An API for Wearable Environments Development and Its Application to mHealth Field †

Abstract

Wearable technologies are transforming research in traditional paradigms of software and knowledge engineering. Among them, expert systems have the opportunity to deal with knowledge bases dynamically varying according to real-time data collected by position sensors, movement sensors, etc. However, it is necessary to design and implement opportune architectural solutions to avoid expert systems are responsible for data acquisition and representation. These solutions should be able to collect and store data according to expert systems desiderata, building a homogeneous framework where data reliability and interoperability among data acquisition, data representation and data use levels are guaranteed. To this aim, the wearable environment notion has been introduced to treat all those information sources as components of a larger platform; a middleware has been designed and implemented, namely WEAR-IT, which allows considering each sensor as a source of information that can be dynamically tied to an expert system application running on a smartphone. As an application example, the mHealth domain is considered.

WearMerge: An Interoperable Framework for Self-tracking Data Integration and Standardization

“…There have been some efforts to develop integration APIs or mobile and web applications for handling the issues above. After careful review, we have identified three domain-related categories: medical applications [4,5,1,6], social and psychological applications [7,8] and data analysis applications [9,2]. However, the majority of these works do not use mobile health data interoperability standards for standardizing and harmonizing data from disparate sources, nor have they made their code open-source, while others support only a limited amount of manufacturers [4].…”