SIGNAL PROCESSING APPARATUS AND METHOD

• US 20130197328A1
• Filed: 12/05/2012
• Published: 08/01/2013
• Est. Priority Date: 04/14/1997
• Status: Active Grant

• Current Assignee: Masimo Corporation
• Original Assignee: Masimo Corporation
• Inventors: Diab, Mohamed K., McCarthy, Rex J.
• Granted Patent: US 9,289,167 B2
• Time in Patent Office: Days
• US Class Current: 600/324
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/02433 for infrared radiation
• CPC Class Codes: A61B 5/1455 using optical sensors, e.g. spectral photometrical oximeters
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/14552 Details of sensors specially adapted therefor
• CPC Class Codes: A61B 5/6826 Finger
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7214 using signal cancellation, e.g. based on input of two identical physiological sensors spaced apart, or based on two signals derived from the same sensor, for different optical wavelengths
• CPC Class Codes: A61B 5/7225 Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation A61B5/30, A61B5/316 take precedence; transformers for specific applications H01F38/00; amplifiers H03F
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/726 using Wavelet transforms
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: G06F 2218/04 Denoising

Abstract

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.

Claims

1-10. -10. (canceled)

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; and

a 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;

(d) reconstruct a time domain data photo-plethysmographic signal from said frequency domain data;

(e) analyze a mathematical transformation of the time domain photo-plethysmographic signal to identify parameters;

(f) use said parameters to separate a physiological signal from an artifact in the time domain photo-plethysmographic signal; and

(g) compute a physiological parameter from said artifact independent physiological signal.

12. The system of claim 11 wherein the physiological parameter comprises pulse rate.

13. The system of claim 11 wherein the mathematical transformation comprises a frequency domain transform.

14. The system of claim 11 wherein analyzing the mathematical transformation of the time domain photo-plethysmographic signal comprises identifying peaks.

15. The system of claim 14 wherein identifying peaks comprises computing a second order derivative.

16. The system of claim 11 wherein the processor is configured to condition the photo-plethysmographic data prior to transforming the data into the frequency domain.

17. The system of claim 16 wherein conditioning said photo-plethysmographic data reduces spectral leakage from subsequent signal processing and frequency analysis.

18. The system of claim 11 wherein the processor is configured to analyze the frequency domain data to locate candidate spectral peaks before transforming said frequency domain data into time domain photo-plethysmographic signal data, 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.

19. The system of claim 11 wherein the processor is configured to analyze the frequency domain data to locate candidate spectral peaks before transforming said frequency domain data into time domain photo-plethysmographic signal data, wherein said analyzing transformed data to locate candidate spectral peaks is performed using a first derivative criteria, wherein said candidate spectral peak is a frequency bin having a slope value equal to approximately zero.

20. The system of claim 11 wherein the processor is configured to compute a second order derivative of the photo-plethysmographic signal after reconstructing the time domain data photo-plethysmographic signal.

21. The system of claim 20 wherein the second order derivative photo-plethysmographic signal is analyzed to determine the absence or presence of cardiac physiologic signal characteristics.

22. The system of claim 21 wherein analyzing said mathematical transformation of the photo-plethysmographic signal comprises the step of performing a morphological analysis of the mathematical transformation of the photo-plethysmographic signal to determine a unique cardiac morphology, wherein said cardiac morphology consists of a plurality of waves.

23. The system of claim 22 wherein analyzing said mathematical transformation of the photo-plethysmographic signal further comprises the step of performing a morphological analysis of the mathematical transformation of the photo-plethysmographic signal to determine at least one height of said waves.

24. The system of claim 20 wherein analyzing said mathematical transformation of the photo-plethysmographic signal comprises the steps of:

determining a plurality of waves, calculating a plurality of heights of said waves, and applying a criterion for detecting a predefined set of waves.

25. The system of claim 24 wherein the criterion for detecting a predefined set of waves among a first set of waves, a second set of waves, a third set of waves, a fourth set of waves, and a fifth set of waves comprises identifying the difference between a first wave and a second wave and determining whether a set of first, second, third, fourth, and fifth waves adhere to a formula.

26. The system of claim 11 wherein the time domain photo-plethysmographic data is reconstructed by including only a plurality of primary candidate spectral peaks and a plurality of corresponding harmonic spectral peaks.

27. The system of claim 11 wherein using said parameters to separate a physiological signal from an artifact comprises removing artifacts from the photo-plethysmographic signal by classifying a first set of waves with a first score as a likely cardiac geometry and classifying a second set of waves with a score as a likely artifact geometry.

28. 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; and

a processor for processing the photo-plethysmographic data, wherein said processor is configured to;

(a) analyze frequency domain data derived from said photo-plethysmographic data,

(b) transform the frequency domain data into a time domain photo-plethysmographic signal;

(c) analyze a mathematical transformation of the time domain photo-plethysmographic signal to identify parameters; and

(d) use the identified parameters to separate a physiological signal from an artifact in the time domain photo-plethysmographic signal.

29. 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; and

a 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;

(d) determine a time domain data plethysmographic signal using 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) compute a physiological parameter from said physiological signal.

30. The system of claim 29 wherein the physiological parameter comprises pulse rate.

31. The system of claim 29 wherein analyzing the time domain plethysmographic signal comprises determining and analyzing a frequency domain transform.

32. The system of claim 31 wherein analyzing the frequency domain transform of the time domain plethysmographic signal comprises identifying peaks.

33. The system of claim 29 wherein the processor is configured to filter the plethysmographic data prior to transforming the data into the frequency domain.

34. The system of claim 33 wherein filtering said plethysmographic data comprises band pass filtering.

35. The system of claim 29 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, wherein analyzing said transformed 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.

36. The system of claim 29 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.

37. The system of claim 29 wherein the processor is configured to identify peaks after determining the time domain data plethysmographic signal.

38. The system of claim 37 wherein a frequency domain transformation of the time domain plethysmographic signal is analyzed to determine a cardiac physiologic signal characteristic.

39. The system of claim 38 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.

40. The system of claim 39 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.

41. The system of claim 38 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.

42. The system of claim 41 wherein the criterion for detecting a predefined category of a set of spectral lines among a first set of spectral lines, a second set of spectral lines, a third set of spectral lines, a fourth set of spectral lines, and a fifth set of spectral lines comprises identifying the difference between a first spectral line and a second spectral line and determining whether a set of first, second, third, fourth, and fifth spectral lines adhere to a formula.

43. The system of claim 29 wherein the time domain plethysmographic data is determined using only a primary candidate spectral peak and a plurality of corresponding harmonic spectral peaks.

44. The system of claim 29 wherein using said parameters to discriminate a physiological signal from a distortion comprises removing distortions from the plethysmographic signal by classifying a harmonic set with a score.

45. 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; and

a processor for processing the plethysmographic data, wherein said processor is configured to;

(a) analyze frequency domain data derived from said plethysmographic data,

(b) determine a time domain plethysmographic signal using 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 in the time domain plethysmographic signal.