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. 2024 Apr 9:10:20552076241238133.
doi: 10.1177/20552076241238133. eCollection 2024 Jan-Dec.

Feasibility and usability of remote monitoring in Alzheimer's disease

Marijn Muurling  1   2 , Casper de Boer  1   2 , Chris Hinds  3 , Alankar Atreya  3 , Aiden Doherty  3 , Vasilis Alepopoulos  4 , Jelena Curcic  5 , Anna-Katharine Brem  6   7 , Pauline Conde  6 , Sajini Kuruppu  6 , Xavier Morató  8 , Valentina Saletti  9 , Samantha Galluzzi  9 , Estefania Vilarino Luis  10 , Sandra Cardoso  11 , Tina Stukelj  12 , Milica Gregorič Kramberger  12   13 , Dora Roik  14 , Ivan Koychev  15 , Ann-Cecilie Hopøy  16 , Emilia Schwertner  13   17 , Mara Gkioka  18 , Dag Aarsland  6   16 , Pieter Jelle Visser  1   2   13   19 ; RADAR-AD consortium
Affiliations

Feasibility and usability of remote monitoring in Alzheimer's disease

Marijn Muurling et al. Digit Health. .

Abstract

Introduction: Remote monitoring technologies (RMTs) can measure cognitive and functional decline objectively at-home, and offer opportunities to measure passively and continuously, possibly improving sensitivity and reducing participant burden in clinical trials. However, there is skepticism that age and cognitive or functional impairment may render participants unable or unwilling to comply with complex RMT protocols. We therefore assessed the feasibility and usability of a complex RMT protocol in all syndromic stages of Alzheimer's disease and in healthy control participants.

Methods: For 8 weeks, participants (N = 229) used two activity trackers, two interactive apps with either daily or weekly cognitive tasks, and optionally a wearable camera. A subset of participants participated in a 4-week sub-study (N = 45) using fixed at-home sensors, a wearable EEG sleep headband and a driving performance device. Feasibility was assessed by evaluating compliance and drop-out rates. Usability was assessed by problem rates (e.g., understanding instructions, discomfort, forgetting to use the RMT or technical problems) as discussed during bi-weekly semi-structured interviews.

Results: Most problems were found for the active apps and EEG sleep headband. Problem rates increased and compliance rates decreased with disease severity, but the study remained feasible.

Conclusions: This study shows that a highly complex RMT protocol is feasible, even in a mild-to-moderate AD population, encouraging other researchers to use RMTs in their study designs. We recommend evaluating the design of individual devices carefully before finalizing study protocols, considering RMTs which allow for real-time compliance monitoring, and engaging the partners of study participants in the research.

Keywords: Alzheimers < disease; apps < personalised medicine; dementia < disease; digital health < general; eHealth < general; neurology < medicine; remote clinical trials < studies; remote patient monitoring

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Conflict of interest statement

JC is an employee and shareholder of Novartis. AD is supported by the Welcome Trust [223100/Z/21/Z]. Research of Alzheimer center Amsterdam is part of the neurodegeneration research program of Amsterdam Neuroscience. Alzheimer Center Amsterdam is supported by Stichting Alzheimer Nederland and Stichting Steun Alzheimercentrum Amsterdam. DA has received research support and/or honoraria from Astra-Zeneca, H. Lundbeck, Novartis Pharmaceuticals, Biogen, and GE Health, and served as paid consultant for H. Lundbeck, Eisai, Heptares, Mentis Cura, and Roche Diagnostics. IK declares support for this work through the National Institute of Health Research (personal award and Oxford Health Biomedical Research Centre) and the Medical Research Council (Dementias Platform UK grant), and is a paid medical advisor for digital healthcare technology companies (Five Lives SAS and Cognetivity Ltd). All other authors declare that there is no conflict of interest.

Figures

Figure 1.
Figure 1.
Indications of problems with the different remote monitoring technologies (RMTs). 0 means no problems, with higher scores indicating more problems. HC: healthy control; PreAD: preclinical AD; ProAD: prodromal AD; MildAD: mild-to-moderate AD; N: number of participants that answered questions regarding that RMT during at least one phone call.
Figure 2.
Figure 2.
Problems per remote monitoring technology per study group. The horizontal axis shows percentage of participants giving a certain answer to the corresponding question/topic. The data is a mean of all calls together, to avoid biases due to drop-outs or missed phone calls. The data presented here was not analyzed statistically.
See this image and copyright information in PMC

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