Dergiler / Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi / 2013 / Cilt: 17 - Sayı: 1
Fibromiyalji Hastalarında Sempatik Deri Cevabının Psikolojik Test Skorlarına Etkisinin YSA Kullanılarak İncelenmesi
- Sayfa
- 27–32
- DOI
- —
Özet
In this study, psychological tests such as Visual Analogue Pain Scale, Verbal Pain Scale, Beck Depression Inventory, Beck Anxiety Inventory, Hamilton Depression Rating Scale and Hamilton Anxiety Scale were applied to the selected healthy subjects and patients with Fibromyalgia Syndrome (FMS) in Suleyman Demirel University, Faculty of Medicine, Department of Physical Medicine and Rehabilitation and the scores were recorded. A measurement system was established in the same department of the university to measure the sympathetic skin response (SSR) from the subjects. The SSR was measured and recorded. The parameters such as latency time, maximum amplitude and the elapsed time were calculated by using Matlab software from the recorded SSR data. SSR parameters were added to the scores and diagnosis accuracy percentages of the FMS calculated by using artificial neural networks (ANNs). Obtained results from the simulations showed that the specified parameters of the SSR and FMS were concerned and these parameters can be used as a diagnostic method in FMS.
Abstract
In this study, psychological tests such as Visual Analogue Pain Scale, Verbal Pain Scale, Beck Depression Inventory, Beck Anxiety Inventory, Hamilton Depression Rating Scale and Hamilton Anxiety Scale were applied to the selected healthy subjects and patients with Fibromyalgia Syndrome (FMS) in Suleyman Demirel University, Faculty of Medicine, Department of Physical Medicine and Rehabilitation and the scores were recorded. A measurement system was established in the same department of the university to measure the sympathetic skin response (SSR) from the subjects. The SSR was measured and recorded. The parameters such as latency time, maximum amplitude and the elapsed time were calculated by using Matlab software from the recorded SSR data. SSR parameters were added to the scores and diagnosis accuracy percentages of the FMS calculated by using artificial neural networks. Obtained results from the simulations showed that the specified parameters of the SSR and FMS were concerned and these parameters can be used as a diagnostic method in FMS.