Biological information sensing using an autoregressive moving average model

Health-care support at home and care facilities is a very important issue in many developed countries because of the arrival of increasingly aging society. Heart rate is one of very important vital signs which indicate daily health state of a person. However, the heart rate is difficult to be estimated because the heart rate signals are weak much less than breathing signal. This paper suggests a heart rate estimation system employing Autoregressive moving average model. which is robust to the body movement based on Autoregressive moving average model performs noise reduction with wavelet thresholding to signal by Stepped-FM UWB sensor.