Hardware Support in an Intelligent IT Diagnostic System for Alzheimer’s Disease

Abstract

The report presents an integrated intelligent diagnostic framework combining semantically oriented knowledge representation based on ontologies, hardware acceleration using FPGA and OSTIS concepts in order to increase the efficiency of real-time processing for IT diagnostics of patients with Alzheimer’s disease. An ontology has been developed for such patients, on the basis of which a knowledge base, a solver and an intelligent interface are presented. An FPGA accelerator is proposed, due to which an intelligent IT diagnostic system for patients with ASTHMA provides efficient collection, preprocessing, feature extraction and semantic analysis of voice data, which reduces diagnostic delays and increases decision-making efficiency by about an order of magnitude. The developed ontologies are consistent with the semantic requirements of the OSTIS knowledge management concepts. The developed hybrid CPU-FPGA architecture and the proposed user interface integrate knowledge base queries, hardware management, real-time monitoring and diagnostic conclusion, demonstrating improved user interaction, semantic transparency and operational efficiency.