Combined Image-Based Approach for Monitoring the Adherence to Inhaled Medications

Vieira‐Marques, Pedro; Teixeira, João F.; Valente, José; Pinho, Bernardo; Guedes, Rui; Almeida, Rute; Jácome, Cristina; Pereira, Ana Margarida; Jacinto, Tiago; Amaral, Rita; Gonçalves, Ivânia; Sousa, A. Sá e; Couto, Mariana; Pereira, Mariana; Ferreira-Magalhães, Manuel; Bordalo, Diana; Nogueira‐Silva, Luís; Fonseca, João

doi:10.1007/978-3-030-31635-8_171

Cited by 3 publications

(5 citation statements)

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“…The existence of an interface that allows the user to correct the identified value or to insert a value when identification was unsuccessful creates a failsafe system. Compared with the initial tests, the template matching phase performance increased substantially (from 42% over 5 inhalers 47 to almost 100% over the 12 inhalers in the present study). The changes focused on redesigning inhaler templates by reducing graphical elements which allowed for a less strict match thus increasing the performance and the user experience.…”

Section: Discussionmentioning

confidence: 49%

“…46 A prototype of a novel approach to acquire inhaler's dosage counter progress, exploring the potential of mobile devices characteristics and available frameworks for image processing and machine learning-based text extraction, to acquire inhaler's dosage counter progress allowing for increased remote and objective monitoring was proposed as part of the application InspirerMundi. This approach was tested with a small subset of available inhalers and although showing promising preliminary results, 47 needed improvements were also identified.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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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.

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Section: Discussionmentioning

confidence: 49%

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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“…These results highlight the difficulty in achieving a continuous medication monitoring. As a mitigation strategy, the remaining doses counter can be used to assess all doses taken between verified intakes, comparing with the registered therapeutic plan, if the same inhaler is used, and estimate a more precise IMA rate (Vieira-Marques et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…For inhalers without a correspondent template on the App, as well as for other types of medication, the usage detection module just collected a photo of the medication. Along with the confirmation of the type of inhaler, the app has a character recognition tool that can be used to assess the number of remaining doses for any inhaler providing a number-based dose counter (Vieira-Marques et al, 2020) As is common in other gamified products, the app makes use of several game mechanics like points, badges and a leaderboard to engage the user. These are part of the game & peer support component dynamics.…”

Section: Methods and Datamentioning

confidence: 99%

Engagement and Usage Patterns of a Mobile Application to Monitor Disease and Treatment Adherence in Patients With Asthma

2020

Proceedings of the 12th International Conference on E-Health (EH2020)

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Inhaled therapies are the cornerstone of effective asthma treatment and adequate inhaled medication adherence (IMA) is critical. mHealth technologies have shown to be promise for asthma self-management, including IMA improvement. InspirerMundi is a mobile application designed to support self-management of patients with asthma. It aims to transform the adherence to treatment into a positive experience through gamification and social interaction while allowing for ubiquitous verified IMA monitoring. The app includes an image-based inhaler usage detection tool, tools for reporting symptoms and burden of the asthma (disease monitoring) and Game & Peer support features. Still, the effectiveness of these tools depends on a regular app use and a real-life assessment of patient engagement and pattern of use is needed. This work evaluates the patient engagement, usage, and acceptance of InspirerMundi app during a real-world multicentre feasibility study. The app use was recommended for a 4-months period to 77 participants with persistent asthma. From those, 72 installed the app, with 67% of them beginning to use both the inhaler usage detection tool and the disease monitoring components within the first week. Over 95% used it more than once, with the period of usage (from first use to last registered monitoring in 2018) being over 30 days for almost 70% of the users, and over 90 days for around 35%. Nevertheless, the usage rate (ratio of the number of days with app usage and the period of use) had a median value of 0.6 and was above 75% for only 35% of the users, revealing room for improvement. In general, the users started to use the app features right after installation and the usage patterns and retention rates indicate that InspirerMundi is well accepted among patients with asthma.

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“…AIRDOC is taking advantage of previously developed tools for objective monitoring of medication adherence. An enhanced version of the image-based dose recognition developed for InspirerMundi app will be integrated into the AIRDOC app (Vieira-Marques et al, 2020). Reports and statistics on the medication adherence will be available to the patient, being shareable with the health professionals.…”

Section: Management Plan Modulementioning

confidence: 99%

Airdoc: Smart Mobile Application for Individualized Support and Monitoring of Respiratory Function and Sounds of Patients With Chronic Obstructive Disease

2020

Proceedings of the 12th International Conference on E-Health (EH2020)

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Current tools for self-management of chronic obstructive respiratory diseases (CORD) are difficult to use, not individualized and requiring laborious analysis by health professionals, discouraging their use in healthcare. There is an opportunity for cost-effective and easy-to-disseminate advanced technological solutions directed to patients and attractive to different stakeholders. The strategy of AIRDOC is to develop and integrate self-monitoring and self-managing tools, making use of the smartphone's presence in everyday life. AIRDOC intends to innovate on: i) technologies for remote monitoring of respiratory function and computerized lung auscultation; ii) coaching solutions, integrating psychoeducation, gamification and disease management support systems; and iii) management of personal health data, focusing on security, privacy and interoperability. It is expected that AIRDOC results will contribute for the innovation in CORD healthcare, with increased patient involvement and empowerment while providing quality prospective information for better clinical decisions, allowing more efficient and sustainable healthcare delivery.

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Combined Image-Based Approach for Monitoring the Adherence to Inhaled Medications

Cited by 3 publications

References 8 publications

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

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

Engagement and Usage Patterns of a Mobile Application to Monitor Disease and Treatment Adherence in Patients With Asthma

Airdoc: Smart Mobile Application for Individualized Support and Monitoring of Respiratory Function and Sounds of Patients With Chronic Obstructive Disease

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