Software tools for organizing cloud computing in psychophysiological research based on eye-tracking data

Abstract

The architecture and web version of the software complex have been developed, which significantly expands the diagnostic capabilities of model-oriented information technologies for the assessment of the neurophysiological state. The complex provides cross-platform cloud computing, increases the productivity and efficiency of scientific research, using methods of non-parametric identification of the oculomotor system based on eye-tracking data, which is achieved thanks to a new concept of cloud computing organization. Cloud computing technology has been further developed thanks to the proposed concept that combines the principles of PaaS (Platform as a Service) and SaaS (Software as a Service). The key feature of the complex is the interface builder and the code translation module, which provide flexibility and convenience of working with the complex, allowing you to configure interface elements and connect them with script-code in different languages. Automatic replacement of values in script-code ​​simplifies the adaptation of the complex to various tasks, making it accessible to users with any skill level, which is especially valuable for science and education. In addition, the important feature of this software complex is its undemanding hardware on the client side thanks to the use of cloud computing, and its modular structure, which allows it to be easily scaled. Compared to other similar services, the complex has several advantages: it provides effective work in research and educational areas, supports several programming languages for improving algorithms, and also allows the use of ready-made identification methods through specially developed GUI interfaces. In addition, it offers social capabilities and a high level of abstraction that optimizes the research process.