Dynamic modeling of breast tissue with application of model reference adaptive system identification technique based on clinical robot-assisted palpation.
Accurate identification of breast tissue's dynamic behavior in physical examination is critical to successful diagnosis and treatment. In this study a model reference adaptive system identification (MRAS) algorithm is utilized to estimate the dynamic behavior of breast tissue from mechanical stress-strain datasets. A robot-assisted device (Robo-Tac-BMI) is going to mimic physical palpation on a 45 year old woman having a benign mass in the left breast. Stress-strain datasets will be collected over 14 regions of both breasts in a specific period of time. Then, a 2nd order linear model is adapted to the experimental datasets. It was confirmed that a unique dynamic model with maximum error about 0.89% is descriptive of the breast tissue behavior meanwhile mass detection may be achieved by 56.1% difference from the normal tissue.
Department of Mechanical Engineering, K. N. Toosi University of Technology, P.O. Box 19395-1999, Tehran, Iran. Electronic address: miladkeshavarzseifi@yahoo.com.
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Keshavarz
Department of Mechanical Engineering, K. N. Toosi University of Technology, P.O. Box 19395-1999, Tehran, Iran. Electronic address: mojra@kntu.ac.ir.
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Mojra
D001696:Biomechanical Phenomena; D001940:Breast / Q000166:cytology*; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation*; D005260:Female; D006801:Humans; D055595:Mechanical Phenomena; D008875:Middle Aged; D008954:Models, Biological; D010173:Palpation / Q000295:instrumentation*; D012371:Robotics / Q000295:instrumentation*
Adaptive; Artificial tactile sensing; Dynamic model; Identification; Model reference system; Soft tissue