Accessible Requires Authentication Published by De Gruyter October 6, 2018

Non-invasive improved technique for lumbar discus hernia classification based on fuzzy logic

Aleksandar Peulić, Tijana Šušteršič ORCID logo and Miodrag Peulić


This paper presents the improved technique for classification of the type of lumbar discus hernia based on fuzzy logic. The reduced mobility of the foot is one of the symptoms of the disease that occurs because of the displaced discs in the space of two vertebrae. This fact was used for non-invasive discus hernia diagnosis by measuring force values from four sensors placed on both feet (first, second and fourth metatarsal head as well as the heel). Hardware and software systems were constructed for the doctor to perform the measurements and have a graphical representation during the measuring procedure. The procedure included measuring force values of 18 subjects during normal standing, standing on forefeet and heels. All subjects were diagnosed by a specialist with either L4/L5 or L5/S1 discus hernia. Filtering and further preprocessing of acquired values included separation of forefeet and heel segments that were used as inputs to fuzzy system. The results showed that the accuracy of such a fuzzy system was around 72%, and the proposed system correctly recognizes healthy individuals. Obtained information about forces on characteristic points on the foot represents useful data in diagnosis which further can be processed in order to be a supportive tool to doctors.

  1. Author Statement

  2. Research funding: Authors state no funding involved.

  3. Conflict of interest: Authors state no conflict of interest.

  4. Informed consent: Informed consent was obtained from all subjects.

  5. Ethical approval: The research related to human use complied with all the relevant national regulations and institutional policies, was performed in accordance with the tenets of the Helsinki Declaration, and has been approved by the local Ethics Committee.


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Received: 2018-01-27
Accepted: 2018-08-31
Published Online: 2018-10-06
Published in Print: 2019-08-27

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