Non-invasive diagnosis of osteoarthritis using Vibroarthrography approach / Farshad Golshan
Osteoarthritis (OA) is one of the most common type of disease among elderly and athletes. Although OA is widely known by doctors and researchers, the current diagnosis methods available for detection of OA are either expensive and invasive or very inconvenient for an average person. Early detection...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Published: |
2018
|
| Subjects: | |
| Online Access: | http://studentsrepo.um.edu.my/9101/1/Farshad_Golshan.bmp http://studentsrepo.um.edu.my/9101/8/farshad.pdf http://studentsrepo.um.edu.my/9101/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Osteoarthritis (OA) is one of the most common type of disease among elderly and athletes. Although OA is widely known by doctors and researchers, the current diagnosis methods available for detection of OA are either expensive and invasive or very inconvenient for an average person. Early detection of osteoarthritis is of utmost importance due to its progressive nature. If OA is left unintended, it can lead to major issues for the patients such as joint bone deformity and infuriating joint pain. This study focuses on the development of a much more suitable method for easy and efficient early diagnosis of osteoarthritis. The previous studies done on non-invasive detection of OA have proven that use of Vibroarthrography (VAG) technique can indeed provide clear results on detecting the difference between OA and healthy knee’s Vibroarthrography signals produced from vibration and acoustic emission of the knee joint while performing an action. To continue the advancement in the Field of non-invasive diagnosis of OA, current proposed researched began tasting on different types of already existing sensors (mainly piezo element, ultrasound sensor and accelerometer) for detection of vibration and acoustic emission of the knee non-invasively. The results of the sensors testing showed that the accelerometer is able to produce much better results compared to other selected sensors. To evaluate and develop a suitable testing method for detection of OA on the knee, a data logging tool was developed to remove the noise from the vibration taken from the sensor and store the data. Tests were done on healthy subjects as well as UMMC patients with the supervision of physicians. The final outcome shows satisfactory results with 95% classification accuracy in differentiating OA knee from healthy knee. This study also discovered major difference between left and right knee VAG differences for both OA and healthy subjects which may provide more answers about the main cause of OA and method of preventing it. |
|---|