Abstract—TENS (Transcutaneous Electrical nerve Stimulation) is explained as stimulating nerves via skin to decrease the pain. The studies about TENS were related to investigate its effects on animals and humans. In this study, the problem is to improve a TENS model by investigating the effective parameters in humans. Skin conductance and skin thickness were chosen as effective parameters. By considering the ailments which cause pain, four implementation zones were studied. For modelling, ANFIS (Adaptive Neuro – Fuzzy Inference System) was employed. Average Training Error changes between 0.149-0.533, while Average Testing Error changes between 0.823-1.0815. This corresponds to maximum 1.0815 mA swing in the electric current that is applied to patient. This swing doesn’t cause a negative effect on patient. By means of this study, time saving and minimizing human originated errors were provided while applying TENS. Besides, TENS can be applied on the patients who have communication difficulties.
Index Terms—TENS, skin impedance, skin thickness, ANFIS
Esra Satir is with Selcuk University, Technical Education Faculty,
Computer and Electronic Education, 42003, Konya, Turkey.
Hakan Isik is with Selcuk University, Technology Faculty, Electronic
Engineering, 42003, Konya, Turkey (Tel.: 00903322233331, fax:
00903322412179, e-mail address: esatir@selcuk.edu.tr).
Cite: Esra Satir and Hakan Isik, "TENS Modelling Via ANFIS," International Journal of Future Computer and Communication vol. 1, no. 2, pp. 173-175, 2012.
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