NDLI: Novel Method of Using Dynamic Electrical Impedance Signals for Noninvasive Diagnosis of Knee Osteoarthritis

Content Provider	IEEE Xplore Digital Library
Author	Gajre, S.S. Anand, S. Singh, U. Saxena, R.K.
Copyright Year	2006
Description	Author affiliation: Shri Guru Gobind Singhji Inst. of Eng. & Technol., Maharashtra (Gajre, S.S.)
Abstract	Osteoarthritis (OA) of knee is the most commonly occurring non-fatal irreversible disease, mainly in the elderly population and particularly in female. Various invasive and non-invasive methods are reported for the diagnosis of this articular cartilage pathology. Well known techniques such as X-ray, computed tomography, magnetic resonance imaging, arthroscopy and arthrography are having their disadvantages, and diagnosis of OA in early stages with simple effective noninvasive method is still a biomedical engineering problem. Analyzing knee joint noninvasive signals around knee might give simple solution for diagnosis of knee OA. We used electrical impedance data from knees to compare normal and osteoarthritic subjects during the most common dynamic conditions of the knee, i.e. walking and knee swing. It was found that there is substantial difference in the properties of the walking cycle (WC) and knee swing cycle (KS) signals. In experiments on 90 pathological (combined for KS and WC signals) and 72 normal signals (combined), suitable features were drawn. Then signals were used to classify as normal or pathological. Artificial multilayer feed forward neural network was trained using back propagation algorithm for the classification. On a training data set of 54 signals for KS signals, the classification efficiency for a test set of 54 was 70.37% and 85.19% with and without normalization respectively wrt base impedance. Similarly, the training set of 27 WC signals and test set of 27 signals resulted in 77.78% and 66.67% classification efficiency. The results indicate that dynamic electrical impedance signals have potential to be used as a novel method for noninvasive diagnosis of knee OA
Sponsorship	IEEE EMB
Starting Page	2207
Ending Page	2210
File Size	227572
Page Count	4
File Format	PDF
ISBN	1424400325
ISSN	1557170X
DOI	10.1109/IEMBS.2006.260671
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Impedance Noninvasive treatment Knee Osteoarthritis Pathology Optical wavelength conversion X-ray imaging Legged locomotion Multi-layer neural network Testing
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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