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dc.creatorŠušteršič, Tijana
dc.creatorPeulić, Aleksandar
dc.date.accessioned2023-03-24T09:59:31Z
dc.date.available2023-03-24T09:59:31Z
dc.date.issued2023
dc.identifier.issn0218-1266
dc.identifier.urihttp://gery.gef.bg.ac.rs/handle/123456789/1220
dc.description.abstractThe 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.sr
dc.language.isoensr
dc.publisherWorld Scientific Publishing Co Pte Ltdsr
dc.rightsclosedAccesssr
dc.sourceJournal of Circuits, Systems and Computerssr
dc.subjectDisc hernia diagnosissr
dc.subjectBayes theoremsr
dc.subjectmedical expert systemsr
dc.subjectFPGAsr
dc.titleFPGA Implementation of Expert System for Medical Diagnosis of Disc Hernia Diagnosis Based on Bayes Theoremsr
dc.typearticlesr
dc.rights.licenseARRsr
dc.citation.volume32
dc.citation.issue3
dc.citation.spage2350038
dc.citation.rankM23
dc.identifier.wos00084936960000
dc.identifier.doi10.1142/S021812662350038X
dc.identifier.scopus2-s2.0-85138175384
dc.type.versionpublishedVersionsr


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