clinical data seem to suggest that this mHealth solution is a promising tool to support clinical decisions.

Keywords: Parkinson’s disease; digital health; remote monitoring; sensors; wearable technology.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Boxplots comparing the evolution of compliance throughout the study for patients at different levels of global compliance. * p-value ≤ 0.05. ** p-value ≤ 0.01.
Figure 2
Figure 2
The average percent of compliance (per patient) with the daily survey and active tests (finger tapping, balance, and walk) during the 28 weeks (7 months) of the study, per day of the week, and per hour of the day. Expected data (100%) correspond to one survey per day and one active test per week. The survey notification was sent at 7:00 p.m. and remained available for 5 h. The gray shaded area identifies the COVID-19 confinement phase in Portugal.
Figure 3
Figure 3
Boxplots comparing the evolution of compliance throughout the study for daily survey and active tests.
Figure 4
Figure 4
Correlations between mKinetikos scores and the respective clinical outcomes (TUG, MDS-UPDRS finger-tapping, gait and balance, and balance items).
See this image and copyright information in PMC

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References

    1. van der Marck M., Kalf J., Sturkenboom I., Nijkrake M., Munneke M., Bloem B. Multidisciplinary care for patients with Parkinson’s disease. Park. Relat. Disord. 2009;15:S219–S223. doi: 10.1016/S1353-8020(09)70819-3. - DOI - PubMed
    1. Rascol O., Payoux P., Ory F., Ferreira J.J., Brefel-Courbon C., Montastruc J.-L. Limitations of current Parkinson’s disease therapy. Ann. Neurol. 2003;53:3–15. doi: 10.1002/ana.10513. - DOI - PubMed
    1. Timotijevic L., Hodgkins C.E., Banks A., Rusconi P., Egan B., Peacock M., Seiss E., Touray M.M.L., Gage H., Pellicano C., et al. Designing a mHealth clinical decision support system for Parkinson’s disease: A theoretically grounded user needs approach. BMC Med. Inform. Decis. Mak. 2020;20:34. doi: 10.1186/s12911-020-1027-1. - DOI - PMC - PubMed
    1. Gatsios D., Antonini A., Gentile G., Marcante A., Pellicano C., Macchiusi L., Assogna F., Spalletta G., Gage H., Touray M., et al. Feasibility and Utility of mHealth for the Remote Monitoring of Parkinson Disease: Ancillary Study of the PD_manager Randomized Controlled Tria. JMIR mHealth uHealth. 2020;8:e16414. doi: 10.2196/16414. - DOI - PMC - PubMed
    1. Elm J.J., Daeschler M., Bataille L., Schneider R., Amara A., Espay A.J., Afek M., Admati C., Teklehaimanot A., Simuni T. Feasibility and utility of a clinician dashboard from wearable and mobile application Parkinson’s disease data. NPJ Digit. Med. 2019;2:95. doi: 10.1038/s41746-019-0169-y. - DOI - PMC - PubMed