Determination of New Bio Signal and Tests Alternative to Verbal Pain Scale for Diagnosing Fibromyalgia Syndrome

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Muhammed Kursad Ucar 1,* Mehmet Recep Bozkurt 1 Ferda Bozkurt 1

1. Department of Electrical and Electronics Engineering, Sakarya, 54187, Turkey

* Corresponding author.


Received: 27 Nov. 2015 / Revised: 5 Jan. 2016 / Accepted: 9 Feb. 2016 / Published: 8 Mar. 2016

Index Terms

Biomedical Signal Analysis, Fibromyalgia Syndrome, Verbal Pain Scale, Sympathetic Skin Response, Biomedical Signal Classification


In this study; values obtained through the analysis of blood samples, taken under laboratory conditions, from patients diagnosed with fibromyalgia syndrome and healthy subjects and the sympathetic skin response parameters were used. With the aim of classifying verbal pain scale, which is one of the psychological test scores used for fibromyalgia syndrome diagnosis; relation between the sympathetic skin response effect on other test data and the verbal pain scale were reviewed by using different conditions of available data. Within this framework, three different algorithms were used for classification with high accuracy rates. These algorithms are: Multi-Layer Feed-Forward Neural Networks, Probabilistic Neural Network and Radial Basis Function Neural Network. For Multi-Layer Feed-Forward Neural Networks classification algorithm, classification was done with three different training algorithms, Levenberg-Marquardt back propagation, Resilient back propagation and the Scaled conjugate gradient back propagation and the results were compared elaborately. Based on the results, by using all variables the following accuracy rates were obtained: 68.2% accuracy with Levenberg-Marquardt training algorithm, 77.3% accuracy with the Resilient back propagation training algorithm, and 68.18% accuracy with the Scaled conjugate gradient training algorithm. These success rates show that there is a relationship between verbal pain scale, sympathetic skin response and other test data.

Cite This Paper

Muhammed Kürşad Uçar, Mehmet Recep Bozkurt, Ferda Bozkurt,"Determination of New Bio Signal and Tests Alternative to Verbal Pain Scale for Diagnosing Fibromyalgia Syndrome", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.8, No.3, pp.1-8, 2016. DOI: 10.5815/ijigsp.2016.03.01


[1]O. Elmas, S. Yildiz, S. Bilgin, S. Demirci, S. Comlekci, H. R. Koyuncuoglu, S. Akkus, O. H. Colak, E. Koklukaya, E. Arslan, O. Ozkan, and G. Bilgin, "Physiological parameters as a tool in the diagnosis of fibromyalgia syndrome in females: A preliminary study.," Life Sci., vol. 145, pp. 51–56, Dec. 2015.

[2]Ö. Özkan, "Use of sympathetic skin response along with artificial neural networks in diagnosing of fibromyalgia syndrome," Sakarya University, 2012.

[3]M. Shipley, "Chronic widespread pain and fibromyalgia syndrome," Medicine (Baltimore)., vol. 42, no. 5, pp. 271–274, May 2014.

[4]S. Bilgin, E. Arslan, O. Elmas, S. Yildiz, O. H. Colak, G. Bilgin, H. R. Koyuncuoglu, S. Akkus, S. Comlekci, and E. Koklukaya, "Investigation of the relationship between anxiety and heart rate variability in fibromyalgia: A new quantitative approach to evaluate anxiety level in fibromyalgia syndrome.," Comput. Biol. Med., vol. 67, pp. 126–35, Dec. 2015.

[5]S. Fischer, J. M. Doerr, J. Strahler, R. Mewes, K. Thieme, and U. M. Nater, "Stress exacerbates pain in the everyday lives of women with fibromyalgia syndrome-The role of cortisol and alpha-amylase.," Psychoneuroendocrinology, vol. 63, pp. 68–77, Jan. 2016.

[6]R. Goulart, C. Pessoa, and I. Lombardi, "Psychological aspects of juvenile fibromyalgia syndrome: a literature review," Rev. Bras. Reumatol. (English Ed., Oct. 2015.

[7]T. V Ting, K. Barnett, A. Lynch-Jordan, C. Whitacre, M. Henrickson, and S. Kashikar-Zuck, "2010 American College of Rheumatology Adult Fibromyalgia Criteria for Use in an Adolescent Female Population with Juvenile Fibromyalgia.," J. Pediatr., vol. 169, pp. 181–187.e1, Nov. 2015.

[8]M. Boden, "A guide to recurrent neural networks and backpropagation," Electr. Eng., no. 2, pp. 1–10, 2001.

[9]M. R. Bozkurt, "Preprocessing and Classification of EMG Signals by Using Modern Methods," Sakarya University, 2007.

[10]M. Riedmiller and H. Braun, "A direct adaptive method for faster backpropagation learning: the RPROP algorithm," IEEE Int. Conf. Neural Networks, vol. 1, pp. 586–591, 1993.

[11]N. D. Ahuja, a. K. Agarwal, N. M. Mahajan, N. H. Mehta, and H. N. Kapadia, "GSR and HRV: its application in clinical diagnosis," 16th IEEE Symp. Comput. Med. Syst. 2003. Proceedings., 2003.

[12]T. Saxena, S. Patidar, and M. Saxena, "Assessment of left ventricular ejection force and sympathetic skin response in normotensive and hypertensive subjects: A double- blind observational comparative case–control study," Indian Heart J., Jan. 2016.

[13]S. Ozgocmen, T. Yoldas, R. Yigiter, A. Kaya, and O. Ardicoglu, "R-R Interval Variation and Sympathetic Skin Response in Fibromyalgia," Arch. Med. Res., vol. 37, pp. 630–634, 2006.

[14]S. Bolat and Ö. Kalenderli, "Electrode Contour Optimization by Artificial Neural Network with Levenberg-Marquardt Algorithm," in IJCI Proceedings of Intl. XII. Turkish Symposium on Artificial Intelligence and Neural Networks, 2003, vol. 1, pp. 408–412.

[15]L. S. H. Ngia and J. Sjoberg, "Efficient training of neural nets for nonlinear adaptive filtering using a recursive Levenberg-Marquardt algorithm," IEEE Trans. Signal Process., vol. 48, no. 7, pp. 1915–1927, 2000.

[16]M. F. Møller, "A scaled conjugate gradient algorithm for fast supervised learning," Neural Networks, vol. 6, no. 4, pp. 525–533, Jan. 1993.

[17]R. Alpar, Applied Statistic and Validation - Reliability. Detay Publishing, 2010.

[18]D. F. Specht, "Probabilistic neural networks," Neural Networks, vol. 3, no. 1, pp. 109–118, 1990.

[19]T. Çakir, D. Evcik, Ü. Dündar, İ. Yiğit, and V. Kavuncu, "Evaluation of Sympathetic Skin Response and F Wave in Fibromyalgia Syndrome Patients," vol. 26, no. 1, pp. 38–43, 2011.

[20]J. McBeth, G. J. Macfarlane, S. Benjamin, S. Morris, and A. J. Silman, "The association between tender points, psychological distress, and adverse childhood experiences: a community-based study.," Arthritis Rheum., vol. 42, no. 7, pp. 1397–404, Jul. 1999.

[21]A. Dönmez and N. Erdoğan, "Fibromyalgia Syndrome," Clin. Dev., pp. 60–64, 1990.

[22]L. Ozdemir, E. Pιnarcι, B. N. Akay, and A. Akyol, "Effect of methylprednisolone injection speed on the perception of intramuscular injection pain.," Pain Manag. Nurs., vol. 14, no. 1, pp. 3–10, Mar. 2013.

[23]M. McCaffery and A. Beebe, "Pain: Clinical Manual for Nursing Practice: Margo McCaffery, Alexandra Beebe, Jane Latham: 9780723419921: Books," 1994. [Online]. Available: [Accessed: 25-Jan-2016].

[24]C. Mathworks, "Simscape TM User ' s Guide R 2015 b," 2015.

[25]M. Singh, B. . Panigrahi, and R. P. Maheshwari, "Transmission line fault detection and classification," 2011 Int. Conf. Emerg. Trends Electr. Comput. Technol., pp. 15–22, 2011.