Identification of a Pluse Rate Prediction Model for Activity Sensing Pacer via SOFIA (Self-Organizing Fuzzy Identi fication Algorithm)

Abstract

This paper presents an identification result of a pulse rate prediction model for activity sensing pacer via SOFIA (Self-Organizing Fuzzy identification Algorithm), which is a modeling method for nonlinear complex systems. Input variable and output variable of the pulse rate prediction model are workload and pulse rate, respectively. It is difficult to predict pulse rate because of nonlinearity between the input variable and the output variable. As a result of cornpairing identification result with those of other pacers, it is shown that SOFIA is useful for predicting pulse rate.