JMIR Publications

JMIR Biomedical Engineering


Recent Articles:

  • 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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  • User Participation and Engagement with the See Me Smoke-Free mHealth App: Results of a Prospective Feasibility Trial

    Date Submitted: Apr 21, 2017

    Open Peer Review Period: May 31, 2017 - Jul 14, 2017

    Background: The See Me Smoke-Free (SMSF) mobile health (mHealth) application (app) was developed to help women quit smoking by targeting concerns about body weight, body image, and self-efficacy throu...

    Background: The See Me Smoke-Free (SMSF) mobile health (mHealth) application (app) was developed to help women quit smoking by targeting concerns about body weight, body image, and self-efficacy through cognitive behavioral techniques and guided imagery audio files addressing smoking, diet, and physical activity. A feasibility trial found associations between SMSF usage and positive treatment outcomes. This paper reports a detailed exploration of program use among those who downloaded the app, and the relationship between program use and treatment outcomes. Objective: To determine whether: 1) participants were more likely to set quit dates, be current smokers, and report higher levels of smoking at baseline than non-participants; 2) participants opened the app and listened to audio files more frequently than non-participants; and 3) participants with more app usage had a higher likelihood of smoking abstinence at follow-up. Methods: The SMSF feasibility trial was a single arm, within-subjects, prospective cohort study with assessments at baseline, 30- and 90-days post-enrollment. The SMSF app was deployed on the Google Play store for download, and basic profile characteristics were obtained for all app installers. Additional variables were assessed for study participants. Participants were prompted to use the app daily during study participation. Crude differences in baseline characteristics between trial participants and non-participants were evaluated using t-tests (continuous variables) and Fisher’s exact tests (categorical variables). Exact Poisson tests were used to assess group-level differences in mean usage rates over the full study period, using aggregate Google Analytics data on participation and usage. Negative binomial regression models were used to estimate associations of app usage with participant baseline characteristics, after adjustment for putative confounders. Associations between app usage and smoking abstinence were assessed using separate logistic regression models for each outcome measure. Results: Participants (n=151) were more likely than non-participants (n=96) to report female gender (P < 0.02) and smoking in the 30 days prior to enrollment (P < 0.0001). Participants and non-participants opened the app and updated quit dates at the same average rate (Rate ratio (RR) 0.98; 95% CI: 0.92, 1.04; P = 0.43), but participants started audio files (RR 1.07; 95% CI: 1.00, 1.13; P < 0.04) and completed audio files (RR 1.11; 95% CI: 1.03, 1.18; P < 0.003) at significantly higher rates than non-participants. Higher app usage among participants was generally associated with increased smoking cessation, and most effect sizes suggested strong associations, though generally without statistical significance. Conclusions: The current study suggests potential efficacy of the SMSF app, as increased usage was generally associated with higher smoking abstinence. A planned randomized controlled trial will assess the SMSF app’s efficacy as an intervention tool to help women quit smoking. Clinical Trial: NCT02972515

  • Low- and No-Cost Strategies to Recruit Women to a Mobile Health Smoking Cessation Trial

    Date Submitted: Jan 19, 2017

    Open Peer Review Period: May 31, 2017 - Jul 14, 2017

    Background: Successful recruitment and retention of adequate numbers of participants to mobile health (mHealth) studies remains a challenge. Given that researchers must decide how to invest limited re...

    Background: Successful recruitment and retention of adequate numbers of participants to mobile health (mHealth) studies remains a challenge. Given that researchers must decide how to invest limited recruitment resources, it is important to identify the most effective recruitment strategies, defined as those that incur low costs relative to participant yield. Objective: The objective of this manuscript is to describe the development and implementation process for the recruitment phase of an mHealth intervention designed to increase smoking cessation among weight-concerned women smokers. These recruitment methods could be applicable across a range of mHealth studies. Methods: Study information was released to the media in multiple phases. First, local city and state media were contacted, followed by national women’s health media, and finally outlets in states with high smoking rates. Stories and mentions resulting from the press releases (earned media) were disseminated via existing department and new study-specific social media accounts. Strategic hashtags were used in Facebook and Twitter posts to connect with broader smoking cessation campaigns. Posts were also made to third-party Facebook smoking cessation communities and Internet classifieds sites. Results: Media coverage was documented across 75 publications and radio/television broadcasts, 35 of which were local, 39 national, and 1 international. Between March 30th and July 31st, 2015, 151 participants were successfully recruited to the study. Conclusions: Leveraging social media, and coordinating with university public affairs offices were effective and low-cost strategies to earn media coverage, and reach potential participants. Clinical Trial: Not Applicable