A Vital Sign Analysis System Based on Algorithm Block Broker for Interoperability between Algorithm Development Tools

• Published in: Applied sciences Vol. 11; no. 4; p. 1913
• Main Authors: Joo, Moon-Il, Kim, Hee-Cheol
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2021
• Subjects: Algorithms; Artificial intelligence; Big Data; C plus plus; Data analysis; Data mining; Electrocardiography; Heart rate; Interoperability; Java; Libraries; Methods; Programming languages; R&D; Research & development; Signal processing; vital sign; vital sign analysis; Wearable computers
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app11041913

With the recent development of artificial intelligence and data mining technology, various and intelligent vital sign analysis technologies have been developed. Vital sign analysis algorithms and technologies are primarily developed using MATLAB and open source technologies, such as Python and R. The analysis algorithms developed with such programming languages can only be employed and run in their own respective development environments and, hence, are unfortunately not considered as platform independent. In that respect, the interoperability between development tools is needed to ensure efficiency in terms of development time and efforts and reusability between analysis technologies and algorithms developed in different languages. This paper presents the development of a vital sign analysis system that ensures interoperability, which leads to one common environment connecting different development platforms. To maintain the interoperability between MATLAB and R programming, we designed and implemented the Algorithm Block Broker (AB Broker). AB Broker is composed of AB Adapter and AB Broker. Here, the AB Broker uses AB Adapter to request execution of analysis algorithms developed in different languages, such as MATLAB, R, and Python. It also searches and runs the algorithm, helping implement the requested analysis technique. The AB Broker-based vital sign analysis system enables the integrated management of analysis and data mining technologies developed in different languages. From a developer’s point of view, therefore, it is convenient and efficient to develop techniques using existing different programming technologies.