Publication

Abstract : Cardiovascular diseases like atherosclerosis, peripheral arterial disease, coronary heart disease, etc. are dangerous and hence early detection of such diseases is important in the field of medical sciences. The existing methods used for diagnosing diseases are time-consuming and highly expensive. On the other hand, experimentation with Cardiovascular System (CVS) for the analysis and decision making for treatment is unsafe and hence it is important to develop an accurate CVS model. It is observed from the existing integer order cardiovascular models that the viscoelastic property of four chambers is not taken into consideration. To accommodate these properties, this paper proposes a fractional order model by introducing fractionality to the dynamical equation of CVS. Further, an optimization method is presented to obtain the fractionality of different chambers by minimizing the integral square error between clinical data of healthy human and model output using Cuckoo search, Firefly and Accelerated particle swarm algorithms. The results indicate that fractional models are better than integer order CVS models and specifically, the Firefly algorithm provides a better fractional model than the models obtained from other algorithms. Further, the best model obtained using firefly algorithm is considered for simulating the diseases (i) increased arterial stiffness and (ii) atherosclerosis.