Abstract: Disclosed herein are methods and systems related to respiration. The methods and systems are related to the analysis of a subject's respiration. In some forms the methods and system can use a nonlinear analysis.

Abstract: Biological outcomes are detected and/or predicted by analyzing biological data containing R-R intervals (RRi). The biological data can be analyzed by performing nonlinear analysis. The biological data can be analyzed when there is minimal noise in the data. The noise in the biological data is minimal before the data is converted to real-time or after the data has been manipulated.

Abstract: Biological anomalies are detected and/or predicted by analyzing input biological or physical data using a data processing routine. The data processing routine includes a set of application parameters associated with biological data correlating with the biological anomalies. The data processing routine uses an algorithm to produce a data series, e.g., a PD2i data series. The data series is used to detect or predict the onset of the biological anomalies. To reduce noise in the data series, the slope is set to a predetermined number if it is less than a predetermined value. To further reduce noise, a noise interval within the data series is determined and, if the noise interval is within a predetermined range, the data series is divided by another predetermined number, and new values are produced for the data series.

Abstract: Cerebral disorders are detected and/or predicted by analyzing input biological or physical data using a data processing routine. The data processing routine includes a set of application parameters associated with biological data correlating with the biological anomalies. The data processing routine uses an algorithm to produce a data series, e.g., a PD2i data series. The data series is used to detect or predict the onset of the cerebral disorders. To reduce noise in the data series, the slope is set to a predetermined number if it is less than a predetermined value. To further reduce noise, a noise interval within the data series is determined and, if the noise interval is within a predetermined range, the data series is divided by another predetermined number, and new values are produced for the data series.