Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/15846
Title: FPGA Implementation of Expert System for Medical Diagnosis of Disc Hernia Diagnosis Based on Bayes Theorem
Authors: Sustersic, Tijana
Peulic, Aleksandar
Issue Date: 2022
Abstract: The aim of this research is to create a medical expert system based on Bayes theorem to diagnose level of disc hernia based on real foot force measurement signals obtained using sensors and implement the whole system on field programable gate array (FPGA). We have created a database of attributes based on recorded foot force values of 33 patients pre-diagnosed with herniated disc on levels L4/L5 or L5/S1 on the left or right side. The results obtained by software (Matlab) and hardware (FPGA simulation) are matching well, achieving high accuracy, which shows that VHDL implementation of Naïve Bayes theorem for disc hernia diagnostics is adequate. The output on FPGA is easy to understand for any user, as it is implemented as four-bit output where the position of bit value 1 indicates the level of disc herniation. The system is able to distinguish between the healthy subjects and subjects with disc herniation and is able to detect if improvement in stability is present after surgery or physical therapy. Our proposed measurement platform can be coupled with FPGA to create a portable and not expensive tool for real time signal acquisition, processing and decision support system in disc hernia diagnosis and post-surgical recovery.
URI: https://scidar.kg.ac.rs/handle/123456789/15846
Type: article
DOI: 10.1142/S021812662350038X
ISSN: 0218-1266
SCOPUS: 2-s2.0-85138175384
Appears in Collections:Faculty of Engineering, Kragujevac

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