Abstract: The improved pulse oximeter preprocesses the sets of red and infrared signals received from the probe to remove ambient light, to remove noise, and to de-exponeniate the signals. The linearity of the processed red and infrared signals allows the use of statistical techniques such as linear regression and linear correlation to fit a best fit straight line to the set of pairs of processed red and infrared data points and to measure the goodness of the straight line fit to these data points. The result of this analysis is a linear regression slope and a goodness of fit correlation coefficient. The correlation coefficient is a measure of the linearity of the input data points and, if less than a predetermined threshold, it indicates that a distorted signal has been received from the probe. This permits the pulse oximeter to detect probe off conditions and/or motion in the patient.

Abstract: The improved pulse oximeter preprocesses the sets of red and infrared signals received from the probe to remove ambient light, to remove noise, and to de-exponeniate the signals. The linearity of the processed red and infrared signals allows the use of statistical techniques such as linear regression and linear correlation to fit a best fit straight line to the set of pairs of processed red and infrared data points and to measure the goodness of the straight line fit to these data points. The result of this analysis is a linear regression slope and a goodness of fit correlation coefficient. The correlation coefficient is a measure of the linearity of the input data points and, if less than a predetermined threshold, it indicates that a distorted signal has been received from the probe. This permits the pulse oximeter to detect probe off conditions and/or motion in the patient.

Abstract: The improved pulse oximeter preprocesses the sets of red and infrared signals received from the probe to remove ambient light to remove noise and to de-exponentiate the signals. The linearity of the processed red and infrared signals allows the use of statistical techniques such as linear regression and linear correlation to fit a straight line to the set of pairs of processed red and infrared data points and to best measure the goodness of the straight line fit to these data points. The result of this analysis is a linear regression slope and a goodness of fit correlation coefficient. The correlation coefficient is a measure of the linearity of the input data points and if less than a predetermined threshold it indicates that a distorted signal has been received from the probe. This permits the pulse oximeter to detect probe off conditions and/or motion in the patient.

Abstract: The improved pulse oximeter preprocesses the sets of red and infrared signals received from the probe to remove ambient light, to remove noise, and to de-exponeniate the signals. The linearity of the processed red and infrared signals allows the use of statistical techniques such as linear regression and linear correlation to fit a best fit straight line to the set of pairs of processed red and infrared data points and to measure the goodness of the straight line fit to these data points. The result of this analysis is a linear regression slope and a goodness of fit correlation coefficient. The correlation coefficient is a measure of the linearity of the input data points and, if less than a predetermined threshold, it indicates that a distorted signal has been received from the probe. This permits the pulse oximeter to detect probe off conditions and/or motion in the patient.