Viscoelastic Model Identification of soft tissue Under Compressive Loading

  • سال انتشار: 1394
  • محل انتشار: کنفرانس بین المللی پژوهشی های نوین در علوم مهندسی
  • کد COI اختصاصی: MRECONF01_027
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 929
دانلود فایل این مقاله

نویسندگان

Masoud Moeinzadeh

School of Mechanical Engineering, Collage of Engineering, University of Tehran, Tehran, Iran

Farshid Najafi

School of Mechanical Engineering, Collage of Engineering, University of Tehran, Tehran, Iran

Moosa Ayati

School of Mechanical Engineering,Collage of Engineering, University of Tehran, Tehran, Iran

چکیده

Tissue modeling is a recent and widespread area in medical and engineering sciences. The material properties of various tissues have been measured in-vitro/vivo for decades. In-vitro tests means removing sample from the body and obtaining experimental data, while in-vivo test measures the material properties of tissues in living animals. Viscoelastic models are capable to parameterize time-dependent dynamics and behaviors of biological tissue by relatively small errors. Various forms of viscoelastic models have been developed, where comprehensiveness and simplicity are necessities of modeling of soft tissue mechanical properties. In this paper’s approach ARMAX (Auto-Regressive Moving Average eXogenous input) model is considered. Experimental data are collected from indentation experiment performed on a chicken breast in in-vitro test. A model order selection procedure and Least Squares Error (LSE) identification algorithm have been utilized to estimate model parameters. The effect of measurement noise is considered during identification and eventually it has been shown that a 3rd order ARX model yields the best accuracy accompanied by mathematical simplicity. Accuracy of estimated model is quantitatively validated using FPE (Finite Prediction Error) criterion. Moreover, estimated model output is compared to real experimental data

کلیدواژه ها

ARMAX model, viscoelastic model, Least Squares, model validation, FPE criterion

مقالات مرتبط جدید

اطلاعات بیشتر در مورد COI

COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.

کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.