A Study on Design Understandability and Interaction of the therapy-specific Robots

Mozhgan Yousefzadeh¹ Negar Yousefzadeh² Sina Alizadeh Tabrizi³

1) PhD Student, Department of Computer Engineering, Ur. C., Islamic Azad University, Urmia, Iran -
2) Master of Physical Education, Sports Sciences, Department of Humanities, Islamic Azad University, Malekan Branch, Tabriz, Iran -
3) PhD Student, Department of Computer Engineering, Ur. C., Islamic Azad University, Urmia, Iran

Publication : National Conference on Information Technology, Nanotechnology, Artificial Intelligence and Technological Futures Studies(itnaf.ir)
Abstract :
The crucial role of artificial intelligence (AI) in devising novel solutions for real-world applications is an enviable fact of the present century, in such way that the applications of the intelligence algorithms of the computer sciences span from sensing of leakage in piping system to automatic analysis and categorization of signals emitted from an electroencephalogram (EEG) device. Recently, autonomous systems, like robots are used for therapeutic purposes, and in analysis and design phases of such systems, there is need for design artifacts reflecting a big picture of the intended system with a highest abstraction level, and these artifacts should be effectively used for communication among all stakeholders, like therapists, parents and engineers. To this end, the present study aims at proposing a novel hybrid modeling framework to synthesis the goal-oriented requirements of Knowledge Acquisition in automated specification (KAOS), considering the precision Unified Modeling Language (UML). The adopted research approaches are qualitative and quantitative approaches. That is, in the former approach, eye tracking can be used, while the latter approach is based on a survey and questionnaire. The findings of the present research proposal can bridge requirements engineering with human-computer interaction, advocating for human-centric AI development in critical healthcare applications.
Keywords : requirements engineering (re) explainable ai (xai) model driven development (mdd) human centered ai domain and application socially assistive robots (sars)