An algorithm for rapid trend detection of physiological parameter is introduced for ambulatory monitoring applications. Kalman prediction error of monitored parameter is used to estimate the physiological status and detect rapid change. With this algorithm, rapid trend during ambulatory monitoring can be found to predict disease exacerbation; and it is also applied to identify outliers of measurement due to poor signal quality to avoid false alarms.