Microprocessor system for the analysis of physiologic and financial datasets

• US 7,758,503 B2
• Filed: 05/17/2002
• Issued: 07/20/2010
• Est. Priority Date: 01/27/1997
• Status: Expired due to Fees

• Current Assignee: Lawrence A. Lynn
• Original Assignee: Eric N Lynn, Lawrence A. Lynn
• Inventors: Lynn, Eric N., Lynn, Lawrence A.
• Primary Examiner(s): Nasser; Robert L
• Application Number:
  US10/150,842
• Publication Number:
  US 20030158466A1
• Time in Patent Office: 2,986 Days
• Field of Search: None
• US Class Current: 600/300
• CPC Class Codes: A61B 5/00 Measuring for diagnostic purposes radiation diagnosis A61B6/00; diagnosis by ultrasonic, sonic or infrasonic waves A61B8/00; Identification of persons
• 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 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/0809 by impedance pneumography
• CPC Class Codes: A61B 5/087 Measuring breath flow
• CPC Class Codes: A61B 5/145 Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissuemeasuring of blood pressure or blood flow A61B5/02; non-radiation detecting or locating of foreign bodies in blood A61B5/06
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/412 Detecting or monitoring sepsis
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

A system and method for organization and analysis of complex and dynamically interactive time series is disclosed. One example comprises a processor based system for relational analysis of physiologic signals for providing early recognition of catastrophic and pathologic events such as pathophysiologic divergence. The processor is programmed to identify pathophysiologic divergence of at least one of first and second physiologic parameters in relationship to the other and to output an indication of the divergence. An object-based method of iterative relational processing waveform fragments in the time domain is described wherein each more complex waveform object inherits the characteristics of the waveform objects from which it is derived. The first physiologic parameter can be the amplitude and frequency of the variation in chest wall impedance or nasal pressure and the second parameter can be a measure or indication of the arterial oxygen saturation.

Claims

1. A microprocessor system for evaluation of a patient, the system comprising:

at least one monitor having at least one sensor for positioning adjacent said patient and at least one processor programmed to;

produce a first timed waveform based on a first physiologic parameter of a patient,

produce a second timed waveform based on a second physiologic parameter which is generally subordinate to said first physiologic parameter, so that said second physiologic parameter normally changes in response to changes in said first physiologic parameter,

identify pathophysiologic divergence of at least one of said first and second physiologic parameters in relationship to the other of said physiologic parameters, the pathophysiologic divergence comprising a change that is both unexpected in the absence of organ dysfunction during clinical monitoring of the patient and pathologic, and

output an indication of said divergence, wherein said second physiologic parameter comprises a measure of arterial oxygenation.

2. The system, as in claim 1, wherein the at least one processor is further programmed to:

a) calculate an index of said pathophysiologic divergence and, b) provide an indication based on said index.

3. The system of claim 1, wherein said first physiologic parameter comprises at least one of an indication and measure of a magnitude of timed ventilation of the patient.

4. The system of claim 3, wherein said first physiologic parameter includes an amplitude and/or frequency of variation in chest wall impedance.

5. The system of claim 3, wherein said first physiologic parameter includes an amplitude and/or frequency of variation in nasal pressure.

6. The system of claim 1, wherein said first physiologic parameter is a measure and/or an indication of carbon dioxide.

7. The system of claim 3, wherein the first physiologic parameter is a measure of timed volume of at least one gaseous component of ventilation.

8. The system of claim 1, comprising an alarm driven by a processor programmed to provide a warning upon detection of at least one occurrence of a degree of pathophysiologic divergence, wherein the pathophysiologic divergence comprises a rise in ventilation in association with a fall in oxygen saturation, and wherein the first physiologic parameter is a measure indicative of ventilation.

9. The system of claim 8 wherein the processor is programmed to determine and output an indication of the degree of the pathophysiologic divergence.

10. The system of claim 8 wherein the first physiologic parameter comprises at least one component indicative of tidal ventilation.

11. The system of claim 8 wherein the first physiologic parameter comprises amplitude and/or frequency of tidal ventilation.

12. The system of claim 8 wherein the processor is programmed to calculate a mathematical index derived from both ventilation rate and ventilation tidal amplitude and wherein the pathophysiologic divergence comprises a rise in the mathematical index in association with the fall in oxygen saturation.

13. The system of claim 1 wherein the at least one processor is programmed to detect a pattern indicative of the pathophysiologic divergence.

14. The system of claim 1 wherein the at least one processor is programmed to output a graphical indication of at least one of the first and second physiologic parameters and to identify, along the graphical indication, at least one of the timed relationships, and a degree and points of pathophysiologic divergence.

15. The system of claim 1 wherein the first physiologic parameter is a parameter type which can provide an indication of hyperventilation, and the at least one processor is programmed to provide an alarm when oxygen saturation reaches an alarm threshold, the processor being further programmed to provide an earlier alarm based on the oxygen saturation when hyperventilation is present even though the oxygen saturation has not reached the alarm threshold, such that the at least one processor can provide earlier warning of occurrences in clinical situations wherein hyperventilation is delaying development of an oxygen saturation threshold breach.

16. The system of claim 15 comprising a hospital monitor for early detection of septic shock.

17. A method of monitoring a patient comprising:

monitoring a patient with at least one sensor to produce a first timed waveform of a first physiologic parameter and a second timed waveform of a second physiologic parameter by transforming sensed physiological input into visual data, the second physiologic parameter being physiologically subordinate to said first physiologic parameter, and

using a processor, the processor identifying a pattern indicative of pathophysiologic divergence of at least one of said waveforms in relation to the other of said waveforms, the pathophysiologic divergence comprising a change that is both unexpected in the absence of organ dysfunction during clinical monitoring of a patient and pathologic, and outputting an indication of said divergence, wherein said second physiologic parameter comprises a measure of arterial oxygenation.

18. The method of claim 17, wherein said first timed waveform is defined by a time interval of greater than about 5-20 minutes.

19. The method of claim 17 wherein said first and second timed waveforms are derived from airflow and pulse oximetry measurements.

20. The method of claim 17, comprising controlling a diagnostic and/or treatment device with a secondary processor programmed to respond to the output of said processor.

21. The method of claim 20, comprising adjusting a program of said secondary processor with said processor.

22. The method of claim 20, comprising recognizing hypopneas with said secondary processor and providing airflow with said treatment device, said processor adjusting a program of said secondary processor based on said pattern.

23. The method of claim 20 wherein said treatment device is an automatic defibrillator.

24. The method of claim 20, comprising mounting said secondary processor with said treatment and/or diagnostic device, and wherein said processor is detachable from a connection with said secondary processor.

25. The method of claim 20, comprising monitoring and analyzing a plurality of different patient related signals including electrocardiographic signals with said processor.

26. The method of claim 20, wherein said-processor is a polysomnography monitor, and comprising monitoring a plurality of different signals including encephalographic signals with said processor.

27. The method of claim 17, wherein said first physiologic parameter is a measure and/or an indication of carbon dioxide.