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A method and an apparatus to analyze two measured signals that are modeled as containing desired and undesired portions such as noise, FM and AM modulation. Coefficients relate the two signals according to a model defined in accordance with the present invention. In one embodiment, a transformation

A method and an apparatus to analyze two measured signals that are modeled as containing desired and undesired portions such as noise, FM and AM modulation. Coefficients relate the two signals according to a model defined in accordance with the present invention. In one embodiment, a transformation is used to evaluate a ratio of the two measured signals in order to find appropriate coefficients. The measured signals are then fed into a signal scrubber which uses the coefficients to remove the unwanted portions. The signal scrubbing is performed in either the time domain or in the frequency domain. The method and apparatus are particularly advantageous to blood oximetry and pulserate measurements. In another embodiment, an estimate of the pulserate is obtained by applying a set of rules to a spectral transform of the scrubbed signal. In another embodiment, an estimate of the pulserate is obtained by transforming the scrubbed signal from a first spectral domain into a second spectral domain. The pulserate is found by identifying the largest spectral peak in the second spectral domain.

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1. A pulse oximetry system for the determination of a physiological parameter wherein said pulse oximetry system is configured to remove motion artifacts from physiological signals, comprising: an optical sensor for providing said pulse oximetry system with photo-plethysmographic data, wherein said

1. A pulse oximetry system for the determination of a physiological parameter wherein said pulse oximetry system is configured to remove motion artifacts from physiological signals, comprising: an optical sensor for providing said pulse oximetry system with photo-plethysmographic data, wherein said sensor comprises a light emitting diode for emitting light and a photo-detector for detecting said light, wherein said detected light contains information on the photo-plethysmographic data; anda processor for processing the photo-plethysmographic data, wherein said processor is configured to: (a) acquire said photo-plethysmographic data;(b) transform the photo-plethysmographic data into frequency domain data;(c) analyze the frequency domain data to determine a result;(d) determine a time domain data photo-plethysmographic signal using said result of said analysis of said frequency domain data;(e) analyze a mathematical transformation of the time domain photo-plethysmographic signal to identify parameters;(f) use said parameters to determine whether an artifact is present and to identify a physiological signal; and(g) determine a physiological parameter from said physiological signal. 2. The system of claim 1 wherein the physiological parameter comprises pulse rate. 3. The system of claim 1 wherein the mathematical transformation comprises a frequency domain transform. 4. The system of claim 1 wherein analyzing the mathematical transformation of the time domain photo-plethysmographic signal comprises identifying peaks. 5. The system of claim 1 wherein the processor is configured to condition the photo-plethysmographic data prior to transforming the data into the frequency domain. 6. The system of claim 1 wherein the processor is configured to analyze the frequency domain data to locate candidate spectral peaks before determining the time domain photo-plethysmographic signal, wherein analyzing said transformed data to locate candidate spectral peaks comprises the steps of assigning a largest power amplitude from said data as a primary candidate spectral peak and assigning a power amplitude that is not a harmonic of said primary candidate spectral peak as a secondary candidate spectral peak. 7. The system of claim 1 wherein analyzing said mathematical transformation of the photo-plethysmographic signal comprises categorizing the signal as corresponding to a predetermined cardiac signal. 8. The system of claim 7 wherein categorizing the signal comprises determining at least one height of a component of the signal. 9. The system of claim 1 wherein analyzing said mathematical transformation of the photo-plethysmographic signal comprises the steps of: determining a plurality of components of the signal, calculating a plurality of heights of said components, and applying a criterion for detecting a predefined set of components. 10. The system of claim 1 wherein using said parameters to identify a physiological signal comprises determining a score indicative of a likelihood that said parameters correspond to said physiological signal. 11. A pulse oximetry system for the determination of a physiological parameter wherein said pulse oximetry system is configured to remove motion artifacts from physiological signals, comprising: an optical sensor for providing said pulse oximetry system with photo-plethysmographic data, wherein said sensor comprises a light emitting diode for emitting light and a photo-detector for detecting said light, wherein said detected light contains information on the photo-plethysmographic data; anda processor for processing the photo-plethysmographic data, wherein said processor is configured to: (a) analyze frequency domain data derived from said photo-plethysmographic data to determine a result,(b) determine a time domain photo-plethysmographic signal using said result of said analysis of said frequency domain data;(c) analyze a mathematical transformation of the time domain photo-plethysmographic signal to identify parameters; and(d) use the identified parameters to determine whether an artifact is present and to identify a physiological signal. 12. A pulse oximetry system for the determination of a physiological parameter wherein said pulse oximetry system is configured to remove motion artifacts from physiological signals, comprising: a sensor for providing said pulse oximetry system with plethysmographic data, wherein said sensor comprises a light emitter for emitting light and a photo-detector for detecting said light, wherein said detected light contains information on the plethysmographic data; anda processor for processing the plethysmographic data, wherein said processor is configured to: (a) acquire said plethysmographic data;(b) transform the plethysmographic data into frequency domain data;(c) analyze the frequency domain data to determine a result;(d) determine a time domain data plethysmographic signal using said result of said analysis of said frequency domain data;(e) analyze the time domain plethysmographic signal to identify parameters;(f) use said parameters to discriminate a physiological signal from a distortion; and(g) determine a physiological parameter from said physiological signal. 13. The system of claim 12 wherein the physiological parameter comprises pulse rate. 14. The system of claim 12 wherein analyzing the time domain plethysmographic signal comprises determining and analyzing a frequency domain transform. 15. The system of claim 14 wherein analyzing the frequency domain transform of the time domain plethysmographic signal comprises identifying peaks. 16. The system of claim 12 wherein the processor is configured to filter the plethysmographic data prior to transforming the data into the frequency domain. 17. The system of claim 6 wherein filtering said plethysmographic data comprises band pass filtering. 18. The system of claim 12 wherein the processor is configured to analyze the frequency domain data to locate candidate spectral peaks before determining time domain plethysmographic signal data, wherein analyzing said frequency domain data to locate candidate spectral peaks comprises determining power amplitudes of a candidate spectral peak and a spectral peak that is not a harmonic of said candidate spectral peak. 19. The system of claim 12 wherein the processor is configured to analyze the frequency domain data to locate candidate spectral peaks before determining time domain plethysmographic signal data using the frequency domain data. 20. The system of claim 12 wherein the processor is configured to identify peaks after determining the time domain data plethysmographic signal. 21. The system of claim 20 wherein a frequency domain transformation of the time domain plethysmographic signal is analyzed to determine a cardiac physiologic signal characteristic. 22. The system of claim 21 wherein analyzing the frequency domain transformation of the time domain plethysmographic signal comprises categorizing a cardiac spectrum, wherein said cardiac spectrum consists of a plurality of spectral lines. 23. The system of claim 22 wherein analyzing the frequency domain transformation of the time domain plethysmographic signal further comprises the step of determining at least one height of said spectral lines. 24. The system of claim 21 wherein analyzing the frequency domain transformation of the time domain plethysmographic signal comprises the steps of: determining a plurality of spectral lines, calculating a plurality of heights of said spectral lines, and applying a criterion for detecting a predefined category of a set of spectral lines. 25. The system of claim 12 wherein using said parameters to discriminate a physiological signal from a distortion comprises classifying a harmonic set with a score. 26. A pulse oximetry system for the determination of a physiological parameter wherein said pulse oximetry system is configured to remove motion artifacts from physiological signals, comprising: a sensor for providing said pulse oximetry system with plethysmographic data, wherein said sensor comprises a light emitter for emitting light and a photo-detector for detecting said light, wherein said detected light contains information on the plethysmographic data; anda processor for processing the plethysmographic data, wherein said processor is configured to: (a) analyze frequency domain data derived from said plethysmographic data to determine a result,(b) determine a time domain plethysmographic signal using said result of said analysis of the frequency domain data;(c) analyze the time domain plethysmographic signal to identify parameters; and(d) use the identified parameters to discriminate a physiological signal from a distortion.