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CC BY-NC-ND 4.0 · Methods Inf Med 2021; 60(S 01): e9-e19
DOI: 10.1055/s-0041-1726277
Original Article

InspirerMundi—Remote Monitoring of Inhaled Medication Adherence through Objective Verification Based on Combined Image Processing Techniques

Pedro Vieira-Marques
1   CINTESIS—Center for Health Technology and Services Research, Faculty of Medicine, University of Porto, Porto, Portugal
,
Rute Almeida
1   CINTESIS—Center for Health Technology and Services Research, Faculty of Medicine, University of Porto, Porto, Portugal
2   Department of Community Medicine, MEDCIDS, Health Information and Decision, Faculty of Medicine, University of Porto, Porto, Portugal
,
João F. Teixeira
3   INESC TEC, Porto, Portugal
,
José Valente
4   MEDIDA—Serviços em Medicina, EDucação, Investigação, Desenvolvimento e Avaliação, LDA, Porto, Portugal
,
Cristina Jácome
1   CINTESIS—Center for Health Technology and Services Research, Faculty of Medicine, University of Porto, Porto, Portugal
2   Department of Community Medicine, MEDCIDS, Health Information and Decision, Faculty of Medicine, University of Porto, Porto, Portugal
,
Afonso Cachim
2   Department of Community Medicine, MEDCIDS, Health Information and Decision, Faculty of Medicine, University of Porto, Porto, Portugal
,
Rui Guedes
2   Department of Community Medicine, MEDCIDS, Health Information and Decision, Faculty of Medicine, University of Porto, Porto, Portugal
,
Ana Pereira
1   CINTESIS—Center for Health Technology and Services Research, Faculty of Medicine, University of Porto, Porto, Portugal
2   Department of Community Medicine, MEDCIDS, Health Information and Decision, Faculty of Medicine, University of Porto, Porto, Portugal
5   Allergy Unit, Instituto and Hospital CUF, Porto, Portugal
,
Tiago Jacinto
1   CINTESIS—Center for Health Technology and Services Research, Faculty of Medicine, University of Porto, Porto, Portugal
4   MEDIDA—Serviços em Medicina, EDucação, Investigação, Desenvolvimento e Avaliação, LDA, Porto, Portugal
6   Department of Cardiovascular and Respiratory Sciences, Porto Health School, Polytechnic Institute of Porto, Porto, Portugal
,
João A. Fonseca
1   CINTESIS—Center for Health Technology and Services Research, Faculty of Medicine, University of Porto, Porto, Portugal
2   Department of Community Medicine, MEDCIDS, Health Information and Decision, Faculty of Medicine, University of Porto, Porto, Portugal
4   MEDIDA—Serviços em Medicina, EDucação, Investigação, Desenvolvimento e Avaliação, LDA, Porto, Portugal
5   Allergy Unit, Instituto and Hospital CUF, Porto, Portugal
› Author Affiliations Funding This work was funded by ERDF (European Regional Development Fund) through the operations: POCI-01-0145-36 FEDER-029130 (“mINSPIRE—mHealth to measure and improve adherence to medication in chronic obstructive respiratory diseases, generalization, and evaluation of gamification, peer support and advanced image processing technologies”) cofounded by the COMPETE2020 (Programa Operacional Competitividade e Internacionalização), Portugal 2020 and by Portuguese Funds through FCT (Fundação para a Ciência e a Tecnologia).
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Abstract

Background The adherence to inhaled controller medications is of critical importance for achieving good clinical results in patients with chronic respiratory diseases. Self-management strategies can result in improved health outcomes and reduce unscheduled care and improve disease control. However, adherence assessment suffers from difficulties on attaining a high grade of trustworthiness given that patient self-reports of high-adherence rates are known to be unreliable.

Objective Aiming to increase patient adherence to medication and allow for remote monitoring by health professionals, a mobile gamified application was developed where a therapeutic plan provides insight for creating a patient-oriented self-management system. To allow a reliable adherence measurement, the application includes a novel approach for objective verification of inhaler usage based on real-time video capture of the inhaler's dosage counters.

Methods This approach uses template matching image processing techniques, an off-the-shelf machine learning framework, and was developed to be reusable within other applications. The proposed approach was validated by 24 participants with a set of 12 inhalers models.

Results Performed tests resulted in the correct value identification for the dosage counter in 79% of the registration events with all inhalers and over 90% for the three most widely used inhalers in Portugal. These results show the potential of exploring mobile-embedded capabilities for acquiring additional evidence regarding inhaler adherence.

Conclusion This system helps to bridge the gap between the patient and the health professional. By empowering the first with a tool for disease self-management and medication adherence and providing the later with additional relevant data, it paves the way to a better-informed disease management decision.

Keywords

medication adherence - mHealth - remote monitoring - serious games


Publication History

Received: 19 May 2020

Accepted: 20 December 2020

Article published online:
27 April 2021

© 2021. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

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