Diabetic diagnose test based on PPG signal and identification system
Hadis Karimipour, Heydar Toossian Shandiz, Edmond Zahedi
DOI: 10.4236/jbise.2009.26067   PDF    HTML     6,199 Downloads   11,773 Views   Citations


In this paper, photoplethysmogram (PPG) signals from two classes consisting of healthy and diabetic subjects have been used to estimate the parameters of Auto-Regressive Moving Average (ARMA) models. The healthy class consists of 70 healthy and the diabetic classes of 70 diabetic patients. The estimated ARMA parameters have then been averaged for each class, leading to a unique representative model per class. The order of the ARMA model has been selected as to achieve the best classification. The resulting model produces a specificity of %91.4 and a sensitivity of, %100. The proposed technique may find applications in determining the diabetic state of a subject based on a non-invasive signal.

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Karimipour, H. , Shandiz, H. and Zahedi, E. (2009) Diabetic diagnose test based on PPG signal and identification system. Journal of Biomedical Science and Engineering, 2, 465-469. doi: 10.4236/jbise.2009.26067.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] D. Gan, editor, (2003) Diabetes atlas, 2nd Edition, Brussels: International Diabetes Federation, http://www.eatlas.idf.org/webdata/docs/Atlas%202003-Summary.pdf.
[2] H. L. Wee, H. K. Ho, and S. C. Li, (2002) Public awareness of diabetes mellitus in singapore, J .Singapore Med 43(3), 128–134.
[3] Cesar Carlos Romanillos Palerm, (2003) Drug infusion control: An extended direct model reference adaptive control strategy, PhD thesis, Rensselaer Polytechnic Institute, Troy, New York.
[4] V. Carmen Doran, H. Nicolas Hudson, T. Katherine, J. Moorhead, Geoffrey Chase, M. Geoffrey Shaw, and E. Chris Hann, (2004) Derivative weighted active insulin control modelling and clinical trials for ICU patients, Elsevier ju, Medical Engineering & Physics.
[5] V. K. Jayasree, T. V. Sandhya, and P. Radhakrishnan (2008) Non-invasive studies on age related parameters using a blood volume pulse sensor, Measurment Science Reveiw, 8(4), Section 2.
[6] L. Ljung, (1999) System identification: theory for user, Second edition, Prentice Hall.

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