Method and apparatus for producing a waveform

Abstract

There is provided herein a method for producing a representative CO.sub.2 waveform, the method comprising obtaining two or more CO.sub.2 waveforms, for each of the two or more CO.sub.2 waveforms determining one or more scale factors and one or more shape factors, computing, based on the one or more shape and scale factors of each of the two or more CO.sub.2 waveforms, a representative set of shape factors and scale factors representing the two or more CO.sub.2 waveforms and constructing a representative waveform based on the representative set of shape and scale factors.

Claims

1. A method for producing a single representative CO.sub.2 waveform representing a set of CO.sub.2 waveforms obtained from a subject, the method comprising: obtaining a set of two or more CO.sub.2 waveforms from the subject; identifying a unique pattern in the two or more waveforms, wherein the unique pattern is a recurring pattern that recurs over a predetermined number of consecutive waveforms of the two or more CO.sub.2 waveforms, and wherein the recurring pattern is representative of a physiological condition; removing the unique pattern from the two or more CO.sub.2 waveforms; determining one or more scale factors and one or more shape factors for each of the two or more CO2 waveforms from which the unique pattern has been removed; computing a representative set of shape factors based on the one or more shape factors; computing a representative set of scale factors based on the one or more scale factors; wherein each of the representative set of shape factors and the representative set of scale factors represent the two or more CO.sub.2 waveforms from which the unique pattern has been removed; constructing a single representative CO.sub.2 waveform based on an integration of the representative sets of shape and scale factors; such that the single representative CO.sub.2 waveform is representative of both the shape and scale of the two or more CO.sub.2 waveforms from which the unique pattern has been removed; superimposing the removed unique pattern on the representative CO.sub.2 waveform to obtain a final representative CO.sub.2 waveform.

2. The method of claim 1, wherein the two or more CO.sub.2 waveforms are waveform sub-segments.

3. The method of claim 1, wherein the determination of one or more scale factors is based on normalization.

4. The method of claim 1, wherein the one or more shape factors are determined by identifying parameters of best fit functions for each of the two or more CO.sub.2 waveforms from which the unique pattern has been removed.

5. The method of claim 4, wherein computing the representative set of shape factors comprises collecting and averaging the parameters of the best fit functions.

6. The method of claim 4, wherein constructing the single representative CO.sub.2 waveform comprises constructing a waveform based on averaged parameters and back scaling.

7. The method of claim 1, further comprising sub-segmenting each of the two or more CO.sub.2 waveforms from which the unique pattern has been removed prior to determining one or more scale and shape factors, and wherein constructing the single representative CO.sub.2 waveform further comprises combining the sub-segments.

8. The method of claim 1, wherein determining the one or more shape factors comprises converting each of the two or more CO.sub.2 waveforms from which the unique pattern has been removed into an independent binary digital matrix, wherein a value of one (1) defines a position in the digital matrix where the waveform passes through, and any other position in the digital matrix is defined by a value of zero (0).

9. The method of claim 8, wherein determining the one or more shape factors further comprises identifying a best fit function for each of the two or more independent digital matrices.

10. The method of claim 8, wherein computing the representative set of shape factors comprises creating a summed matrix by summing the two or more independent digital matrices.

11. The method of claim 1, comprising removing CO.sub.2 waveforms having artifacts from the set of the two or more waveforms, wherein the artifacts comprise non-recurring patterns.

12. The method of claim 1, comprising displaying the final representative CO.sub.2 waveform on a display unit, wherein the display unit is configured to display the final representative CO.sub.2 waveform starting at a predetermined point in a breath cycle of the subject.

13. A display unit configured to display a representative waveform and an area depicting a normal range of CO.sub.2 waveforms associated with a patient; wherein the representative waveform is overlaid on the area depicting the normal range of CO.sub.2 waveforms; and wherein the representative waveform comprises a single waveform computed based on an integration of a representative set of shape and scale factors, wherein said representative set of shape factors is determined based on one or more shape factors; wherein said representative set of scale factors is determined based on one or more scale factors; and wherein each of the representative set of shape factors and the representative set of scale factors represent two or more measured waveforms from which a unique pattern has been identified and removed, and wherein the unique pattern is a recurring pattern that recurs over a predetermined number of consecutive waveforms of the CO.sub.2 waveforms, and wherein the recurring pattern is representative of a physiological condition.

14. The display unit of claim 13 further configured to update the displayed representative waveform every preselected period of time and/or every preselected number of waveforms.

15. The display unit of claim 13, wherein the representative waveform is displayed starting at a predetermined point in a breath cycle of the subject.

16. The display unit of claim 13, further configured to display the representative waveform starting at a corner position of a display screen of the display unit such that the representative waveform is anchored to the corner position of the display screen such that a start position of the representative waveform does not change over time or number of breaths of the patient.

17. The display unit of claim 13, wherein the representative waveform is overlaid on the CO.sub.2 waveforms depicted in the displayed area.

Description

BRIEF DESCRIPTION OF FIGURES

(1) Examples illustrative of embodiments of the invention are described below with reference to figures attached hereto. In the figures, identical structures, elements or parts that appear in more than one figure are generally labeled with a same numeral in all the figures in which they appear. Dimensions of components and features shown in the figures are generally chosen for convenience and clarity of presentation and are not necessarily shown to scale. The figures (FIGs.) are listed below.

(2) FIG. 1 schematically shows a “normal” (textbook) CO.sub.2 waveform;

(3) FIG. 2A schematically shows a measured capnogram which includes a series of successive CO.sub.2 waveforms;

(4) FIG. 2B shows one representative waveform that represents all successive CO.sub.2 waveforms shown in FIG. 2A, according to some embodiments of the invention;

(5) FIG. 3A shows a series of CO.sub.2 waveforms presented on top of each other and a representative waveform that represents all CO.sub.2 waveforms, according to some embodiments of the invention;

(6) FIG. 3B shows a representative waveform that represents all CO.sub.2 waveforms of FIG. 3A, according to some embodiments of the invention;

(7) FIG. 4A schematically shows an area representing the normal range of CO.sub.2 waveforms for a healthy subject and a representative waveform, according to some embodiments of the invention;

(8) FIG. 4B schematically shows the same area as in FIG. 4A representing the normal range of CO.sub.2 waveforms for a healthy subject and a representative waveform of an asthma patient, according to some embodiments of the;

(9) FIG. 5 schematically shows an area representing series of CO.sub.2 waveforms and representative waveforms, according to some embodiments of the invention;

(10) FIGS. 6A-B show a flow charts illustrating a process of producing (constructing) a representative waveform, according to some embodiments of the invention;

(11) FIGS. 7A-F show CO.sub.2 waveforms taken under different conditions, according to some embodiments of the invention;

(12) FIGS. 8A-B show CO.sub.2 waveforms, according to some embodiments of the invention;

(13) FIG. 9 shows CO.sub.2 waveforms, according to some embodiments of the invention;

(14) FIGS. 10A-B show CO.sub.2 waveforms, according to some embodiments of the invention;

(15) FIG. 11 shows CO.sub.2 sample waveforms (taken from normal dataset) and their estimated fit with the five functions, according to some embodiments of the invention;

(16) FIG. 12 shows CO.sub.2 sample waveforms (taken from asthma patient dataset) and their estimated fit with the five functions, according to some embodiments of the invention;

(17) FIGS. 13A, B, C, and D which show a grid-matrix (20×20) representation of waveform sub-segments, according to some embodiments of the invention;

(18) FIG. 14 shows a waveform sub-segment of FIG. 14A on the binary grid-matrix (20×20) and its fit line, according to some embodiments of the invention;

(19) FIG. 15 shows a summed grid-matrix of waveform sub-segments, N=10, according to some embodiments of the invention; and

(20) FIG. 16 shows the optimal pathway with an overlay of the original waveform sub-segments and the best-fit, according to some embodiments of the invention.

DETAILED DESCRIPTION OF EMBODIMENTS

(21) In the following description, various aspects of the invention will be described. For the purpose of explanation, specific configurations and details are set forth in order to provide a thorough understanding of the techniques. However, it will also be apparent to one skilled in the art that the techniques may be practiced without specific details being presented herein. Furthermore, well-known features may be omitted or simplified in order not to obscure the description(s) of the techniques.

(22) Reference is now made to FIG. 1 which shows a “normal” (textbook) CO.sub.2 waveform (capnogram). Curve 100 represents the varying CO.sub.2 levels throughout the respiratory cycle. Points A, B, C, D, E and F are depicted on the capnogram. Section (A-B) represents the end of inspiration (Phase I), where the CO.sub.2 level is zero. Point B represents the beginning of exhalation. The sharp upstroke (B-C) represents the exhalation (Phase II). Follows is a gradual rise (C-D) (Phase III), a plateau having a peak just before (D) which represents the end of exhalation. The sharp down-stroke back to zero (D-E) represents the inspiration (Phase IV) and is followed by a clean inspiration period (section E-F).

(23) Reference is now made to FIG. 2A which shows a measured capnogram 200 which includes a series of twenty one (21) successive CO.sub.2 waveforms (for example, 202, 204 and 206). It can be seen that each of the waveform is slightly different from the others both in shape and scale factors. Therefore, obtaining valuable information from such capnogram, particularly just from looking at it, may be very hard if not impossible. FIG. 2B schematically shows one representative waveform 210 that represents all twenty one (21) successive CO.sub.2 waveforms shown in FIG. 2A, in accordance with some embodiments of the invention. This representative waveform is anchored to a corner (zero), not running across the screen and can change every X number of breaths or every Y number of seconds. A user (such as a doctor or a nurse) can easily obtain information from looking at the representative waveform, according to some embodiments of the invention. The scope of this invention, according to some embodiments, covers any method for displaying a representative waveform, such that it is anchored to a certain position in the monitor, such as a corner of the display.

(24) Reference is now made to FIG. 3A, showing an example of series of CO.sub.2 waveforms 302, and to FIG. 3B which shows representative waveform 306, which represents all CO.sub.2 waveforms 302 of FIG. 3A, according to some embodiments of the invention. As seen from FIG. 3A, obtaining any valuable information from looking at the multiplicity of the CO.sub.2 waveforms 302, is much more complicated than from the single, clear representative waveform 306.

(25) Reference is now made to FIG. 4A, which schematically shows an area 402 representing the normal range of CO.sub.2 waveforms for a healthy subject and a representative waveform 406 (reconstructed from the last 16 breathes) of a healthy subject, according to some embodiments of the invention. FIG. 4B schematically shows the same area 402 representing the normal range of CO.sub.2 waveforms for a healthy subject and a representative waveform 408 of an asthma patient (reconstructed from the last 16 breathes), according to some embodiments of the invention. Such presentation allows a user to clearly see that the representative waveform 406 is well within the normal range while representative waveform 408 (of an asthma patient) is not in the normal range. It can also be seen, for example, that representative waveform 408 (of an asthma patient) is lower and the “shoulder” defined as point C in FIG. 1 is rounder as compared to representative waveform 406 (of a healthy subject).

(26) Reference is now made to FIG. 5, which schematically shows the last three representative waveforms 506, 508 and 510 of an asthma patient (each calculated every 16 breathes) presented over a background of an area 502 representing a “textbook” overall location of a series of CO.sub.2 waveforms of a healthy patient, according to some embodiments of the invention. As seen from FIG. 5 it is clear to any user when looking at representative waveforms 506, 508 and 510 over the background of area 502, that the patient presenting representative waveforms 506, 508 and 510 has a breathing performance which is not normal. In addition, representative waveforms such as 506, 508 and 510 may represent a trend allowing a user to see changes of the patient condition over time.

(27) It is noted that an area, such as area 502, representing a “textbook” (normal) overall location of a series of CO.sub.2 waveforms of a healthy patient, may also be presented as two lines showing the upper limit and the lower limit of a normal range, as a collection of waveforms (as seen in FIG. 3A) or in any other way.

(28) Producing (Constructing) a Representative Waveform

(29) Reference is now made to FIG. 6A, which shows a flow chart 60 summarizing a process of producing (constructing) a representative waveform, according to some embodiments of the invention. Step 62 includes obtaining two or more waveforms. For the purpose of illustration, flow chart 60 refers to two waveforms (WF1 and WF2) but it is noted that any number of waveforms may be applied, for example, 5-20 waveforms, the number of waveforms detected in a period of time, such as 10-60 seconds or any other number of waveforms. Step 64 includes determining one or more scale factors (ScF) and one or more shape factors (ShF) for each of the two or more waveforms. Step 66 includes computing, based on the one or more shape and scale factors of each of the two or more waveforms, a representative (Rep) set of shape factors and scale factors representing the two or more waveforms (WF1 and WF2). Step 68 includes constructing a representative waveform (Rep WF) based on representative set of shape and scale factors one or more scale and shape factors.

(30) Reference is now made to FIG. 6B, which shows a flow chart 600 illustrating, in more detail, the process of producing (constructing) a representative waveform, according to some embodiments of the invention. When obtaining waveform(s) the first step 602 includes segmentation. Segmentation includes definition (beginning and end) of a single breath cycle (waveform) to be analyzed. A basic assumption may be that an anticipated waveform which would be received from a healthy subject would have a quasi-trapeze shape (see FIG. 1), with the four accepted identified stages (namely A-B, B-C, C-D, D-E and E-F). According to some embodiments, a received waveform that does not have one of these clear steps is considered as a breath without a shape that has clinical, physiological significance and hence is not used.

(31) Step 604 includes artifact identification. There are many artifacts that can cause changes to waveforms and create difficulties to distinguish between patterns that have physiological importance and those that do not. An artifact may be defined, according to some embodiments, as a section of a waveform that has no clinical value. In many cases, artifacts do not originate from a medical condition and particularly do not originate from respiratory and cardiac physiology. Examples of artifacts may include notches and spikes caused by talking, coughing, drinking, eating, interference by an appliance such as a cell phone, a computer or the like. These artifacts are generally non-repetitive.

(32) Other changes to the waveforms may be caused by regular activities, such as, moving, lying, sitting, changing a position and the like. These may optionally be treated as artifacts but may also be treated as different variations of waveforms and may still be regarded as “acceptable” data.

(33) Another effect that may cause changes to the waveform is the dilution of the breath sample with gasses, such as O.sub.2, which are delivered to the subject. This type of effect generally changes the waveforms in a repetitive manner.

(34) Methods are disclosed herein, in accordance with some embodiments, for eliminating or reducing the effect of artifacts. Artifacts may be identified based on predefined patterns that have been identified using controlled studies on both ill and healthy patients. They may further be identified, by their more ad-hoc appearance, shape and position in the waveform.

(35) Examples of the effect of patient's activities and O.sub.2 flow on waveforms can be seen in FIGS. 7A-F, which demonstrate waveforms of a patient taken during sitting, lying on the back, eating, talking, receiving O.sub.2 flow, and coughing, respectively. By looking at FIGS. 7A-F it can be seen that a user may loose valuable information due to the masking effect of the artifacts that may hide the required and meaningful information. According to some embodiments, breath cycles (waveforms) with a measurable quantity of artifacts may be identified and removed from the set of waveforms used to reconstruct the representative waveforms.

(36) According to some embodiments, in order to define artifacts a dataset comprising well defined and labeled artifacts (such as the activities discussed in relation to FIGS. 7C, D and F) may be generated. According to some embodiments, among the features that discriminate between artifacts and regular waveform features are dips trend and depth and the fit to function (such as, the presence and trend of dips larger than a certain threshold during upstroke and the measure of fitness to a function, Mean Square Error, for example). For example, a mathematical definition of artifact may include a waveform with dips larger than 5 mmHg during upstroke or plateau or with mse of a logarithmic function>2. Down-stroke dips are generally not regarded as artifacts since they often occur with addition of oxygen flow. FIGS. 8A-B show CO.sub.2 waveforms, according to some embodiments of the invention. Upstroke dip 802 having depth of approximately 8 mmHg can be seen in CO.sub.2 waveform 800 in FIG. 8A. Two down-stroke dips 812 and 814 with depth 1 and 20 mmHg respectively can be seen in CO.sub.2 waveform 810 in FIG. 8B. Upstroke dip 802 of CO.sub.2 waveform 800 in FIG. 8A may represent an artifact, if it is not a frequent (repetitive) event.

(37) FIG. 9 shows a series of waveforms some of which (waveforms under the arrows) have significant artifacts. Waveforms having significant artifacts may be excluded from further analysis (see next step, step 604).

(38) Returning to flow chart 600 of FIG. 6B, the next step after identifying artifacts (step 604) is step 606 which includes removal of waveforms with artifacts. According to some embodiments, these waveforms will not be used for further analysis. After this step, the waveforms are cleaned (or at least essentially cleaned) from artifacts, which as mentioned hereinabove, did not originate from a medical and physiological condition.

(39) Step 608 includes identification of unique patterns (characters) which generally have clinical significance. These unique patterns are typically recurring patterns that are superimposed on the standard waveforms, having an essentially trapeze like shape. According to some embodiments, the term “recurring patterns” may refer to patterns that recur in X % of the waveforms, wherein X % can be over 10%, over 20%, over 30-50% or X can be any other percent which can be constant or vary before or during monitoring. These unique patterns may provide clinical information when analyzed based on predefined patterns learnt during clinical studies. FIGS. 10A and B show, according to some embodiments, waveforms having reoccurring well-defined unique patterns, with seemingly physiological origins.

(40) Returning to flow chart 600 of FIG. 6B, the next step after identification of unique patterns (step 608) is step 610, which include removal of the (recurring) unique patterns. According to some embodiments, these unique patterns are separated from the standard wave shape (standard/normal waveform) but are returned in a later stage of the process of waveform reconstruction (step 652).

(41) Step 611 is optional and includes sub-segmentation of the waveform. As discussed above, segmentation (step 602) includes definition (beginning and end) of a single breath cycle (waveform) to be analyzed. Sub-segmentation (step 611) includes defining the “stages” of the waveform. As mentioned above, a basic assumption may be that an anticipated waveform which would be received from a healthy subject would have a quasi-trapeze shape (see FIG. 1), with the four accepted identified stages (namely A-B, B-C, C-D, D-E and E-F). A waveform could be divided into any number of stages, such as 1 (not dividing at all), 2, 3, or more. For example, as shown herein, according to some embodiments, the waveform is sub-segmented into two sub-segments. The first stage (sub-segment) relates to the increase in CO.sub.2 stage, including both upstroke (section B-C in FIG. 1) and plateau (section C-D in FIG. 1). The second stage (sub-segment) relate to the decrease in CO.sub.2, including the down-stroke (section D-E in FIG. 1) and the following clean inspiration period (section E-F in FIG. 1). These two stages (sub-segments) basically separate between initiation of exhalation up to the end of exhalation, and to the onset of inhalation up to the next initiation of exhalation.

(42) In case optional step 611 was applied, the following steps of flow chart 600 may be done on each sub-segment of the waveform separately or on a combination of sub-segments. In case optional step 611 was not applied, the following steps of flow chart 600 may be done on a whole waveform (a single breath cycle) from its beginning to its end.

(43) Step 612 includes identification of “scale factors” and scaling. Scale factors, as discussed hereinabove, refer to waveform values, such as, height, width, duty cycle, area under the curve or any other parameter or combination of parameters. Scaling may include, for example, normalization. Normalization may include for example, normalization of CO.sub.2 value by dividing CO.sub.2 by its maximum, such that the maximum value of CO.sub.2 will always be 1.

(44) The next steps of flow chart 600, which describes the process of producing (constructing) a representative waveform, relate to handling the waveforms “shape factors”. Shape factors, as discussed hereinabove, refer to any parameter that relate to and/or describe the shape of a waveform. For example, parameters of a non-linear function describing the upstroke or the entire exhalation stage as portrayed by a waveform. The shape factors of the waveform(s) are generally indicative of physiological condition(s) of a patient. For example, dominant shape factors of the waveform(s) may relate to respiratory process such as the mechanics of breathing. At this point, flow chart 600 may split. According to some embodiments of the invention, construction of the representative waveform may be based on a “best fit” mathematical approach (step 614) and/or on digitization (digital approach) (step 616).

(45) First Option (Step 614):

(46) The “best fit” mathematical approach (step 614) may include initial characterization extraction based on given, predefined functions describing (fitting) a given waveform or sub-segment in a waveform, for example, one or two sub-segments of a two sub-segment waveform (as disclosed herein above, the first sub-segment may relate to the decrease in CO.sub.2, including the upstroke (section B-C in FIG. 1) and plateau (section C-D in FIG. 1) and the second sub-segment may relate to the decrease in CO.sub.2, including the down-stroke (section D-E in FIG. 1) and the following clean inspiration period (section E-F in FIG. 1)). For applying the “best fit”, any known mathematical means of best fit may be used, such as “fit to function” or a look up table with limited best fit possibilities. Construction of the representative waveform can be realized for example, by choosing from a given limited number of possible, predefined shapes (based on “closest to”) or by a “true” mathematical calculation of representative value(s) using predefined functions for this purpose. A mixture of both options can also be used, in other words, first calculating the “true” representative value(s) and then looking for its best fit.

(47) Each waveform (and also the representative waveform) can thus be defined by a set of functions with their parameters (shape factors) and by other parameters (scale factors) which together build up the waveform. Hence the waveform obtained in the last “x” seconds or the “y” waveforms obtained can be memorized by defining just a few given parameters (shape factors and scale factors).

(48) Reference is now made to FIG. 11, which shows a sample waveform 1102 (taken from normal dataset) and its estimated fit with five functions. Reference is also made to FIG. 12, which shows sample waveforms 1202 (taken from asthma patient dataset) and its estimated fit with five functions. In each of FIGS. 11 and 12 only the first sub-segment of each wave form is shown with the “fit to function(s)” but of course the second sub-segment may also be processed to fit to any number of functions. It is also noted that each waveform can be divided to any number of sub-segments and each sub-segment or combination of sub-segments may be processed to fit to any number of functions out of which the best fit (for example, the function that is closest to the waveform curve) may be selected.

(49) The functions shown in FIGS. 11 and 12 are the following (the function names are arbitrary):

(50) $\begin{array}{c}1\text{-}\mathrm{Log}\text{:}\\ y=\frac{\mathrm{p2}}{\left(1+p3.Math.\exp \left(-p1.Math.x\right)\right)}\\ 2\text{-}\mathrm{GLC}\left(\mathrm{generalized}\mathrm{logistic}\mathrm{curve}\right)\text{:}\\ y=p2+\frac{p3}{{\left(1+p4.Math.\exp \left(-p1.Math.\left(x-\mathrm{p5}\right)\right)\right)}^{p4}}\\ 3\text{-}\mathrm{Verhulst}\text{:}\\ y=\frac{p4.Math.a}{b},\mathrm{where},a=1+p1.Math.\exp \left(-x/\mathrm{p2}\right);b=1+p3.Math.\exp \left(-x/\mathrm{p2}\right)\\ 4\text{-}\mathrm{WeibullCDF}\text{:}\\ y=p3.Math.{\left(1-\exp \left(-x/p1\right)\right)}^{p2}\\ 5\text{-}\mathrm{pl}5p\text{:}\\ y=p1+\frac{p5-p1}{a},\mathrm{where},a={\left(1+{\left(\frac{x}{p2}\right)}^{p3}\right)}^{p4}\end{array}$

(51) It is noted that any other function or combination of functions may be used and that the five functions presented herein are only exemplary functions.

(52) Returning to flow chart 600 of FIG. 6B, the next step include collection of functions, step 620. This step includes collecting the parameters of the functions that describe each waveform.

(53) The next step, step 622, includes averaging these parameters (and/or using any linear or non-linear mathematical method/function, such as arithmetic mean, geometric mean, integration, median or any power mean) over “y” waveforms or over the waveforms obtained during “x” seconds. Averaging the parameters and/or using any linear or non-linear mathematical method/function may permit, for example, computation of the most dominant, or reoccurring, most representative parameters. Averaging may include using a weighted average. In addition, waveforms with parameters that are far from the mean may be removed or used with lower weighting.

(54) This step results in obtaining the parameters of a representative normalized waveform or representative normalized waveform sub-segment(s) (when the waveform was sub-segmented first, such as in step 611).

(55) As mentioned above, one can also use a given limited list of waveform shapes, and mathematics may be used to find a given waveform shape which is closest to the measured waveform. This way, it is possible to have a limited list of predefined possible waves, for simpler and faster calculations.

(56) The next step, step 650, includes scale back and combining the representative normalized waveform sub-segments (if applicable). The parameters that were used to normalize may also be averaged, and used to return the representative normalized waveform back to the size that represents the true waveforms used to create it. This step results in a representative waveform that still lacks the recurring unique patterns which were removed step 610.

(57) The next step, step 652, thus includes adding (superimposing) any recurring or dominant unique patterns which were previously removed (such as in step 610) to the representative waveform. These unique patterns may be saved and reconstructed from predefined shapes stored in the memory, but whose sizes are defined based on the collected waveforms. This step results in the final representative waveform 654.

(58) Optional step 656 may include comparing the final representative waveform to library of waveforms which are indicative of known medical conditions (for example, typical abnormal waveforms). This may facilitate providing diagnosis, the degree of severity and/or medical recommendations.

(59) Second Option (Step 616):

(60) Returning to step 610 of flow chart 600 of FIG. 6B, instead of (or in some cases, in addition to) continuing to step 614 (“best fit” mathematical approach), the digital approach, step 616 (digitalization), may be selected. This step includes creating a low-resolution digital matrix to individually define the normalized waveforms. The matrix may be for example, a 20 by 20 or 50 by 50 matrix wherein a value of “1” defines a position where the wave passes through and “0” for other point.

(61) Step 616 of flow chart 600 of FIG. 6B can be described, for example, by FIGS. 13 A, B and C which shows a binary grid-matrix (20×20) representation of waveform sub-segments 1302, 1304, 1306, respectively. The waveform sub-segments in FIGS. 13A, B, C and D are the upstroke (exhalation) parts of whole breathing waveforms, but can be any other sub-segments or combinations of sub-segments. In each one of FIGS. 13A, B, C and D, waveform sub-segments 1302, 1304, 1306 and 1308, respectively, were placed on a grid-matrix (shown as 20×20 squares, but of course it can be more or less, depending on the resolution required, the more squares the better the resolution). Every square through which waveform sub-segments of 1302, 1304, 1306 or 1308 passes gets a value of one (1), while squares through which waveform sub-segments 1302, 1304, 1306 or 1308 do not passes get a value of zero (0).

(62) After Step 616 of flow chart 600 of FIG. 6B two options are possible, option A (step 630 of flow chart 600 of FIG. 6B) and option B (step 640 of flow chart 600 of FIG. 6B).

(63) Option A (Step 630 of Flow Chart 600 of FIG. 6B):

(64) Step 630 includes comparing separate grid-matrices to a set of preselected functions of waveforms (function bank/database). In this step, a set of predefined functions are collected. These selected functions best describe the separated waveforms. The representative normalized waveform or representative normalized waveform segment(s) can then be found based on mathematical integration and/or weighting of the waveforms building up the set (by going to step 622).

(65) FIG. 14 shows waveform sub-segment 1302 on the binary grid-matrix (20×20) of FIG. 13 A and its fit line 1402 (from a set of preselected functions of waveforms, function bank/database). Fit line 1402 best describes (fits) the grid-matrix's squares which received a value of 1 (through which waveform sub-segments of 1302 passed). Fit line 1402 in this example is number 20 from a database, with confidence level 0.84.

(66) Option B (Step 640 of Flow Chart 600 of FIG. 6B):

(67) Step 640 of flow chart 600 of FIG. 6B includes performing a mathematical combination (sum) of the digitized matrices to form a superimposed digitized matrix. Again, outlying waveforms may be removed.

(68) After forming the superimposed (summed) digitized matrix (step 640), step 642 includes finding the best path or in other words, finding the most dominant digital path taken by the largest number of matrices (which represent the waveforms). This step also promotes removal of artifacts that were not attended to previously.

(69) The following step 644 includes finding the best fit function to the superimposed (summed) digitized matrix (from a set of preselected functions of waveforms, function bank/database). This accelerates the computation and minimizes the data storage.

(70) Examples for steps 640-644 of flow chart 600 of FIG. 6B can be found in FIGS. 15 and 16.

(71) FIG. 15 shows the summed grid-matrix of waveform sub-segments (upstroke part of the whole breathing waveform) with N=10 (wherein N is the number of waveform sub-segments). The Shades indicate the number of gridded-waves that passed through each square in the matrix. The stars represent the optimal pathway.

(72) FIG. 16 shows the optimal pathway with an overlay of the original (normalized) waveform sub-segments 1602 and the best-fit 1604 (from a set of preselected functions of waveforms, function bank/database).

(73) Returning to flow chart 600 of FIG. 6B, the next step after step 644, is step 650, which includes scale back and combining the representative normalized waveform sub-segments (if applicable), as disclosed hereinabove.

(74) According to some embodiments, the methods disclosed herein allow memorizing a large history and or number of waveform data by just remembering the representative waveform characteristic parameters and using a driver to reconstruct the waveform on demand. This condensed manner of saving memory, may allow scrolling through representative waveforms over time, moving back to baselines or events, comparing with last “z” minutes or any other period of time or number of waveforms.

(75) According to some embodiments, any of the methods disclosed herein may further provide a confidence index (graphical or value), which may be a measure of how dominant the representative waveform is. This confidence level may be based on how many artifacts were there and/or dispersion of the data building the representative waveform. According to some embodiments, any of the methods disclosed herein may further provide a measure of the dispersion (graphical or value) of one or more given important scale factor parameters for example, height, width or I to E (Inhalation to Exhalation) ratio.

(76) In the description and claims of the application, each of the words “comprise” “include” and “have”, and forms thereof, are not necessarily limited to members in a list with which the words may be associated.

(77) The invention has been described using various detailed descriptions of embodiments thereof that are provided by way of example and are not intended to limit the scope of the invention. The described embodiments may comprise different features, not all of which are required in all embodiments of the invention. Some embodiments of the invention utilize only some of the features or possible combinations of the features. Variations of embodiments of the invention that are described and embodiments of the invention comprising different combinations of features noted in the described embodiments will occur to persons with skill in the art. It is intended that the scope of the invention be limited only by the claims and that the claims be interpreted to include all such variations and combinations.