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The invention analyzes relationships between factors, within a patient population, to identify autonomic dysfunction patterns. Patient test results are then compared with the identified patterns to determine the patient's autonomic function. The invention can continually amend the patient population

The invention analyzes relationships between factors, within a patient population, to identify autonomic dysfunction patterns. Patient test results are then compared with the identified patterns to determine the patient's autonomic function. The invention can continually amend the patient population with new test results to create increasingly accurate normative data sets from which a patient's autonomic function can be more accurately assessed. The invention may apply this concept in an application service provider model. An embodiment of the invention may use a novel method of identifying certain components on physiological signals such as the R-wave for an ECG. The method locates R-waves by searching for maximum slope values and cycle lengths that satisfy certain threshold values. Another embodiment of the invention entails a non-provocative HRV test whereby certain time domain and frequency domain factors are analyzed to determine a patient's autonomic function.

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What is claimed is: 1. A method for analyzing a physiological signal comprising the steps of: obtaining a physiological signal that comprises a set of waveforms followed by an additional waveform; wherein the set of waveforms comprises: a first waveform; a last waveform; and one or more intermediat

What is claimed is: 1. A method for analyzing a physiological signal comprising the steps of: obtaining a physiological signal that comprises a set of waveforms followed by an additional waveform; wherein the set of waveforms comprises: a first waveform; a last waveform; and one or more intermediate waveforms located between the first waveform and the last waveform; obtaining a maximum slope for the first waveform, the last waveform and the one or more intermediate waveforms; obtaining a maximum slope for the additional waveform by performing the steps of: confirming the maximum slope for the additional waveform is greater than a minimum threshold; and confirming the maximum slope for the additional waveform is less than a maximum threshold; wherein the minimum threshold and the maximum threshold are derived from the maximum slopes for the first waveform, the last waveform and the one or more intermediate waveforms. 2. The method of claim 1 comprising the additional step of obtaining a second set of waveforms that is located between the set of waveforms and the additional waveform; wherein the second set of waveforms comprises one or more waveforms. 3. The method of claim 1 wherein the one or more intermediate waveforms comprise a predetermined number of waveforms. 4. The method of claim 3 wherein the predetermined number of waveforms is determined pursuant to empirical observation. 5. The method of claim 1 further comprising the step of calculating a mean value of the maximum slopes for the first waveform, the last waveform and the one or more intermediate waveforms. 6. The method of claim 5 wherein the minimum threshold is derived by multiplying the mean value by a predetermined value. 7. The method of claim 6 wherein the predetermined value is about 0.06. 8. The method of claim 5 wherein the maximum threshold is derived by multiplying the mean value by a predetermined value. 9. The method of claim 8 wherein the predetermined value is about 1.6. 10. The method of claim 1 further comprising the step of calculating a median value of the maximum slopes for the first waveform, the last waveform and the one or more intermediate waveforms. 11. The method of claim 10 wherein the minimum threshold is derived by multiplying the median value by a predetermined value. 12. The method of claim 11 wherein the predetermined value is about 0.06. 13. The method of claim 10 wherein the maximum threshold is derived by multiplying the median value by a predetermined value. 14. The method of claim 13 wherein the predetermined value is about 1.6. 15. The method of claim 1 further comprising the step of obtaining a cycle length between the maximum slope for the last waveform and the maximum slope for the additional waveform. 16. The method of claim 15 further comprising the step of determining whether the cycle length is less than a maximum cycle length. 17. The method of claim 16 wherein the maximum cycle length is about 2000 ms. 18. The method of claim 16 further comprising the step of obtaining a longest cycle length within the set of waveforms; wherein the maximum cycle length is derived from the longest cycle length within the set of waveforms. 19. The method of claim 16 wherein the physiological signal is filtered with a moving average filter and a band pass filter before maximum slopes are obtained for the first waveform, the last waveform and the one or more intermediate waveforms. 20. The method of claim 15 further comprising the step of determining whether the cycle length is greater than a minimum cycle length. 21. The method of claim 20 wherein the minimum cycle length is about 330 ms. 22. The method of claim 20 further comprising the step of obtaining a shortest cycle length within the set of waveforms; wherein the minimum cycle length is derived from the shortest cycle length within the set of waveforms. 23. The method of claim 1 wherein the physiological signal is filtered with a moving average filter and a band pass filter before maximum slopes are obtained for the first waveform, the last waveform and the one or more intermediate waveforms. 24. The method of claim 1 wherein the physiological signal is comprised of data selected from the group consisting of: ECG data, EMG data and EEG data. 25. One or more program storage media readable by a machine and containing instructions for performing the method contained in claim 1. 26. A system for analyzing a physiologic signal comprising: one or more memory units operable for storing one or more computer products for assessing autonomic performance; and one or more processors coupled to the one or more memory units, wherein the one or more processors execute the one or more computer products for performing the steps of: obtaining a physiological signal that comprises a set of waveforms followed by an additional waveform; wherein the set of waveforms comprises: a first waveform; a last waveform; and one or more intermediate waveforms located between the first waveform and the last waveform; obtaining a maximum slope for the first waveform, the last waveform and the one or more intermediate waveforms; obtaining a maximum slope for the additional waveform by performing the steps of: confirming the maximum slope for the additional waveform is greater than a minimum threshold; and confirming the maximum slope for the additional waveform is less than a maximum threshold; wherein the minimum threshold and the maximum threshold are derived from the maximum slopes for the first waveform, the last waveform and the one or more intermediate waveforms. 27. The system of claim 26 wherein the one or more processors execute the one or more computer products for performing the additional step of obtaining a second set of waveforms that is located between the set of waveforms and the additional waveform; wherein the second set of waveforms comprises one or more waveforms. 28. The system of claim 26 wherein the one or more intermediate waveforms comprise a predetermined number of waveforms. 29. The system of claim 28 wherein the predetermined number of waveforms is determined pursuant to empirical observation. 30. The system of claim 29 wherein the one or more processors execute the one or more computer products for performing the additional step of calculating a mean value of the maximum slopes for the first waveform, the last waveform and the one or more intermediate waveforms. 31. The system of claim 30 wherein the minimum threshold is derived by multiplying the mean value by a predetermined value. 32. The system of claim 31 wherein the predetermined value is about 0.06. 33. The system of claim 30 wherein the maximum threshold is derived by multiplying the mean value by a predetermined value. 34. The system of claim 33 wherein the predetermined value is about 1.6. 35. The system of claim 26 wherein the one or more processors execute the one or more computer products for performing the additional step of calculating a median value of the maximum slopes for the first waveform, the last waveform and the one or more intermediate waveforms. 36. The system of claim 35 wherein the minimum threshold is derived by multiplying the median value by a predetermined value. 37. The system of claim 36 wherein the predetermined value is about 0.06. 38. The system of claim 35 wherein the maximum threshold is derived by multiplying the median value by a predetermined value. 39. The system of claim 38 wherein the predetermined value is about 1.6. 40. The system of claim 26 wherein the one or more processors execute the one or more computer products for performing the additional step of obtaining a cycle length between the maximum slope for the last waveform and the maximum slope for the additional waveform. 41. The system of claim 40 wherein the one or more processors execute the one or more computer products for performing the additional step of determining whether the cycle length is less than a maximum cycle length. 42. The system of claim 41 wherein the maximum cycle length is about 2000 ms. 43. The system of claim 41 wherein the one or more processors execute the one or more computer products for performing the additional step of obtaining a longest cycle length within the set of waveforms; wherein the maximum cycle length is derived from the longest cycle length within the set of waveforms. 44. The system of claim 41 further comprising a moving average filter and a band pass filter for filtering the physiological signal. 45. The system of claim 41 wherein the one or more processors execute the one or more computer products for performing the additional step of filtering the physiological signal with a moving average filter and a band pass filter before maximum slopes for the first waveform, the last waveform and the one or more intermediate waveforms are obtained. 46. The system of claim 40 wherein the one or more processors execute the one or more computer products for performing the additional step of determining whether the cycle length is greater than a minimum cycle length. 47. The system of claim 46 wherein the minimum cycle length is about 330 ms. 48. The system of claim 46 wherein the one or more processors execute the one or more computer products for performing the additional step of obtaining a shortest cycle length within the set of waveforms; wherein the minimum cycle length is derived from the shortest cycle length within the set of waveforms. 49. The system of claim 26 further comprising a moving average filter and a band pass filter for filtering the physiological signal. 50. The system of claim 26 wherein the physiological signal is comprised of data selected from the group consisting of: ECG data, EMG data and EEG data. 51. A method for analyzing a physiological signal comprising the steps of: obtaining a physiological signal that comprises a set of waveforms followed by an additional waveform; wherein the set of waveforms comprises: a first waveform; a last waveform; and one or more intermediate waveforms located between the first waveform and the last waveform; obtaining a fiduciary point for the first waveform, the last waveform, the one or more intermediate waveforms and the additional waveform; obtaining a cycle length between the fiduciary point for the last waveform and the fiduciary point for the additional waveform; obtaining a longest cycle length within the set of waveforms; obtaining a shortest cycle length within the set of waveforms; obtaining a verified fiduciary point for the additional waveform by performing the steps of: confirming the cycle length is less than a maximum cycle length; and confirming the cycle length is greater than a minimum cycle length; wherein the maximum cycle length is derived from the longest cycle length within the set of waveforms and the minimum cycle length is derived from the shortest cycle length within the set of waveforms. 52. The method of claim 51 comprising the additional step of obtaining a second set of waveforms that is located between the set of waveforms and the additional waveform; wherein the second set of waveforms comprises one or more waveforms. 53. The method of claim 51 wherein the one or more intermediate waveforms comprise a predetermined number of waveforms. 54. The method of claim 53 wherein the predetermined number of waveforms is determined pursuant to empirical observation. 55. The method of claim 51 wherein the fiduciary points for the first waveform, the last waveform, the one or more intermediate waveforms and the additional waveform are derived from a maximum slope for the first waveform, the last waveform, the one or more intermediate waveforms and the additional waveform. 56. The method of claim 51 wherein the fiduciary points for the first waveform, the last waveform, the one or more intermediate waveforms and the additional waveform are derived from a peak amplitude for the first waveform, the last waveform, the one or more intermediate waveforms and the additional waveform. 57. The method of claim 51 wherein the maximum cycle length is about 2000 ms. 58. The method of claim 51 wherein the minimum cycle length is about 330 ms. 59. The method of claim 51 wherein the physiological signal is filtered with a moving average filter and a band pass filter before fiduciary points are obtained for the first waveform, the last waveform and the one or more intermediate waveforms. 60. One or more program storage media readable by a machine and containing instructions for performing the method contained in claim 51.