A High-Level Adaptation Toolkit for Unified Integration of Software Systems with Neural Interfaces
Svetlana Igorevna Chuprina, Ivan Aleksandrovich Labutin · Scientific Visualization · 2024
The paper is devoted to the urgent problem of automating the process of integrating different types of neurointerfaces into the infrastructure of the Internet of Things. Due to the low-level nature of these devices and related tools, integrating neurointerfaces with a wide range of IoT devices is a complex task requiring specialized knowledge and skills in the fields of neuroscience and signal processing. To tackle the significant challenge of automating such kind integration we continue to improve our previously proposed ontology-driven methods and tools for seamless integration of software systems with neural interfaces in a unified way. The presented notable improvements include the introduction of a new data processing pipeline that utilizes a portable device to validate the effectiveness of the system and the development of an intuitive graphical user interface enabling real-time data visualization facilities that provides an easy and understandable feedback.