Balascopy system and method with improved sensitivity

• US 6,768,948 B2
• Filed: 10/29/2002
• Issued: 07/27/2004
• Est. Priority Date: 10/29/2002
• Status: Expired due to Fees

• Current Assignee: Vadim Kvitash
• Original Assignee: Vadim Kvitash
• Inventors: Kvitash, Vadim
• Primary Examiner(s): Hoff, Marc S.
• Assistant Examiner(s): Charioui, Mohamed
• Application Number:
  US10/282,512
• Publication Number:
  US 20040083059A1
• Time in Patent Office: 637 Days
• Field of Search: 702/19-22, 702/67, 702/179-181, 702/187, 702/189, 128/920-925, 600/300, 600/301, 600/509, 345/440, 345/805, 426/634
• US Class Current: 702/19
• 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 5/412 Detecting or monitoring sepsis
• CPC Class Codes: A61B 5/417 the bone marrow
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence

Abstract

The method and system improve the balascopic concept disclosed in U.S. Pat. No. 4,527,240 by introducing relative balascopic units more convenient for graphical representation of parameters in a multiple-parametric system. The “analysis-of-pair” method is improved by replacing the graphical linear representation with balascopic vectors, which show a direction of changes of the relationship from normal and the length of which corresponds to the amount of the change. The circular diagram method is improved by dimensisonlessly rescaling the balascopic units into a system in which deviations for all parameters are shown from mean statistic values recalculated on the same radius of the circular diagram. According to another embodiment for balascopic representation of diagnostic data, the circular diagram of the invention are developed into a linear form.

Claims

1. A method of evaluating data for a plurality of parameters in a multi-parametric system, comprising the steps of:

(a) obtaining a plurality of parametric data for said parameters of said multi-parametric system;

(b) converting each of said parametric data into balascopic units;

(c) providing a known reference data for each of said parametric data in said balascopic units;

(c) converting said balascopic units of each of said parametric data into relative balascopic units relative to said known reference data which is taken as 100%;

(d) further converting said relative balascopic units into a graphical form selected from a group consisting of a linear vector/scolar form, a matrix form, a circular diagram form, a linear diagram form obtained by developing said circular diagram form, and a multiple link form which shows connections between at least a part of said parameters having specific relationships; and

(e) evaluating said multi-parametric system by comparing said graphic forms with a known reference graphic form plotted on the basis of said known reference data of said multi-parametric system.

2. The method of claim 1, wherein said known reference data comprises a mean normal statistic value of said parametric data and wherein for each of said parametric data said relative balascopic units are obtained by multiplying each said parametric data by 100 and dividing the obtained product by the number of balascopic units contained in said mean normal statistic value of said parametric data.

3. The method of claim 2, wherein said step of converting into said linear vector/scolar form comprises:

a. finding specific relationships between pairs of said parameters;

b. classifying said specific relationships into relationships types;

c. providing a common axis for plotting said relative balascopic units on said common axis; and

plotting said parametric data for each of said relationship types plotted in said relative balascopic units on axes parallel to said common axes and in alignment therewith.

4. The method of claim 3, wherein said specific relationships comprises a group that contains at least normal relationships (N), closer-than-normal relationships (CN), further-than-normal relationships (FN), normal-inverted relationships (NI), closer-inverted relationships (CI), and further-inverted relationships (FI).

5. The method of claim 4, wherein said normal relationships (N) and said normal-inverted relationships (NI) are described by scolar linear sections and wherein said closer-than-normal relationships (CN), further-than-normal rlationships (FN), closer-inverted relationships (CI), and further-inverted relationships (FI) are described by vectorial linear sections, said scolar linear sections and said vectorial linear sections being arranged parallel to said common axis.

6. The method of claim 5, further comprising a step of determining direction of change in said closer-than-normal relationships (CN), further-than-normal relationships (FN), closer-inverted relationships (CI), and further-inverted relationships (FI) from said normal relationships.

7. The method of claim 2, wherein said steps of converting into said linear diagram form comprises:

(a) providing linear axes, one for each of said parameters, calibrated in said relative balascopic units;

(b) arranging said linear axes of said parameters parallel to each other;

(c) calibrating said linear axes in said relative balascopic units;

(d) determining minimal normal statistic values and maximal normal statistic values for each of said parameters;

(e) determining normal mean statistic value of said parameters;

(f) converting said minimal normal statistic values, maximal normal statistic data, and said normal mean statistic values into said relative balascopic units;

(g) plotting said relative balascopic units of said minimal normal statistic values, maximal normal statistic data, and said normal mean statistic values on said radial axes;

(f) creating a minimal normal linear pattern, a maximal normal linear pattern, and mean normal linear pattern by interconnecting points of maximal, minimal, and normal mean values on adjacent ones of said parametric axes;

(g) plotting said relative balascopic units of said parametric data on said linear axes for obtaining a parametric linear pattern; and

(g) evaluating said multi-parametric system by comparing the position of said parametric linear pattern with respect to positions of said a minimal normal linear pattern and maximal normal linear pattern.

8. The method of claim 7, further comprising the steps of:

providing at least one more linear diagram form after a predetermined period of time by repeating said steps from (a) to (g) of claim 7, and plotting said at least one more linear diagram on the same linear axes as in claim 7, arranging said at least one more linear diagram under said linear diagram of claim 7, and aligning respective linear axes of said linear diagram of claim 7 with respective axes of said at least one more linear diagram; and

analyzing the dynamics of change that occurred in said multiparametric system during said certain period of time by observing variations that occurred in said relative balascopic units on aligned axes of said linear diagram of claim 7 and of said at least one more linear diagram.

9. The method of claim 8, wherein said specific relationships comprise a group that contains at least normal relationships (N), closer-than-normal relationships (CN), further-than-normal relationships (FN), normal-inverted relationships (NI), closer-inverted relationships (CI), and further-inverted relationships (FI).

10. The method of claim 9, further comprising the steps of:

establishing second-order relationships between at least two different cells of said matrix; and

analyzing said multiparametric system on the basis of said second-order relationships.

11. The method of claim 2, wherein said step of converting into said matrix form comprises:

forming an orthogonal matrix with the same parameters arranged on equally numbered horizontal rows and vertical columns so that diagonal cells are located on intersections of said equally-numbered rows and columns;

determining specific relationships between pairs of said parameters and arranging said specific relationships in the matrix cells formed by intersections of parameters of said pairs; and

placing in said diagonal cells parametric data of said parameters at least in terms of said relative balascopic units.

12. The method of claim 11, wherein said specific relationships comprise a group that contains at least normal relationships (N), closer-than-normal relationships (CN), further-than-normal relationships (FN), normal-inverted relationships (NI), closer-inverted relationships (CI), and further-inverted relationships (FI).

13. The method of claim 12, further comprising the steps of:

establishing second-order relationships between at least two different cells of said matrix; and

analyzing said multiparametric system on the basis of said second-order relationships.

14. The method of claim 11, additionally placing in said diagonal cells natural values of said parametric data of said parameters.

15. The method of claim 2, wherein said conversion into said multiple link form which shows connections between at least a part of said parameters having specific relationships comprises the steps of:

designating said parameters of said multi-parametric system with specific designations;

establishing a circular coordinate system with a center of origin and a plurality of radii extending from said center of origin with the number of radii equal to the number of said parameters;

designating said radii with said specific designations which correspond to said parameters;

selecting one of said parameters and placing said specific designations of one of said parameters into said center of origin;

plotting values of changes in said specific relationships between said one of said parameters and other of said parameters on said respective radii in said relative balascopic units starting from said point of origin;

designating a direction of said changes by vectors; and

showing the amount of said changes by the lengths of said vectors.

16. The method of claim 15, further comprising the step of indicating the absolute values of said changes in relationships by attaching a number to each said vector.

17. The method of claim 16, further comprising a step of plotting said said values of changes on said radii on a logarithmic scale.

18. The method of claim 15, further comprising a step of plotting said values of changes on said radii on a logarithmic scale.

19. The method of claim 2, wherein said conversion into said multiple link form which shows connections between at least a part of said parameters having metabolic relationships comprises the steps of:

designating all parameters of said multi-parametric system by dots with specific designation of each of said parameters;

connecting the dots of at least a part of said parameters which have specific relationships by multiple links;

determining links between parameters having normal relationships and abnormal relationships;

designating said links of said abnormal relationships by vectors with directions of said vectors showing the direction of change of said relationships relative to said normal relationship; and

showing the amount of said changes by the lengths of said vectors.

20. The method of claim 19, further comprising the step of indicating absolute values of said changes in relationships by attaching a number to each said vector.

21. The method of claim 2, wherein said steps of converting into said circular diagram form comprises:

(a) providing a circular coordinate system having radial axes corresponding to said parameters of said multi-parametric system, each axis being calibrated in said relative balascopic units;

(b) determining minimal normal statistic values and maximal normal statistic values of said parameters;

(c) determining normal mean statistic values of said parameters;

(d) converting said minimal normal statistic values, maximal normal statistic data, and said normal mean statistic values into said relative balascopic units;

(e) plotting said relative balascopic units of said minimal normal statistic values, maximal normal statistic data, and normal mean statistic values on said radial axes;

(f) creating a minimal dosed-loop pattern, a maximal closed-loop pattern, and normal mean closed-loop area by interconnecting points of maximal, minimal, and normal mean values on adjacent ones of said radial axes;

(g) plotting said relative balascopic units of said parametric data on said axes; and

(g) evaluating said multi-parametric system by comparing said closed configuration patterns with the area between said minimal closed-loop pattern and said maximal closed-loop pattern.

22. The method of claim 1, wherein the number of said parameters is n, the number of the types of said specific relationships is m, and the maximum possible number of links between pairs of said parameters is a number of combination of n by 2.

23. The method of claim 22, wherein said known reference data comprises a mean normal statistic value of said parametric data and wherein for each of said parametric data said relative balascopic units are obtained by multiplying each said parametric data by 100 and dividing the obtained product by the number of balascopic units contained in said mean normal statistic value of said parametric data.

24. The method of claim 23, wherein said step of converting into said linear vector/scolar form comprises:

a. finding specific relationships between pairs of said parameters;

b. classifying said specific relationships into said types of said specific relationships;

c. providing a common axis for plotting said relative balascopic units on said common axis; and

plotting said parametric data for each of said types of specific relationships plotted in said relative balascopic units on axes parallel to said common axes and in alignment therewith.

25. The method of claim 22, wherein said step of convening into said matrix form comprises:

forming an orthogonal matrix with said n parameters arranged on equally numbered horizontal rows and vertical columns so that diagonal cells are located on intersections of said equally-numbered rows and columns;

determining said types of specific relationships between pairs of said n parameters and arranging said types of specific relationships in the matrix cells formed by intersections of parameters of said pairs; and

placing in said diagonal cells parametric data of said parameters at least in terms of said relative balascopic units.

26. A system for evaluating data for a plurality of parameters in a multi-parametric system, comprising:

(a) a plurality of parametric data for said parameters of said multi-parametric system, said parametric data being converted into relative balascopic units, wherein said relative balascopic units being obtained by multiplying each said parametric data by 100 and dividing the obtained product by the number of conventional balascopic units contained in a mean normal statistic value of said parametric data;

(b) a graphic representation of said parametric data in said relative balascopic units selected from a group consisting of a linear vector/scolar representation, a matrix representation, a circular diagram representation, a linear diagram representation obtained by developing said circular diagram representation, and a multiple link representation, which shows connections between at least a part of said parameters having specific relationships; and

(c) a graphic representation of a known reference data of said parameters in the same representation forms as those selected for said parametric data in item (b) for comparison with said parametric data of said multi-parametric system.

27. The system of claim 26, wherein said known reference data comprises a mean normal statistic value of said parametric data.

28. The system of claim 27, wherein said linear vector/scolar representation comprises:

at least two pairs of said parameters having specific relationships which are classified by relationship types with specific designation of said relationship types;

a common axis for plotting said relative balascopic units on said common axis; and

parametric data for each of said relationship types plotted in said relative balascopic units on axes parallel to said common axes and in alignment therewith.

29. The system of claim 28, wherein said specific relationships comprises a group that contains at least normal relationships (N), closer-than-normal relationships (CN), further-than-normal relationships (FN), normal-inverted relationships (NI), closer-inverted relationships (CI), and further-inverted relationships (FI).

30. The system of claim 29, wherein said normal relationships (N) and said normal-inverted relationships (NI) are described by scolar linear sections and wherein said closer-than-normal relationships (CN), further-than-normal relationships (FN), closer-inverted relationships (CI), and further-inverted relationships (FI) are described by vectorial linear sections, said scolar linear sections and said vectorial linear sections being arranged parallel to said common axis.

31. The system of claim 30, wherein said linear diagram representation comprises:

(a) a plurality of linear axes, one for each of said parameters, calibrated in said relative balascopic units and arranged in alignment with and parallel to each other;

(b) minimal normal statistic value, maximal normal statistic values for each of said parameters; and

normal mean statistic value of said parameters plotted in said relative balascopic units on said linear axes;

(c) a minimal normal linear pattern, a maximal normal linear pattern, and a mean normal linear pattern formed by interconnecting points of said maximal, minimal, and normal mean values on adjacent ones of said parametric axes;

(d) relative balascopic units of said parametric data plotted on said linear axes for obtaining a parametric linear pattern; and

(e) a linear pattern of said parametric data obtained by connecting points of said parametric data on adjacent ones of said linear axes.

32. The system of claim 31, comprising at least one more linear representation of claim 29 plotted on the bases of sad said parametric data obtained after expiration of a predetermined period of time and arranged in a position where said linear axes of said one more linear representation are aligned with the positions of respective axes of said linear representation of claim 29 for possibility of observation of dynamical changes in said parametric data.

33. The system of claim 30, wherein directions of change in said closer-man-normal relationships (CN), further-than-normal relationships (FN), closer-inverted relationships (CI), and further-inverted relationships (FI) from said normal relationships correspond to directions of said vectorial linear sections.

34. The system of claim 26, wherein said matrix representation comprises:

an orthogonal matrix with the same parameters arranged on equally numbered horizontal rows and vertical columns so that diagonal cells are located on intersections of said equally-numbered rows and columns;

specific relationships between pairs of said parameters indicated in the matrix cells formed by intersections of parameters of said pairs; and

at least said parametric data being indicated in said diagonal cells of said matrix at least in terms of said relative balascopic units.

35. The system of claim 34, additionally indicating in said diagonal cells natural values of said parametric data of said parameters.

36. The system of claim 35, wherein said specific relationships comprises a group that contains at least normal relationships (N), closer-than-normal relationships (CN), further-than-normal relationships (FN), normal-inverted relationships (NI), closer-inverted relationships (CI), and further-inverted relationships (FI).

37. The system of claim 34, wherein said specific relationships comprises a group that contains at least normal relationships (N), closer-than-normal relationships (CN), further-than-normal relationships (FN), normal-inverted relationships (NI), closer-inverted relationships (CI), and further-inverted relationships (FI).

38. The system of claim 26, wherein said multiple-link representation comprises:

a circular coordinate system with a center of origin and a plurality of radii extending from said center of origin with the number of said radii equal to the number of said parameters, wherein each of said radii corresponds to a one of said parameters and wherein the number of said radii is equal the number of said parameters minus 1;

one of said parameters being designated by a dot coinciding with said center of origin, while the remaining of said parameters being designated by dots plotted on said radii corresponding to said respective parameters in said relative balascopic units, distances from said center of origin to said dots on said radii being shown by vectors wherein directions of said vectors indicate directions of said change and wherein the lengths of said vectors indicate the amount of said change.

39. The system of claim 38, further comprising numbers indicating absolute values of said change.

40. The system of claim 39, further comprising logarithmic scales on said radii for plotting said dots in relative balascopic units on said logarithmic scales.

41. The system of claim 26, wherein said multiple-link representation between at least a part of said parameters having specific relationships comprises:

designation of said parameters of said multi-parametric system by dots with specific designation of each of said parameters;

connection lines connecting the dots of at least a part of said parameters which have specific relationships;

designation of connection lines between parameters having normal relationships and abnormal relationships;

designation of said connection lines between parameters having said abnormal relationships by vectors with directions of said vectors showing the direction of change of said specific relationships, the lengths of said vectors corresponding to the amount of said change.

42. The system of claim 41, further comprising numbers attached to said vectors and indicating the absolute values of said change in said specific relationships.

43. The system of claim 26, wherein the number of said parameters is n, the number of the types of said specific relationships is m, and the maximum possible number of links between pairs of said parameters is a number of combination of n by 2.

44. The system of claim 43, wherein said known reference data comprises a mean normal statistic value of said parametric data and wherein for each of said parametric data said relative balascopic units are obtained by multiplying each said parametric data by 100 and dividing the obtained product by the number of balascopic units contained in said mean normal statistic value of said parametric data.

45. The system of claim 26, wherein said circular presentation comprises:

(a) a circular coordinate system having radial axes corresponding to said parameters of said multi-parametric system, each axis being calibrated in said relative balascopic units;

(b) minimal normal statistic values, maximal normal statistic values, and normal mean statistic value of said parameters plotted on said radial axes in said relative balascopic units;

(c) a minimal closed-loop pattern, a maximal closed-loop pattern, and normal mean closed-loop pattern formed by interconnecting points of maximal, minimal, and normal mean values on adjacent ones of said radial axes;

(d) relative balascopic units of said parametric data plotted on said radial axes; and

(e) a closed-loop configuration pattern of said parametric data formed by interconnecting points of said parametric data on adjacent ones of said radial axes.