Detection and characterization of cholinergic oscillatory control in peripheral microvasculature

• US 7,367,941 B2
• Filed: 05/14/2003
• Issued: 05/06/2008
• Est. Priority Date: 11/14/2000
• Status: Expired due to Term

• Current Assignee: David G. Silverman, Robert G. Stout
• Original Assignee: Yale University
• Inventors: Silverman, David G., Stout, Robert G.
• Primary Examiner(s): Nasser, Jr.; Robert L.
• Assistant Examiner(s): Mallari; Patricia
• Application Number:
  US10/437,452
• Publication Number:
  US 20030233048A1
• Time in Patent Office: 1,819 Days
• Field of Search: None
• US Class Current: 600/300
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/0059 using light, e.g. diagnosis by transillumination, diascopy, fluorescence A61B5/0093, A61B5/1455, A61B5/02416 and A61B5/0261 take precedence
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/0261 using optical means, e.g. infrared light
• CPC Class Codes: A61B 5/4035 Evaluating the autonomic nervous system

Abstract

The present invention is an apparatus and method for assessing the condition of a subject by measuring and characterizing one or more oscillatory activities of the subject. The oscillatory activities are under the control of the autonomic nervous system and characterizing the activities provides information related to the status of the autonomic nervous system.

Claims

1. A method of selectively identifying frequency and power of cholinergic oscillatory activity in microvasculature of a human comprising:

a). measuring the frequency and power of the oscillatory activity in the microvasculature of the human at a frequency of from about 0.12 Hz to about 0.18 Hz; and

b). distinguishing the measured activity obtained in step a) from the sympathetic oscillatory activity and the proximally generated parasympathetic oscillatory activity, thereby selectively identifying the frequency and power of the cholinergic oscillatory activity.

2. The method of claim 1, wherein distinguishing the cholinergic oscillatory activity from the proximally generated parasympathetic activity comprises controlling effects of respiration by setting the human'"'"'s respiratory rate to 0.20 Hz or greater.

3. The method of claim 2, wherein the effects of respiration are controlled by having the human breathe voluntarily at a rate of 0.20 Hz or greater.

4. The method of claim 1, wherein the measured activity is distinguished from frequencies less than about 0.12 Hz, and from frequencies greater than about 0.18 Hz, by utilizing a method selected from the group consisting of frequency subtraction, signal filtering, analyzing absolute frequency contributions, analyzing relative frequency contributions, and determining proportional activities of the frequencies.

5. The method of claim 1, wherein the measuring comprises monitoring a plurality of vessels of the microvasculature.

6. The method of claim 1, wherein the measuring comprises monitoring a plurality of blood vessels in the distal microvasculature.

7. A method of assessing cholinergic oscillatory activity of a subject comprising:

a). measuring the frequency and power of the oscillatory activity of a cardiovascular signal in the microvasculature of the subject at a frequency from about 0.12 Hz to about 0.18 Hz; and

b). distinguishing the measured activity obtained in step a) from the sympathetic oscillatory activity and the proximally generated parasympathetic oscillatory activity, thereby selectively identifying the frequency and power of the cholinergic oscillatory activity in the microvasculature, and

c). assessing the condition of the subject, wherein the cholinergic oscillatory activity is indicative of an autonomic dysfunction, an autonomic neuropathy, a prehypertensive state, a hypertensive state, a decrease in parasympathetic activity, and diabetes.

8. The method of claim 7, wherein the cardiovascular signal is detected in a vessel or a plurality of vessels.

9. The method of claim 7, wherein the measurement is accomplished using a laser Doppler flowmeter.

10. The method of claim 7, wherein the data are further analyzed by determining the power of the frequencies in individual bins and/or individual bands.

11. The method of claim 7, further comprising normalizing the oscillatory activity data by:

measuring the oscillatory activity at different times, measuring the oscillatory activity at different sites in the peripheral vasculature, or measuring the oscillatory activity with different devices.

12. The method of claim 11, wherein the data are normalized to a mean value obtained for a given period of measurement.

13. The method of claim 11, wherein the data are normalized to a median value obtained for a given period of measurement.

14. The method of claim 11, further comprising performing spectral-domain analysis of the normalized data.

15. The method of claim 7, wherein the oscillatory activity data are converted to discrete variable time interval data so as to facilitate comparisons to R-R intervals and EKG measurements.

16. The method of claim 7, further comprising performing time-domain analysis of the data.

17. The method of claim 16, further comprising determining indices such as maximum, minimum, and max-min of individual signals on a beat-to-beat basis.

18. The method of claim 17, further comprising determining the beat-to-beat percent change.

19. The method of claim 18, further comprising determining the percentage of beat-to-beat changes beyond an established cutoff.

20. The method of claim 19, wherein the established cutoff is 5% (PBB5%) or 10% (PBB 10%).

21. The method of claim 16, further comprising mathematically manipulating the data to determine indices for comparison.

22. The method of claim 21, further comprising determining the normalization of time-domain indices of variability of waveforms by dividing an index by the mean value of the signal during a specific study interval.

23. The method of claim 22, further comprising determining the normalization of time-domain indices of variability of waveforms by dividing an index by the median value of the signal during a specific study interval.

24. The method of claim 7, wherein the method utilizes graphic time-domain displays.

25. The method of claim 7, wherein the measuring step is accomplished from an event selected from the group consisting of baseline, during drug therapy, during physiological challenges, during psychological challenges, and various stages of a disease.

26. The method of claim 7, wherein the data are analyzed using joint time-frequency analysis.

27. The method of claim 26, wherein the data are measured using a laser Doppler flowmeter.

28. The method of claim 7, wherein the subject is exposed to a pharmacologic challenge.