Background More than a million health and well-being apps are available from the Apple and Google app stores. Some apps use built-in mobile phone sensors to generate health data. Clinicians and patients can find information regarding safe and effective mobile health (mHealth) apps in third party–curated mHealth app libraries. Objective These independent Web-based repositories guide app selection from trusted lists, but do they offer apps using ubiquitous, low-cost smartphone sensors to improve health? This study aimed to identify the types of built-in mobile phone sensors used in apps listed on curated health app libraries, the range of health conditions these apps address, and the cross-platform availability of the apps. Methods This systematic survey reviewed three such repositories (National Health Service Apps Library, AppScript, and MyHealthApps), assessing the availability of apps using built-in mobile phone sensors for the diagnosis or treatment of health conditions. Results A total of 18 such apps were identified and included in this survey, representing 1.1% (8/699) to 3% (2/76) of all apps offered by the respective libraries examined. About one-third (7/18, 39%) of the identified apps offered cross-platform Apple and Android versions, with a further 50% (9/18) only dedicated to Apple and 11% (2/18), to Android. About one-fourth (4/18, 22%) of the identified apps offered dedicated diagnostic functions, with a majority featuring therapeutic (9/18, 50%) or combined functionality (5/18, 28%). Cameras, touch screens, and microphones were the most frequently used built-in sensors. Health concerns addressed by these apps included respiratory, dermatological, neurological, and anxiety conditions. Conclusions Diligent mHealth app library curation, medical device regulation constraints, and cross-platform differences in mobile phone sensor architectures may all contribute to the observed limited availability of mHealth apps using built-in phone sensors in curated mHealth app libraries. However, more efforts are needed to increase the number of such apps on curated lists, as they offer easily accessible low-cost options to assist people in managing clinical conditions.

Background: Clinically valid and reliable simulated inspiratory sounds were required for the development and evaluation of a new therapeutic respiratory exergame application (i.e., QUT Inspire). This smartphone application virtualises incentive spirometry, a longstanding respiratory therapy technique. Objectives: Inspiratory flows were simulated using a 3 litre calibration syringe and validated using clinical reference devices. Syringe flow nozzles of decreasing diameter were applied to model the influence of mouth shape on audible sound levels generated. Methods: A library of calibrated audio inspiratory sounds was created to determine the reliability and range of inspiratory sound detection at increasing distances separating the sound source and smartphones running the app. Results: Simulated inspiratory sounds were reliably detected by the new application at higher air inflows (high, medium), using smaller mouth diameters (<25 mm) and where smartphones were held proximal (< = 5 cm) to the mouth (or at distances up to 50 cm for higher airflows). Performance was comparable for popular smartphone types and using different phone orientations (i.e., held horizontally, at 45° or 90°). Conclusions: These observations inform future application refinements, including prompts to reduce mouth diameter, increase inspiratory flow and maintain proximity to the phone to optimise sound detection. This library of calibrated inspiratory sounds offers reproducible non-human reference data suitable for development, evaluation and regression testing of a therapeutic respiratory exergame application for smartphones.

Clinicians are cautious about embracing prescription of health and well-being (i.e., mHealth) smartphone apps to patients, citing a lack of evidence regarding safety, reliability and clinical validity as barriers to wider adoption. This doctoral thesis presents an exploration of a new smartphone mHealth app (QUT Inspire) which virtualises a longstanding respiratory therapy technique called Incentive Spirometry (i.e., ISy); this new app detects inspired breath sounds using the built-in phone microphone and displays responsive animated on-screen graphics to encourage engagement, effort and persistence with virtualised ISy therapy.

IntroductionA new smartphone app (QUT Inspire) has been developed to detect inspiratory sound and deliver virtual incentive spirometry (ISy), a respiratory therapy technique used in postoperative recuperation, management of some chronic conditions and with potential applications in SARS-CoV-2 rehabilitation. The aim of this study was to compare the usability of this new app with a clinical ISy device as measured by effectiveness, efficiency and satisfaction.MethodsIn this mixed-methods randomised usability study, healthy volunteers (aged 39.2±12.2 years, n=24) compared inspirations using the QUT Inspire app and a Triflo II clinical ISy device. A post-test questionnaire and a semi-structured interview explored dimensions of usability regarding the new app.ResultsThe duration of inspirations performed using the QUT Inspire app (7.3±2.0 s) were comparable with use of the Triflo II ISy device (7.5±2.3 s). No artefacts arising from the order of device testing were identified. App users held their phones adjacent but not proximal to their mouths (13.6±6.4 cm), notwithstanding instructions to keep the phone less than 5 cm away for optimal breath sound detection. The use of onscreen text or video instructional materials did not result in a significant reduction in this distance. Participants reported clear preferences for the app (100%, n=24) to motivate persistence with repeated inspirations. App gamification features such as a timer (75%, n=18) and breath counter (83.3%, n=20) were well regarded. Analysis of semi-structured interviews identified four main themes arising from this study: visual reward from responsive app animations, clinical look and feel influencing credibility, perceived effort affecting engagement and selective adoption of gamification features.ConclusionThis study demonstrates that a virtual ISy app can be effective, efficient and have high satisfaction. Improvements informed by this research include use of additional phone sensors to optimise sound detection and minimising the distance that phones are held from the user’s mouth. Further research in randomised controlled trials are needed to evaluate performance of this app in clinical contexts where ISy is currently employed.

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