Hearbeat time series obtained by Holter monitoring of 10 healthy subjects are studied using a nonlinear predictor (S map). The normalized prediction error was calculated as a function of the model control parameter in order to get information on the amount of nonlinearity in the data. Moreover, to search for possible chaotic behavior, the linear correlation coefficient between predicted and real values was calculated as a function of the prediction time. The results of this analysis reveal no clear evidence of chaoticness or nonlinearity in the data. Moreover, for 8 subjects out of 10, the predictability during sleep is better than during the daytime.
Search for nonlinearity in the heartbeat time series.
Di Garbo A;Balocchi R;Carpeggiani C;
1997
Abstract
Hearbeat time series obtained by Holter monitoring of 10 healthy subjects are studied using a nonlinear predictor (S map). The normalized prediction error was calculated as a function of the model control parameter in order to get information on the amount of nonlinearity in the data. Moreover, to search for possible chaotic behavior, the linear correlation coefficient between predicted and real values was calculated as a function of the prediction time. The results of this analysis reveal no clear evidence of chaoticness or nonlinearity in the data. Moreover, for 8 subjects out of 10, the predictability during sleep is better than during the daytime.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
