Estimation of Bladder Pressure from Pudendal Electrical Activity of Rabbit Based on the Self-Organized RecurrentNeural Network

  • سال انتشار: 1402
  • محل انتشار: ششمین همایش بین المللی زیست شناسی و علوم زمین
  • کد COI اختصاصی: BIOLOGY06_083
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 204
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نویسندگان

Meisam Baradaran

Biomedical Engineering Research Center, Mashhad Branch, Islamic Azad University, Mashhad, Iran

Hamidreza Kobravi

Biomedical Engineering Research Center, Mashhad Branch, Islamic Azad University, Mashhad, Iran

Ali Mighimi

Biomedical Engineering Research Center, Mashhad Branch, Islamic Azad University, Mashhad, Iran

Saleh Lashkari

Rayan Center for Neuroscience & Behavior, Department of Biology, Faculty of Science, Ferdowsi University of Mashhad,Mashhad, Iran

چکیده

Hyper-reflexive and loss of voluntary control is a common result of neurological diseasessuch as spinal cord injury. Electrical stimulation is an alternative treatment forhyperreflexia. To inhibit the bladder, we need to detect nascent bladder contraction.Previous studies reported that electrical activity of the pudendal nerve is correlated withbladder pressure. The aim of this study is developing a neural network model for estimatingbladder pressure during bladder contraction based on the electrical activity of the pudendalnerve. Three models of neural networks were used to identify the relationship betweenbladder pressure and pudendal nerve activity: NARX, GRNN, and SRBFNN. Ten adultmale rabbits were used in this study. Five experiments were performed to record bladderpressure at different conditions. Finally, to evaluate the performance of the ENG -pressureneural network model, the normalized root-mean-square (NRMS) index was calculated.NRMS for NARX, GRNN, and SRBFNN were obtained ۱۲.۱۶, ۱۰.۴۹, and ۹.۴۲,respectively. Results indicate that the SRBFNN network has less NRMS error than theother networks. Results shows proposed research is a promising approach to detect nascentbladder contraction.

کلیدواژه ها

Hyperreflexia, Spinal cord injury, Neural network, Bladder

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