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JMIR Biomedical Engineering


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  • Source: Pixabay; Copyright: Gerd Altmann; URL:; License: Public Domain (CC0).

    Heart Rate Monitoring Apps: Information for Engineers and Researchers About the New European Medical Devices Regulation 2017/745

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    Background: After years in the making, on April 5, 2017, the European Parliament and Council finally adopted Regulation (EU) 2017/745, the new Medical Devices Regulation (MDR), repealing the existing Medical Device Directive (MDD) 93/42/EEC. Though long anticipated, this shift in policy will have strong and lasting effects in the medical devices industry. Objective: This paper focuses specifically on the classification of software as a potential medical device under MDD and MDR and examines whether or not the regulatory framework for health apps has changed substantially and what, if any, impact is to expected. A particular emphasis will be on the issue of classification uncertainty raised by borderline cases such as heart rate monitoring and well-being apps. The paper primarily targets researchers and engineers unfamiliar with regulatory requirements for medical devices and aims to provide a concise, yet accurate, overview of the European regulatory framework. This is of particular relevance as with the exponential growth of fitness and health-related apps, the lines between toys, lifestyle products, and medical devices have increasingly blurred. Methods: The recently published European Medical Device Regulation is analyzed and compared to the preceding MDD. Results: The previous regulatory framework already provided for the possibility of apps to fall under the definition of medical devices, in which case classification rules for active medical devices applied. However, while applicability of the new regulatory framework still hinges on whether the intended purpose is medical or not, the threshold for classifying as a medical device has been considerably lowered due to a broader interpretation of what constitutes a medical purpose. Conclusions: The adoption of the new European regulation on medical devices entails the risk that manufacturers previously unaffected by the medical devices regulatory framework may now unwillingly and unwittingly find themselves in the arena of medical device manufacturing.

  • Wearable Devices and Smart Watches for Fitness and Hospital Health Tracking. Source:; Copyright: BrotherUK; URL:; License: Creative Commons Attribution (CC-BY).

    Motivations and Key Features for a Wearable Device for Continuous Monitoring of Breathing: A Web-Based Survey


    Background: Analysis of patterns of breathing over time may provide novel information on respiratory function and dysfunction. Devices that continuously record and analyze breathing rates may provide new options for the management of respiratory diseases. However, there is a lack of information about design characteristics that would make such devices user-friendly and suitable for this purpose. Objective: Our aim was to determine key device attributes and user requirements for a wearable device to be used for long-term monitoring of breathing. Methods: An online survey was conducted between June and July 2016. Participants were predominantly recruited via the Woolcock Institute of Medical Research database of volunteers, as well as staff and students. Information regarding the survey, a consent form, and a link to a Web-based questionnaire were sent to participants via email. All participants received an identical survey; those with doctor-diagnosed asthma completed an extra questionnaire on asthma control (Asthma Control Test). Survey responses were examined as a group using descriptive statistics. Responses were compared between those with and without asthma using the chi-square test. Results: The survey was completed by 134 participants (males: 39%, median age group: 50-59 years, asthma: 57%). Of those who completed the Asthma Control Test, 61% (47/77) had suboptimal asthma control. Of the 134 participants, 61.9% (83/134) would be willing to wear a device to monitor their breathing, in contrast to 6.7% (9/134) who would not. The remaining 31.3% (42/134) stated that their willingness depended on specific factors. Participants with asthma most commonly cited their asthma as motivation for using a wearable; the most common motivation for use in those without asthma was curiosity. More than 90% of total participants would use the device during the day, night, or both day and night. Design preferences among all users included a wrist watch (nominated by 92.5% [124/134] for both day and night use, out of four body sites), the ability to synchronize breathing data with a mobile phone or tablet (81.3%, 109/134), overnight power charging (33.6%, 45/134), and a cost of ≤Aus $100 (53.7%, 72/134). Conclusions: We have explored the motivations and likelihood for adopting wearable technologies for the purpose of monitoring breathing and identified user preferences for key design features. We found participants were motivated to adopt a wearable breathing monitor irrespective of health status, though rationale for use differed between those with and without asthma. These findings will help inform the design of a user-acceptable wearable device that will facilitate its eventual uptake in both healthy and asthma populations.

  • CJTF-HOA shares best health practices with Dikhil women. Image Source: Author:Staff Sgt. Christopher Gross. License:PUBLIC DOMAIN.

    A Six-Step Framework on Biomedical Signal Analysis for Tackling Noncommunicable Diseases: Current and Future Perspectives


    Low- and middle-income countries (LMICs) continue to face major challenges in providing high-quality and universally accessible health care. Researchers, policy makers, donors, and program implementers consistently strive to develop and provide innovative approaches to eliminate geographical and financial barriers to health care access. Recently, interest has increased in using mobile health (mHealth) as a potential solution to overcome barriers to improving health care in LMICs. Moreover, with use increasing and cost decreasing for mobile phones and Internet, mHealth solutions are becoming considerably more promising and efficient. As part of mHealth solutions, biomedical signals collection and processing may play a major role in improving global health care. Information extracted from biomedical signals might increase diagnostic precision while augmenting the robustness of health care workers’ clinical decision making. This paper presents a high-level framework using biomedical signal processing (BSP) for tackling diagnosis of noncommunicable diseases, especially in LMICs. Researchers can consider each of these elements during the research and design of BSP-based devices, enabling them to elevate their work to a level that extends beyond the scope of a particular application and use. This paper includes technical examples to emphasize the applicability of the proposed framework, which is relevant to a wide variety of stakeholders, including researchers, policy makers, clinicians, computer scientists, and engineers.

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  • Level of Evidence in ICT for Alzheimer’s Disease: A Systematic Literature Review

    Date Submitted: Oct 12, 2017

    Open Peer Review Period: Oct 14, 2017 - Dec 9, 2017

    Background: Alzheimer’s Disease (AD) is one of the top ten leading causes of death and only one that cannot be completely prevented or cured in the United States. The cost on AD is high: the total p...

    Background: Alzheimer’s Disease (AD) is one of the top ten leading causes of death and only one that cannot be completely prevented or cured in the United States. The cost on AD is high: the total payments for health care, long-term care and hospice are estimated to be $236 billion, and these could rise to more than 1$ trillion by 2050. Objective: By performing the systematic literature review of information and communications technologies on AD, we aimed to identify the level of evidence in this field by focusing on the following five items: 1) purposes when ICT was utilized on AD, 2) types of conducted studies, 3) characteristics of the target populations in the previous studies, 4) types of methods used in the previous studies, and 5) benefits for the patients, caregivers, and physicians. Methods: We performed four rounds: database selection, keyword search, screening with inclusion criteria, and screening the full-text to identify previous studies. The databases we used were PubMed, SCOPUS, PSYCINFO, Web of Science (WoS), and CINAHL. We used the following two concepts that answer to our research questions when creating combinations of keywords: Alzheimer’s disease and information and communication technologies. Results: We found sixteen articles published between 2010 May and 2016 January, which corresponded to each individual study. The findings of the systematic literature review were arranged and assessed with six categories: purposes of using ICT, study design, devices, evaluation, target population, methods, and benefits of research. Conclusions: The main contribution of our study was to identify the level of evidence in this field with the following themes: purposes, types of studies, types of ICT, evaluation criteria, target population, methods, and benefits. Such contribution guides other researchers interested in this field to perform more effective research and devise ICT tools for ADs.