این سایت در حال حاضر پشتیبانی نمی شود و امکان دارد داده های نشریات بروز نباشند
Journal of Computational and Applied Research in Mechanical Engineering - JCARME، جلد ۱۴، شماره ۱، صفحات ۰-۰
عنوان فارسی
چکیده فارسی مقاله
کلیدواژه‌های فارسی مقاله
عنوان انگلیسی Prediction of sudden cardiac death based on fundamental changes in nonlinear characteristics of cardiac signals
چکیده انگلیسی مقاله To quickly detect sudden cardiac death (SCD), it is decisive to gather suitable information and enhance the accuracy of the diagnosis algorithms. Consequently, in the present study, the heart rate variability (HRV) signal of subjects who experience sudden cardiac death (SCD) is studied. We looked at people's heart signals for one hour before something happens to see if there are any noticeable changes. The patients' HRV signals are segregated into 5-minute parts in the suggested approach. Each section is divided into four shorter signals. Thereupon, the energy and instant amplitude of each sub-signal are examined. The information flows between signal strengths and measuring the complexity of energy sub-signals are checked. A significant change from its former section is identified. A support vector machine classifier benefits from detecting individuals exposed to SCD by considering significant changes as indicators of the SCD process. It can anticipate SCD 15 minutes before it happens. Not restricted to any special subclass of cardiac diseases, this technique has priority. To evaluate the specificity of the algorithm, it has been used not only with patients having SCD but also with individuals who are healthy, as well as those with coronary artery disease (CAD) and congestive heart failure (CHF), analyzing their HRV signals. The specificity values for normal, CHF, and CAD patients are 100%, 93.3%, and 95.6%, respectively, in the results.
کلیدواژه‌های انگلیسی مقاله Sample entropy, Teager-Kaiser operator, Transfer entropy, Local characteristic decomposition, Heart rate variability
نویسندگان مقاله Adel Maghsoudpour |
Department of Mechanical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.

Ali Dorostghol |
Department of Mechanical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

Ali Ghaffari |
Department of Mechanical Engineering, K.N. Toosi University of Technology. NO. 19 Pardis St., Mollasadra Ave., Vanak Sq., Tehran, Iran.

Mansour NikkhahBahrami |
Department of Mechanical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

نشانی اینترنتی https://jcarme.sru.ac.ir/article_2107_f3d455bea95cf729677b8ed24fc9d656.pdf
فایل مقاله فایلی برای مقاله ذخیره نشده است
کد مقاله (doi)
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده
نوع مقاله منتشر شده
برگشت به: صفحه اول پایگاه   |   نسخه مرتبط   |   نشریه مرتبط   |   فهرست نشریات