A Vital Sign Analysis System Based on Algorithm Block Broker for Interoperability between Algorithm Development Tools
Source abstract
Abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Anomaly Detection Techniques and Applications · Artificial Intelligence in Healthcare · Healthcare Technology and Patient Monitoring
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Digital Anti-aging Healthcare, Inje University, Gimhae-si 50834, Korea
Department of Computer Engineering, Inje University, Gimhae-si 50834, Korea
Funding
Ministry of Trade, Industry and Energy
References (24)
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