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سال انتشار: 1390

محل انتشار: نوزدهمین کنفرانس مهندسی برق ایران

تعداد صفحات: 4

نویسنده(ها):

Vahid Abouei – Amirkabir University of Technology (Tehran Polytechnic), Department of Biomedical Eng
Hani Sharifian – Amirkabir University of Technology (Tehran Polytechnic), Department of Biomedical Eng
Farzad Towhidkhah – Amirkabir University of Technology (Tehran Polytechnic), Department of Biomedical
Vahidreza Nafisi – Islamic Azad University (Tehran), Department of Biomedical Eng

چکیده:

Hypotension during hemodialysis session is one of the most common problems occurred in about 20% of hemodialysis patients. Now, one of the problems of dialysis departments is to understand this, because it requires continuous monitoring of blood pressure in dialysis patients. To resolve this problem, in this study using data from patient’s heart rate and blood concentrations that are recorded non-invasively and using neural network, develop a model, in addition to the mapping of these two parameters on blood pressure, be able to predict the patient pressure. By this neural network model, the error percentage of pressure instantly is 8.9% and the average error percentage of the predicted pressure 9% was obtained. Considering the amount of patient’s pressure changes approximately 10-15% will be ignored, and does not produce a particular problem for patients, this model, has the high ability to predict pressure and estimation of situation of the patient