BackgroundA transformation is underway regarding how we deal with our health. Mobile devices make it possible to have continuous access to personal health information. Wearable devices, such as Fitbit and Apple’s smartwatch, can collect data continuously and provide insights into our health and fitness. However, lack of interoperability and the presence of data silos prevent users and health professionals from getting an integrated view of health and fitness data. To provide better health outcomes, a complete picture is needed which combines informal health and fitness data collected by the user together with official health records collected by health professionals. Mobile apps are well positioned to play an important role in the aggregation since they can tap into these official and informal health and data silos.ObjectiveThe objective of this paper is to demonstrate that a mobile app can be used to aggregate health and fitness data and can enable interoperability. It discusses various technical interoperability challenges encountered while integrating data into one place.MethodsFor 8 years, we have worked with third-party partners, including wearable device manufacturers, electronic health record providers, and app developers, to connect an Android app to their (wearable) devices, back-end servers, and systems.ResultsThe result of this research is a health and fitness app called myFitnessCompanion, which enables users to aggregate their data in one place. Over 6000 users use the app worldwide to aggregate their health and fitness data. It demonstrates that mobile apps can be used to enable interoperability. Challenges encountered in the research process included the different wireless protocols and standards used to communicate with wireless devices, the diversity of security and authorization protocols used to be able to exchange data with servers, and lack of standards usage, such as Health Level Seven, for medical information exchange.ConclusionsBy limiting the negative effects of health data silos, mobile apps can offer a better holistic view of health and fitness data. Data can then be analyzed to offer better and more personalized advice and care.

<span>This article reports on an m-learning research agenda instituted at our university in order to explore how mobile technology can enhance active, experiential learning. Details of the implementation and results of four areas of m-learning are presented: mobile supported fieldwork, fostering interactivity in large lectures with mobile technology, using mobile devices to learn about mobile technology and, finally, podcasting. These directions are informed by a concern for achieving m-learning practices consistent with sound educational theory and the needs of the contemporary, technologically aware student body. All four implementations have been successfully embedded in mainstream subjects on a continuing basis. Therefore they represent a departure from the project based approach of much m-learning reported in the literature. This outcome was achieved through a focus on the economic sustainability and feasibility of each case. An evaluation focusing on how well each case assisted students' learning found that, with the exception of lecture podcasting, all supported high quality experiential learning.</span>

No abstract

An increasing aged population worldwide puts our medical capabilities to the test. Research and commercial groups are investigating novel ways to care for the aged and chronically ill both in their own homes and in care facilities. This paper describes a prototype we have developed for remote healthcare monitoring. This personalized smart homecare system uses smart phones, wireless sensors, web servers and IP webcams. To illustrate the functionality of the prototype we describe a series of typical tele-health monitoring scenarios.