Patent Publication Number: US-2017367618-A1

Title: Side-Stream Respiratory Gas Monitoring System

Description:
FIELD OF THE INVENTION 
     The present invention relates to a system and method for monitoring respiration and, more particularly to a respiration monitoring system that is configured to monitor respiratory and physiological performance of a person being monitored. The invention provides a system and method for real time, breath-by-breath side-stream monitoring of a patient. The system monitors respiration flow rate and flow constituents to assess various parameters of a patient&#39;s physiological condition and respiration performance and is configured to effectuate temporal alignment of respiration flow and gas concentration data. 
     BACKGROUND OF THE INVENTION 
     As disclosed in Applicant&#39;s U.S. Pat. No. 8,459,261, it is generally well accepted that monitoring respiration performance provides diagnostic insight into a patient&#39;s overall health as well as specific respiratory function. Understandably, the accuracy of any diagnosis or conclusion based on respiratory performance depends upon the skill of the technician interpreting the interpretation as well, the accuracy of the information acquired, and the timeliness of the calculation of the information. Respiratory monitoring generally requires the acquisition of the breath sample and a determination of a make-up or composition of the acquired breath sample. Physiologic events, patient condition, equipment construction and operation, and ambient conditions directly affect the accuracy of the information acquired by the respiration monitoring system. Accordingly, failure to account for activities associates with these events detrimentally affects the accuracy of the information acquired and any conclusions based thereon. Furthermore, the timeliness of the respiration performance determination directly affects patient treatment determinations. 
     The cardiac cycle is one physiological event that can be taken, into account in generating respiratory performance information. During the cardiac cycle, expansion of the chambers of the heart compresses against the lungs and generates a flow anomaly in the respiration cycle. Although the flow anomaly is internally imperceptible to most people, the flow anomaly presents a discontinuity in the respiratory flow that, if unaddressed, can lead to inaccurate interpretation of respiration performance. Other physiological conditions, such as poor lung performance, can also detrimentally affect interpretation of monitored respiration information. Flow path dead-space is another factor that must be addressed to provide an accurate determination of respiration performance. The flow path dead-spaces include patient respiration dead-spaces as well as dead-spaces associated with respiration monitoring system, or aspiration dead-spaces. 
     Respiration flow path dead-spaces are those portions of a respiration path that are susceptible to retaining exhalation or inhalation gases. Within a patient, the tracheal passage, mouth, and tongue can each contribute to respiration flow dead-spaces. Gases from a previous inhalation or exhalation cycle may momentarily remain in these spaces even though a subsequent inhalation or exhalation has begun. Within the monitoring equipment, the connection lines and sensor construction can each present dead-space data collection errors. That is, the lines that connect the sensor to the monitor and the sensor inserted into the respiration flow path may each retain gases associated with a previous inhalation of exhalation cycle. The accuracy of any respiration monitoring depends in part upon the monitoring systems ability to correct the respiration performance information for each of these exemplary dead-spaces. 
     Ambient conditions also affect the accuracy of the information acquired during respiration monitoring. For example, in an oxygen rich environment, an exhalation that includes elevated levels of oxygen would not provide an accurate indication of respiration performance if compared to respiration performance for an environment that does not include the elevated levels of oxygen. Similarly, an exhalation that includes excessive amounts of carbon dioxide provides no indication of the physiological performance if the testing environment is already rich in carbon dioxide. Accordingly, accurate respiration monitoring system must also account for deviations in the ambient test conditions. 
     Capnography, or the measurement of carbon dioxide in an exhalation, is commonly performed in many medical fields, including ventilated patients. Knowing the concentration of carbon dioxide as a function of time renders information about breath frequency, e.g. breaths per minute, and inspired or re-breathed levels of carbon dioxide. In some circumstances there is good agreement between the highest levels measured, often the end-tidal concentration of the carbon dioxide, and an arterial concentration, which is of value in caring for seriously compromised individuals. Understandably, such methods of comparing exhaled carbon dioxide levels to arterial carbon dioxide levels lack real-time monitoring of respiration performance. 
     Ascertaining an actual amount of a chemical being consumed or generated by a patient enhances the temporal or real-time monitoring and diagnosis of a patient condition. That is, monitoring both the respiration composition as well as volume enhances the diagnostic feature of a respiration monitoring system. Prior methods have relied upon collecting the exhalation gases and analyzing them sometime after the exhalation to ascertain the condition of the patient. This method, commonly referred to as the “Douglas Bag” collection method, is cumbersome, labor intensive, and discounts all of the information that can be acquired with real-time breath-by-breath data acquisition and analysis. This method is also commonly referred to as ‘indirect calorimetry’ for its indirect determination of the caloric expenditure of a patient by quantifying the carbon dioxide produced. Accordingly, it is desired to provide a respiration monitoring system that is configured to directly measure gas volumes as they are being produced or in real-time and preferably on a breath-by-breath basis. 
     To accomplish the measuring of gas volumes on a breath-by-breath basis, the gas concentrations as a function of time must be collected simultaneously with the flow information. Gas concentrations measured at the same location and at the same time as the flow measurement are commonly referred to as mainstream monitoring. A disadvantage of mainstream monitoring is that the monitoring is commonly performed at the location of the patient&#39;s exhaled breath, i.e., the mouth, or as close to the site of exhalation as possible. The equipment commonly utilized for such monitoring generally tends to be large, cumbersome, and costly. Another drawback of such monitoring systems is the increase in dead-space volumes that must be overcome by a patient. Attempts at miniaturizing these devices only further increases the cost associated with these diagnostic tools. Accordingly, there is a need for a lightweight, portable respiration monitoring system with reduced dead-space volumes. 
     Although side-stream systems, also known as metabolic carts, address most of these issues, such systems present other drawbacks. A side-stream system draws a sample of the patient&#39;s breath and transmits it to a remote gas concentration analyzer. A side-stream system is normally capable of measuring the flow in real time. However, the acquired expiration sample must travel some distance thru lumen tubing or the like to reach the gas content analyzer. Since the gas sample is analyzed at some time after the passage of the patients flow, such side-stream systems present a temporal misalignment between the value of the respiration flow and the gas concentration values. This temporal or time wise misalignment makes side-stream systems more difficult to implement and the data acquired therefrom more difficult to interpret. Accordingly, technicians must be extensively trained in the operation and understanding of the information acquired with such systems. As such, there is also a need for a respiration monitoring system that is cost effective to manufacture, implement, and operate. 
     Another consideration of respiration monitoring systems is calibration of the monitoring system as well as the display of the acquired information. The calibration of known respiratory monitoring systems is a time consuming and labor intensive process. The calibration generally consists of a technician passing a known volume of a known gas several times into the monitoring system. The combination of the known gas and the relatively known volume provides operative information that provides for calibrating the monitoring system. Unfortunately, the calibration process is generally only performed at the initiation of a monitoring session, must be frequently repeated to ensure the accurate operation of the monitoring system, and does not adequately address variations in the testing environment. Additionally, such calibration generally relies heavily on the experience of the technician performing the calibration and the availability of the calibration tools such as a gas tube injector of a known volume and a known gas. 
     The output of known monitoring systems also presents the potential for misinterpretation. During inhalation, the monitored oxygen level should be at a maximum level and the monitored carbon dioxide level should be at a minimum, i.e. ambient conditions. During exhalation, the detected oxygen level should be at a minimum and the detected carbon dioxide level should be a maximum. The inverse relationship of the oxygen level and the carbon dioxide level across a respiration cycle as well as the dynamic function of the respiration flow is generally not temporary aligned across a respiration cycle. As shown in  FIG. 1 , the respiration information is generally produced with no cyclic alignment and a technician must mentally align the output to generate a real-time flow and composition of the respiratory function.  FIG. 1  represents a trend plot  8  that includes a carbon dioxide trend  10  and a flow trend  12 . A first ordinate  14  shows that the carbon dioxide trend  10  is always positive as indicated by abscissa  15  and ranges from a plurality of relative minimums  16  to a plurality of relative maximums  18 . As discussed above, the relative maximums  18  of the carbon dioxide trend  10  reflect patient expiration whereas areas proximate relative minimums  16  reflect carbon dioxide levels associated with dead-space data acquisition and ambient carbon dioxide levels. 
     Flow trend  12  is indexed at second ordinate  20 . Flow trend  12  repeatedly crosses abscissa  15  such that positive values indicate an inhalation and negative values indicate an exhalation. As discussed above, each exhalation, a flow associated with a negative flow trend value, should correlate to a relative maximum of the carbon dioxide trend. As indicated with the reference letters A, B, C, and D, temporally aligning the flow trend and the carbon dioxide trend requires phase shifting of flow trend  12  to the right relative to carbon dioxide trend  10 . An identifier must be acquired to ensure an appropriate shift of the relative trends in determine the time-wise alignment of the flow and respiration composition information. Another lacking of known respiration monitoring systems is the ability to concurrently align a respiration flow value, a carbon dioxide concentration value, and an oxygen concentration value. Frequently, a carbon dioxide value and an oxygen value are displayed on different axis or completely different screens and therefore are not time aligned for interpretation. 
     Each of the drawbacks discussed above result in shortcomings in the implementation of known respiration monitoring systems. The cost and complexity of these respiration monitoring systems result in their infrequent utilization or improper interpretation of thee results acquired with such systems. Furthermore, the information acquired and utilized by such systems limits the diagnostic functionality of such systems in disregarding that information that can be utilized by time aligning the variable functions of the respiration cycle and variations in operation of the monitoring system. Although Applicant&#39;s prior patent U.S. Pat. No. 8,459,261 resolved a number of considerations discussed above, improvements to the accuracy, ease of operation, and accuracy of the data collected and displayed by the respiration monitoring system disclosed therein are disclosed herein. 
     For instance, the respiration monitoring system disclosed in Applicant&#39;s U.S. Pat. No. 8,459,261 discloses a flow and composition data alignment methodology wherein patient physiologic events, such as cardiac cycle artifacts, can be ascertained from the acquired composition and flow data. However, the physiologic events associated with respiration monitoring of some patients may be insufficiently represented in the flow and composition data to achieve the desired degree of accuracy associated with the time-wise alignment of the flow and composition data. In an attempt to achieve time-wise alignment of the flow and composition data, others, such as the system disclosed in U.S. Patent Application 2011/0161016, disclose systems that mathematically manipulate the flow and/or composition data, or derivatives or integrands thereof, to manipulate the time-wise alignment of the acquired flow and composition data. Unfortunately, such approaches rely on the accuracy of the acquired data to effectuate the proposed time-wise alignment of the data. 
     Accordingly, there is a need for a real-time respiratory monitoring system that is configured to align respiration flow information and respiration composition information in a manner that relies on data acquired from the flow sensor and can be independent of a physiologic event associated with patient respiration performance. Furthermore, there is a need for a respiration monitoring system that is simple and efficient to manufacture and operate and one which provides concise real-time time aligned respiration performance information. There is a further need for respiration monitoring system capable of generating an alignment signal that can be acquired with the respiration flow and composition information and whose information can be used to verify and/or align in a time-domain the respiration flow and respiration flow composition information. 
     BRIEF DESCRIPTION OF THE INVENTION 
     The present invention is directed to a respiration monitoring system that overcomes one or more of the aforementioned drawbacks. A side-stream respiration monitoring system according to one aspect of the present invention includes an analyzer that is configured to be fluidly connected to a flow sensor that is constructed to be disposed in a respiration flow path. A controller is associated with the analyzer and is configured to initiate delivery of an alignment signal generated by the analyzer to the flow sensor during a portion of at least one breath cycle. The controller determines a respiration flow value and at least a portion of a composition of the respiration flow on a breath-by-breath basis and temporally associates in a time-domain the determined respiration flow value and the determined portion of the composition associated with the breath-by-breath basis as a function of information associated with the alignment signal delivered to the flow sensor by the analyzer during the portion of the at least one breath cycle. Such a system allows alignment or confirmation of the time-wise alignment of the respiration flow and respiration composition information during those instances when other data, such as data associated with respiration performance manipulating physiologic events, is unavailable or otherwise insufficient to establish the desired time-wise alignment of the acquired respiration flow and respiration composition information. 
     Another aspect of the invention discloses a method of monitoring patient respiration information. A patient respiration flow is measured and a side-stream breath sample is acquired via a flow sensor associated with a respiration flow path. The method includes generating an alignment signal and acquiring at least a portion of the alignment signal with the side-stream breath sample. A flow of the side-stream breath sample, a concentration of oxygen, and a concentration of carbon dioxide in the acquired side-stream breath sample are determined and aligned with one another in a time domain with respect to their occurrence in the acquired side-stream breath sample as a function of information associated with the portion of the alignment signal acquired with the side-stream breath sample. 
     Another aspect of the invention discloses a method of manipulating respiration performance data in a side-stream respiration monitoring system. The method includes introducing an alignment signal to a respiration flow passing through a sensor. A flow rate and at least a portion of a composition of a respiration flow passing through the sensor are determined and aligned with one another in a time domain from information attributable to the alignment signal. 
     Various other feature, aspects, and advantages of the present invention will be made apparent from the following detailed description and the drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The drawings illustrate one preferred embodiment presently contemplated for carrying out the invention. In the drawings: 
         FIG. 1  is a schematic representation of data representation of prior art devices; 
         FIG. 2  is a perspective view of a side-stream respiration monitoring system according to the present invention; 
         FIG. 3  is a plan view of an analyzer of the monitoring system shown in  FIG. 2 ; 
         FIG. 4  is a perspective view of one embodiment of a sensor of the monitoring system shown in  FIG. 1  with an optional adapter and mask attached to the sensor; 
         FIGS. 5 a  and 5 b    are elevational end views of the sensor shown in  FIG. 4  with adapter connected to the sensor and the mask removed therefrom; 
         FIG. 6 a    is an elevational view of the sensor of the monitoring system shown in  FIG. 5  with the adapter removed from the sensor; 
         FIG. 6 b    is a perspective view of another sensor for use with the monitoring system shown in  FIG. 5 ; 
         FIG. 6 c    is a plan view of the sensor shown in  FIG. 6   b;    
         FIG. 6 d    is a cross-sectional view of the sensor shown in  FIG. 6 b    along line  6   d - 6   d;    
         FIGS. 7 a  and 7 b    are a schematic representation of the monitoring system shown in  FIG. 2 ; 
         FIG. 8  is a schematic representation of a flow determination correction procedure performed by the monitoring system shown in  FIG. 2   
         FIG. 9  is a schematic representation of a series of first composition correction operations performed by the monitoring system shown in  FIG. 2 ; 
         FIG. 10  is a schematic representation of a second composition correction procedure performed by the monitoring system shown in  FIG. 2 ; 
         FIG. 11  is a graphic representation of a concentration domain response time enhancement achieved with prior art respiration monitoring systems; 
         FIG. 12  is a graphic representation of a sample time response time enhancement achieved by the respiration monitoring system shown in  FIG. 2 ; 
         FIGS. 13 a  and 13 b    are a graphic representation of a data correction process performed by the analyzer shown in  FIG. 3 ; 
         FIG. 14  is a schematic representation of a gas concentration physiological mirror correction procedure performed by the monitoring system shown in  FIG. 2 ; 
         FIG. 15  is a graphic representation of one embodiment of a dead-space correction procedure achieved by the respiration monitoring system shown in  FIG. 2 ; 
         FIG. 16  is a graphical representation of a flow reversal synchrony that shows the time aligned flow and gas concentration values achieved by the respiration gas monitoring system shown in  FIG. 2 ; 
         FIG. 17  is a schematic representation of a threshold calibration and check procedure performed by the respiration gas monitoring system shown in  FIG. 2 ; 
         FIG. 18  is a schematic representation of an ambient condition flow and gas concentration alignment procedure performed by the respiration gas monitoring system shown in  FIG. 2 ; 
         FIGS. 19 a  and 19 b    are a schematic representation of a flow cycle determination and correction procedure performed by the respiration gas monitoring system shown in  FIG. 2 ; 
         FIGS. 20 a  and 20 b    are a schematic representation of a time aligned respiration information generation procedure that accounts for the flow cycle determination and correction procedure shown in  FIGS. 19 a    and  19   b;    
         FIG. 21  is an exemplary display of the information acquired and corrected by the respiration gas monitoring system shown in  FIG. 2 ; 
         FIG. 22  is a schematic representation of an, alternate respiration flow and composition time alignment protocol that includes an extraneous alignment signal that is communicated to a flow sensor and information associated therewith being subsequently utilized to achieve a flow and composition time alignment offset; 
         FIGS. 23-26  show various plots associated with the generation of respiration flow and respiration composition data offset values associated with the generating a time domain alignment of the respiration flow and respiration composition data associated with utilization of the extraneous time domain alignment signal. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
       FIG. 2  shows a monitoring system  30  according to the present invention. Monitoring system  30  includes a control or analyzer  32 , a sensor  34 , and a display  36 . Sensor  34  is constructed to engage a respiration flow, indicated by arrow  38 , or a participant or patient  40 . A number of lumens or tubes  42  operatively connect sensor  34  to analyzer  32 . A first and a second tube  44 ,  46  are connected to sensor  34  to detect a pressure differential of respiration flow  38  in sensor  34 . A third tube  48  acquires an aspirated sample of respiration flow  38  and communicates the sample to analyzer  32 . A physiological detector, preferably a heart rate monitor  50 , is also connected to analyzer  32  and constructed to communicate a patient cardiac status to analyzer  32 . Preferably, monitor  50  is configured to monitor both the pulsatile effects of the patient&#39;s cardiac cycle as well as the saturated oxygen content of the patient&#39;s circulation system. 
     Analyzer  32 , having acquired the data or signals from tubes  42  and heart rate monitor  50 , generates time aligned and composition corrected respiration information and outputs the information at display  36  as explained further below. Analyzer  32  includes optional user inputs  52  that allow a user to selectively configure the operation of analyzer  32  and the output of display  36  such that analyzer  32  and display  36  generate and output the desired information, respectively. It is further appreciated that display  36  can be constructed as a touch screen display such that a user or technician can manipulate the display results thereof and operation of analyzer  32  by touching selected areas of the display without utilization of auxiliary input devices such as a keyboard  54  and/or a mouse  56 . 
     As described further with respect to  FIG. 3 , analyzer  32  includes a first input  57  and a second input  59  to allow multiple gas sources to concurrently be connected to analyzer  32 . As shown in  FIG. 2 , first input  57  is connected to sensor  34  and second input  59  is connected to another sensor, a Douglas bag, gas cylinder, or container  61 . It is appreciated that container  61  can be configured to contain a volume of a known gas or a volume of a gas collected from another patient. Such a configuration allows monitoring system  30  to monitor and assess multiple gas sources. Such a configuration is particularly useful in environments where monitoring of several patients is desired or where patients with reduced respiration tidal volumes, such as premature babies, have such low respiration volumes that collection of a respiration is required to assess the composition of the respiration gases. 
     Referring to  FIG. 3 , analyzer  32  includes a housing  58  having a control or controller  60  contained therein. An oxygen sensor  62 , a nitrous oxide sensor  64 , and a carbon dioxide sensor  66 , and a flow sensor  67  are also positioned in housing  58 . It is understood that oxygen sensor  62  be any of a number of technology based such as laser, acoustic, solid state, amperometric such as galvanic, or potentiometric. A number of tubes  68  interconnect sensors  62 ,  64 ,  66  and communicate respective portions of the acquired flow through the analyzer. A pump  70  and a number of valves  72 ,  74 ,  76  control the directional passage of the respiration flow through analyzer  32 . Analyzer  32  includes a humidity sensor  78  and a temperature sensor  80  configured to monitor both ambient temperature and humidity as well as temperature and humidity of the respiration flow. It is further appreciated that analyzer  32  include an optional heater and/or humidifier to communicate thermal energy and/or moisture to a patient via the respiration flow. 
     First input  57  and second input  59  extend through housing  58  and are constructed to removably engage the tubes  42  connected to sensor  34  or container  61  as shown in  FIG. 2 . An electrical connector  84  also extends through housing  58  and is constructed to communicate information generated by analyzer  32  to external devices such as personal computers, personal data assists (PDA&#39;s), cell phones, or the like. Alternatively, it is further understood that analyzer  32  include a wireless interface to allow wireless communication of the information acquired and calculated by analyzer  32  to external devices. Analyzer  32  includes an input connector  82  constructed to communicate information from patient monitor  50  to the analyzer. Input  84  is constructed to removably connect monitor  50  to analyzer  32  to communicate the information acquired by monitor  50  to the analyzer  32 . It is understood that inputs and connectors  84  be any conventional connection protocol such as serial pin connectors, USB connectors, or the like, or have a unique configuration. Analyzer  32  further includes a leak test valve  89 , the operation of which is described below with respect to the automatic calibration and performance monitoring of analyzer  32 . It is appreciated that the relatively compact and lightweight nature of analyzer  32  provides a respiration monitoring system  10  that is highly portable and operable with a number of sensors.  FIGS. 4-6  show a number of sensors that are applicable with the present invention. 
       FIG. 4  is an enlarged view of sensor  34  with an optional adapter  88  and an optional mask  90  connected thereto. Mask  90  ensures that nasal respiration is prevented or directed toward sensor  34  during a respiration monitoring procedure. Such a configuration ensures information indicative of an entire respiration flow is communicated to analyzer  32 . Comparatively, adapter  88  is constructed to allow a portion of a respiration flow to bypass sensor  34 . Such a configuration is particularly applicable to acquiring respiration data during periods of high respiration flow such as during adult or athlete stress testing procedures. 
     As shown in  FIGS. 5 a    and  5   b,  adapter  88  includes a number of passages  92  constructed to allow a portion of a total respiration flow to pass to atmosphere thereby bypassing a flow passage  94  of sensor  34 . Preferably, adapter passages  92  are configured to allow a flow that is a multiple of the flow directed through sensor  34  to pass through adapter  88 . More preferably, passages  92  are constructed to allow a multiple of ten&gt;of the respiration flow directed through sensor  34  to pass through adapter  88 . Such a configuration simplifies the calculation associated with determining the total flow information when only a fraction of the total flow is directed through the sensor  34 . Adapter  88  facilitates the increased respiration flow generally associated with a stress test without overly burdening the respiration system of the patient or participant associated with requiring the entirety of the respiration flow to pass through the more constricted passage of sensor  34 . 
       FIG. 6 a    is a detailed view of sensor  34  with adapter  88  and mask  90  removed therefrom. Adapter  88  includes a patient end  96  and an atmosphere end  98 . A sensor section  100  is generally disposed between the patient end  96  and the atmosphere end  98 . Sensor section  100  includes a venturi-like section  102  constructed to generate a pressure differential between respective ends of the sensor section  100 . Signals communicated to analyzer  32  via first tube  44  and second tube  46  allow analyzer  32  to detect the pressure differential across sensor section  100  and thereby provide information utilized to calculate the respiration flow  38  communicated through sensor  34 . Third tube  48  acquires a sample of the respiration flow, or an aspiration, and communicates the acquired sample to the analyzer  32  which then determines the make-up or composition of the gas of the respiration flow. It is appreciated that the construction of the sensor may vary depending, in part, on a patient&#39;s respiration ability. That is, sensor  34  may be adapted to accommodate respiration monitoring of patients with low respiration tidal volumes or flows such as for analyzing respiration compositions associated with premature infants, neonatal patients or the like. For such applications sensor  34  may be configured to operate at a flow resistance over a differential pressure range of approximately 0-16 cm water which covers a smaller flow range generally in the range of 0 to ten liters per minute. Further details of the construction and operation of sensor  34  are disclosed in Applicant&#39;s U.S. Pat. Nos. 5,925,831 and D413,825 and U.S. Publication No. 2004/0254491, all of which are incorporated herein by reference. 
       FIG. 6 b    shows another sensor  550  according to the present invention. A first end  552  of sensor  550  is constructed to be directed toward a patient side  554  of a respiration path, indicated by arrow  556 . Sensor  550  includes an intubation tube  558  for those patients that are required to be intubated. Another end.  560  of sensor  550  is constructed to be directed toward a source of respiration gas  562 . For those patients that require respiration assistance, sensor  550  is connected to a respirator (not shown) by a tube assembly  564 . Tube assembly  564  includes a first tube  566  constructed to extend between a valve  568  an end  560  of sensor  550 . A second tube  570  extends between valve  568  and the respirator. Valve  568  includes a vent  572  and is constructed to direct an exhaled gas to atmosphere. Valve  568  is commonly understood as a “Wye” valve and is configured to prevent the direction of the exhalation toward the respirator. Understandably, gas directed through vent  572 , rather than being dumped to atmosphere, could be connected to another tube and collected at a Douglas bag as described herein for analysis by analyzer  32 . 
     Sensor  550  includes a body  574  that extends between first end  552  and second end  560 . A number of tubes  576 ,  578 ,  580  are connected to body  574  and fluidly connected between the respiration path  556  and an analyzer  32 . Tubes  576  and  578  are connected to sensor  550  and analyzer  32  to detect the flow associated with respiration path  556 . Tube  580  is connected to sensor  550  to acquire an aspiration sample of the respiration gas. Unlike sensor  34 , the aspiration sample acquiring tube  580  is positioned outside the space between the flow sensing tubes  576 ,  578 . The importance of this distinction is described further below with respect to  FIG. 6   c.  A number of cavities  582  are formed in an exterior surface  584  of body  574  and do not extend through the body  574  into the respiration path  556  formed therethrough. A first adapter  586  and a second adapter  588  are engaged with body  574  proximate first end  552  and second end  560 , respectively. Adapters  586 ,  588  are configured to facilitate the connection of sensor  550  to tubes  558 ,  566  without detrimentally affecting the dead-space associated with sensor  550  or the patient dead-spaces discussed herein. 
       FIG. 6 c    shows sensor  550  with adapters  586  and  588  removed therefrom. Body  574  includes a first section  590  constructed to removably engage adapter  586  and a second section  592  constructed to removably engage adapter  588 . Understandably, adapters  586 ,  588  could be integrally formed with body  574  to provide a patient and application specific sensor  550 . A detecting section  594  includes a first port  596  and a second port  598  fluidly connected to respiration path  556  with cavities  582  disposed between the ports  596 ,  598 . Body  574  includes a sample port  600  that also extends through body  574  and is fluidly connected to respiration path  556 . Sample port  600  extends through body  574  downstream from a patient side of respiration path  556  relative to first and second ports  596 ,  598 .  FIG. 6 c    also includes several exemplary dimension values  602  which show an exemplary positioning of ports  596 ,  598 ,  600  relative to first, second, and detecting sections  590 ,  592 ,  594  of body  574 . Understandably, these dimensions are merely exemplary and other relative sizes and orientations are envisioned and within the scope of the claims. 
       FIG. 6 d    shows a cross-section of sensor  550  along line  6   d - 6   d  indicated in  FIG. 6 c    with adapters  586 ,  588  connected thereto.  FIG. 6 d    also includes several exemplary dimensions  603  associated with the relative size and construction of sensor  550 . As shown in  FIG. 6   d,  an interior surface  604  of body  574  includes a restricting member  606  that projects from interior surface  604  into a flow passage  608  of body  574 . Preferably, restricting member  606  extends into flow passage  608  past the centerline of the passage  608  to create a pressure differential between ports  596 ,  598 . In a preferred embodiment, restricting member  606  has a generally arcuate or curved outer surface. This pressure differential is communicated to analyzer  32  via ports  596 ,  598  and tubes  576 ,  578  (as shown in  FIG. 6 b   ) and is utilized to generate the respiration flow data. Cavities  582  extend into body  574  are prevent deformation of restricting member  606  from a desired shape and size during the forming process. Understandably, although two cavities  583  are shown, other numbers of cavities or cavity constructions are envisioned and within the scope of the claims. 
     Sample acquiring tube  580  is sealingly received in port  600  and has an end  610  that preferably extends beyond interior surface  604  of body  574  into flow passage  608 . The extension of end  610  beyond the interior surface  604  of body  574  reduces the potential of collecting moisture associated with the respiration flow  556 . Understandably, port  600  of body  574  could be constructed to include a nipple that would extend from interior surface  604  to provide this reduction in the potential collection of respiration condensation or water content. Tube  580  communicates the acquired sample to analyzer  32 , or a Douglas bag, for a determination of the composition of the respiration gas. 
     The relative positioning of sample port  600  outside of the space between ports  596  and  598  is particularly applicable for respiration flow monitoring of those patients with reduced respiration flow tidal volumes such as premature infants. Generally, premature babies has such fast respiration rates with such low respiration tidal volumes that acquiring a respiration sample proximate restricting member  606  can detrimentally affect patient respiration. That is, acquiring a sample much closer to the patient than a trailing edge  612  of restricting member  606  has the effect of acquiring a sample that is larger than an actually expired sample. Accordingly, such a configuration has the effect of extracting respiration gas from a patient rather than allowing the patients anatomy to exhale the respiration gases. As such, sensor  550  is configured to allow breath-by-breath monitoring in even the smallest of patients. It is further appreciated that an interior surface, or respiration flow facing surface of one of more of sensors  34 ,  550  can include a hydrophobic or more preferably a hydrophilic layer or coating configured to effect the generation of condensate associated with the passage of the respiration flow through sensor  34  and to mitigate interference of condensate or moisture associated with the respiration flow with the acquisition of the flow and flow composition signals. 
       FIG. 7  shows a schematic representation of sample flow through analyzer  32 . Analyzer  32  is constructed to receive any of a number of inputs  106  associated with a gas to be analyzed. Inputs  106  can include a room air or ambient input  108 , a calibration gas input  110 , a Douglas bag input  112 , and a patient input  114 . A first tube  116  communicates ambient input  108  to gas valve  72  and a second tube  118  communicates ambient input  108  to flow valves  74 ,  76  of analyzer  32 . Similarly, tubes  44  and  46  connected to sensor  34  communicate patient flow-to-flow valve  74  and  76 . When a Douglas bag input  112  is utilized with analyzer  32 , a first tube  120  and a second tube  122  communicate a Douglas bag gas material to valves  74 ,  76 . Understandably, it is appreciated that a Douglas bag is a container configured to store a respiration sample or a known expiration sample. 
     Regardless of the source of the input gas, flow valves  74 ,  76  communicate the received flow to a flow analyzer  124  via tubes  126 ,  128 . Flow analyzer  124  is connected to a temperature sensor  130  and includes a temperature correction protocol  132  configured to detect and associate a detected flow with a respective temperature of the analyzer  32  or atmosphere. Temperature correction protocol  132  corrects the calculated flow value for variable temperatures associated with the test environment. Flow analyzer  124  includes a flow offset drift compensator  134  figured to account for drift variations associated with extended operation of analyzer  32 . Accordingly, flow analyzer  124  is configured to adjust the measured flow parameter for variations associated with ambient conditions as well as operational variation of the flow analyzer  124 . 
     Gas samples that are communicated to gas valve  72  are communicated to a pump control  136  and therefrom to each of oxygen sensor  62 , nitrous oxide sensor  64 , and carbon dioxide sensor  66 . Oxygen sensor  62 , nitrous oxide sensor  64 , and carbon dioxide sensor  66  are configured to indicate the respective levels of the constituent gases contained in the input flow regardless of the source of the input gas. Accordingly, analyzer  32  is operable with a number of gas sources that can be concurrently connected to the analyzer  32 . As will be described further, controller  60  is configured to assess which type of gas source is connected to the analyzer and initiate a monitoring sequence or a calibration sequence. 
     Still referring to  FIG. 7 , analyzer  32  generates a number of outputs  140 , including a sample aspiration rate  142  that is derived from pump control  136 . A chamber pressure value  144  and an uncompensated carbon dioxide value  146  are derived from carbon dioxide sensor  66 . An uncompensated nitrous oxide value  148  is derived from nitrous oxide sensor  64  and an uncompensated oxygen value  150  is generated from oxygen sensor  62 . Flow analyzer  124  generates patient pressure data  152  and respiration flow data  154 . Analyzer  32  also includes a plurality of user inputs that include a power input  156 , a valve control input  158 , a serial communication input  160 , a sensor-type selection  162 , an ambient pressure input  164  and a patient finger clip  166  configured to monitor patient cardiac condition. 
     Analyzer  32  includes an oxygen saturation controller  168  that determines a patient oxygen saturation level communicated to the oxygen saturation controller  168  from an oxygen saturation serial communication link  170  constructed to engage the patient monitor  50 . Analyzer  32  is also configured to generate an output associated with a sensor type  172  and an ambient pressure determination  174 . As discussed above, analyzer  32  includes a number of serial communication links  176  that facilitate connectivity between analyzer  32  and other auxiliary devices such as personal computers, PDA&#39;s and the like. Such a configuration allows analyzer  32  to operate with a number of different flow input sources, be configured to operate with a number of gas and flow sensors, and provide a number of variable format outputs. Analyzer  32  is constructed to be dynamically responsive to the gases communicated to the analyzer, the connectivity modalities associated with the separable components of the monitoring system, and providing data that is in a user desired format. 
     Analyzer  32  includes a flow determination and correction protocol  224  as shown in  FIG. 8 . Correction protocol  224  acquires respiration flow data  154  from flow analyzer  124  as shown in  FIG. 7 . A noise filter  226  addresses electrical signal noise associated with operation of flow analyzer  124 . Correction protocol  224  is also configured to determine a sensor type  228  associated with acquisition of the flow. That is, the determination of the flow sensor type  228  determines whether the sensor is constructed to receive the respiration flow of an adult, a neonatal or infant, a premature baby, or a high-flow, i.e., bypass sensor configuration as previously described with respect to  FIGS. 2-7 . 
     Correction protocol  224  calculates the respiration flow  230  using a flow calculation curve as described below. A patient pressure flow correction  232  is calculated from the patient pressure data  152  as determined by flow analyzer  124 . A sample aspiration rate correction  234 , is implemented and utilizes the sample aspiration rate  142  generated from pump control  136  as shown in  FIG. 7 . Having calculated and corrected the flow based on patient pressure and aspiration rate correction, correction protocol  224  determines a respiration flow value  236  associated with each breath cycle of a monitored respiration cycle. The flow value  236  is then temporally aligned with a respiration phase  238  using an inspired/expired flag  240  as acquired from the respiration cycle. Having determined the phase of the associated flow value, correction protocol  224  generates a respiration aligned flow value  242  indicative of the flow value at any given time during a respiration cycle. 
       FIG. 9  shows a number of first data correction procedures performed by analyzer  32 . As discussed above with respect to  FIG. 7 , analyzer  32  is constructed to detect a chamber pressure  178 , an ambient pressure  180 , and is responsive to a pressure units selection  182 . These parameters are input to a pressure conversion factor controller  184  that is configured to output a corrected detected pressure in desired units  186 . Analyzer  32  also includes a carbon dioxide correction protocol  188 , an oxygen correction protocol  190 , and a nitrous oxide correction protocol  192 . Carbon dioxide correction protocol  188  adjusts a respiration carbon dioxide value  194  by passing the uncompensated carbon dioxide value  146  through a noise filter  198 , a unit converter  200 , a pressure-broadening correction  202  and a gas interaction correction  204 . Noise filter  198  is constructed to resolve electrical noise associated with operation of the carbon dioxide sensor  66 . Unit converter  200  is constructed to convert the carbon dioxide value to user-desired units. Pressure broadening correction  202  is constructed to further adjust the uncompensated carbon dioxide value  146  with respect to operation of the carbon dioxide sensor  66  at the system, environment, or ambient operating pressure. 
     Gas interaction correction  204  corrects the uncompensated carbon dioxide value  146  for misrecognition of other gas molecules as carbon dioxide molecules. That is, due the nature of the operation of the carbon dioxide sensor  66 , nitrous oxide molecules may occasionally be recognized by carbon dioxide sensor  66  as carbon dioxide molecules. Gas interaction correction  204  adjusts the uncompensated carbon dioxide value  146  for such occurrences to provide a carbon dioxide level  196  that is adjusted for these molecule misrecognition events. 
     Oxygen correction protocol  190  also includes a noise filter  206  configured to correct the uncompensated oxygen value  150  generated or provided by oxygen sensor  62 . Noise filter  206  addresses the electrical noise associated with operation of oxygen sensor  62 . A unit&#39;s conversion  208  is configured to provide an oxygen value associated with a desired user oxygen value units. Similar to gas interaction correction  204 , oxygen correction protocol  190  includes a gas interaction correction  210  configured to correct the uncompensated oxygen value  150  for occurrences of oxygen sensor  62  interpreting non-oxygen molecules as oxygen. Oxygen correction protocol  190  generates an oxygen level value  212  that has been corrected for electrical noise associated with operation of the sensor  62 . Similar to carbon dioxide correction protocol  188 , nitrous oxide correction protocol  192  corrects an uncompensated nitrous oxide value  148  through utilization of a noise filter  214 , a unit&#39;s conversion  216 , pressure broadening correction  218  and a gas interaction correction  220  to provide a nitrous oxide level value  222  that more accurately reflects an actual amount of nitrous oxide contained in a respiration or gas sample and a value that has been corrected for the background noise associated with operation of the nitrous oxide sensor  64  and is in a user desired units. The nitrous oxide value has also been corrected for atmospheric and operational pressure differentials, and non-nitrous oxide gas interaction correction. 
       FIG. 10  shows a response time and enhancement protocol  250  performed by analyzer  32  for each of the carbon dioxide level  196 , oxygen level value  212  and nitrous oxide level value  222  calculated as shown in  FIG. 9 . As shown in  FIG. 10 , response time protocol  250  receives an input  252  associated with the level values  196 ,  212 ,  222  which are associated with the respective gas levels in any given sample. Inputs  252  are verified and adjusted via a physiological mirror  254  as described further below. Protocol  250  calculates a slope sign and magnitude-determined constant K  256  for each input  252  associated with the respective gas. A concentration domain enhancement  258  is generated for each input  252 . The slope of the acquired data signal is determined, for example based on the signal change over the last ten samples, and, if the slope is flat or approximates zero, the constant K is chosen to be zero. By first qualifying the state of the rate of change of the signal, analyzer  32  avoids amplifying noise which would occur if a uniform K value were applied regardless of the instantaneous sample change. When the signal slope changes significantly, due to a fast rising or falling edge, constant K is computed to be generally proportional to the slope change of the concentration and proportional to accumulated flow volume up to a maximum allowed value. The interaction of the flow volume in addition to the change in concentration information is used to qualify constant K. 
       FIG. 11  shows a problem associated with prior art concentration domain response time enhancement procedures that are overcome by the present invention. Usually, a speed-up circuit, or its equivalent in software, is employed in the concentration domain. That is, if the rise at the analyzer is x, then the actual rise at the aspiration location must have been at least y wherein y is a value greater than x.  FIG. 11  shows that if gain concentration enhancement of gain times 20 is used, a change in concentration X would result in a reported concentration Y over the same time interval. This approach has severe limitations in that it attempts to compensate a function of concentration versus time by only adjusting the information in one axis. To reproduce a very fast rise, say that which is generated by a square wave input at the aspiration site, overshoot occurs long before a squared output can be obtained. This overshoot is often followed by ringing of the function about the final value before settling occurs thereby detracting from the responsiveness of the system. As shown, simply reducing the gain factor does not reproduce what occurred at the aspiration site but merely reduces the amount of the overshoot and ringing or signal bounce. 
     Referring to  FIGS. 10 and 12 , unlike the solely concentration domain enhancement results shown in  FIG. 11 , response time enhancement protocol  250  adjusts for variable gains associated with any of the respective input  252 . Having acquired the concentration domain enhancement  258 , enhancement protocol  250  performs a time shift of the signal in proportion to the magnitude of slope and a second derivative  262  associated with inputs  252 . After the signal is enhanced in the concentration domain, the signal is enhanced in the time domain. Analyzer  32  calculates the first and second derivative of the signal and computes incremental time points from the first and second derivative magnitudes. This manipulation pushes the start of the signal ahead in time, while the upper part of the signal, where the signal begins to plateau, gets retarded in time such that there is no residual time shifting when the slope returns to zero. 
     As shown in  FIG. 12 , for samples acquired every five milliseconds, the carbon dioxide trend is adjusted for multiple gains, indicated by arrows  263 ,  265  across an acquisition cycle. Each correction protocol  188 ,  190 ,  192  performed by controller  60  of analyzer  32  is configured to determine a parameter output value by adjusting a value of an input, i.e. the detected value, in both an amplitude domain  265  and a time domain  263 . It is appreciated that the amplitude domain  265  can be any of a concentration, a temperature, a pressure, or a flow value associated with the acquired data. It is further understood that when the amplitude domain  265  is a concentration, the associated value is the detected concentration of a gas of interest such as oxygen, carbon dioxide, nitrous oxide, or water vapor. It is further appreciated that each correction protocol  188 ,  190 ,  192  be configured to the type of sensor being utilized. That is, the correction protocol will not be the same for a laser-type oxygen sensor as compared to the galvanic-type oxygen sensor. 
       FIGS. 13 a  and 13 b    show uncorrected data and an exemplary first corrected output associated with use of a galvanic-type oxygen sensor, respectively. As shown in  FIG. 13   a,  due in part to sensor selection and construction, the responsiveness as well as the gain accuracy of the respective sensors must be corrected.  FIG. 13 a    shows an uncorrected fractional percentage of an oxygen deficit value  265  and an uncorrected fractional percentage carbon dioxide value  267 . During a first portion of the data acquisition cycle  277 , oxygen sensor  62  is more responsive than the carbon dioxide sensor  64  resulting in oxygen value  265  remaining to the left of the carbon dioxide value  267 . After a given period, gain deviation of the oxygen sensor  62  results in the oxygen deficit data value falling below the carbon dioxide value  267 . This operational variation of the sensors results in a deviation in the respiratory quotient value. These offsets, generally associated with the operation gain of the sensors, can be accounted for in a relatively simple manner over extended data acquisition cycles, however, these operational variations should be addressed to improve the accuracy of the real-time breath-by-breath monitoring. 
       FIG. 13 b    shows an output associated with a first correction of a response time characteristic. As shown in  FIG. 13   b,  adjusting oxygen deficit values  265  during portion  277  of the data acquisition cycle achieves the alignment of the fractional percentage of carbon dioxide value  267  and the deficit fractional percentage of the oxygen value  265  such that the two values generally correlate as determined by the RQ value. During operation, analyzer  32  determines a maximum slope of a leading edge of the acquired oxygen and carbon dioxide values. A difference in the abscissa value associated with a line corresponding to the maximum slope provides an oxygen to carbon dioxide offset value. This offset value is applied to generally align the carbon dioxide and deficit oxygen values over portion  277  of the data acquisition cycle. To align the portion of the acquisition cycle beyond portion  277 , analyzer  32  generates a gain prediction associated with operation of each of oxygen sensor  62  and carbon dioxide sensor  64 . The oxygen sensor gain value is then determined to account for the deviation between the operation of the carbon dioxide sensor and the oxygen sensor over an extended duration such that the deficit oxygen value correlates to the carbon dioxide value over nearly the entirety of the data collection cycle. That is, the first correction corrects for a response time difference between the pair of sensors and the second correction is different than the first correction and corrects for another response time characteristic, i.e. gain differentiation between the respective sensors. 
     Referring back to  FIG. 10 , protocol  250  performs a second physiological mirror  264  on the time adjusted concentration values. Procedure  250  performs a second concentration domain enhancement  266  and a second time domain enhancement  268  time shift in proportion to the magnitude and slope of the second derivative. After the second time domain enhancement  268 , protocol  250  again updates the data with a physical mirror check  269  and adjusts the data with a concentration domain enhancement  271  wherein constant K is divided by an exponential increase of half of the constant K utilized at enhancement  258 . Process  250  further adjusts the time domain enhancement shift  273  in proportion to the magnitude of the slope and the second derivative prior to completion  275  of the time enhancement protocol  250 . Upon completion  275  of protocol  250 , analyzer  32  generates a partial pressure compensated gas concentration for each of the inputs  252  associated with the gasses communicated to analyzer  32 . 
     Having corrected the respective gas values for partial pressure and temporal delays in the operation of the sensors  62 ,  64 ,  66 , analyzer  32  verifies the calculated data through application of a physiological mirror comparison. That is, dynamic alignment is needed to account for differences between internal, pneumatic connections, resistances and dead-space volumes associated with the sample gas acquisition. This compensation becomes more important if there are more than one gas species to be analyzed. It is commonly understood that for every oxygen molecule consumed in a living organism, there is some concomitant generation of carbon dioxide. The exact relationship of these quantities is based upon the stoichiometric relationship of the associated gas. Because the chemical makeup of proteins, carbohydrates, fats, etc. is different the exact relationship of oxygen to carbon dioxide is different. However, there are some aerobic physiologic ranges which cannot be exceeded and therefore generate a physiologic mirror between the associated gases. It is generally accepted that the physiologic mirror of the association carbon dioxide to oxygen during human respiration is approximately between 0.66 and 1.3 for humans at rest. 
     Analyzer  32  utilizes this physiological mirror to align the signals of different gas sensors as well as for filtering the signals associated with the respective sensors by identifying anomalies in the physiological mirror. Analyzer  32  is preferably configured to acquire and analyze a gas sample every five milliseconds. Analyzer  32  collects and corrects flow and gas concentration data as well as other information such as patient pressure and temperature and computes the carbon dioxide produced and the oxygen consumed for each sample acquired. The division of the carbon dioxide value by the oxygen value provides a respiratory quotient (RQ) for each sample acquired. By calculating the respiratory quotient every sample cycle, any misalignment of the respective outputs of the gas sensors becomes readily apparent and can be adjusted for. This process provides an indication as to the operating condition of the analyzer  32 . 
     As shown in  FIG. 14 , partial pressure compensated values  270  of the respective sample constituents, a process using a physiological mirror  272  as described above to provide a further corrected output  274  associated with each of the respective constituent sample gases. Referring to  FIG. 15 , analyzer  32  also includes a dead-space compensation protocol. A plot  276  showing an Aitkin dead-space shows one exemplary output associated with a dead-space calculation. Other procedures, such as the Bohr method and/or consideration of a patient&#39;s arterial carbon dioxide concentration obtained from blood gas sampling method, are equally applicable to the present invention. Instead of viewing a sample against time, plot  276  shows a gas concentration as a function of expired volume. 
     The particular breath shown in  FIG. 15  shows an oxygen consumption trend  278  which represents inspired volume minus concentration as volume increases. Plot  276  includes an oxygen trend  278  and a carbon dioxide trend  280  associated with a sample breath. Vertical lines  282 ,  284  represent transition positions of the breath phase. The left of vertical line  284  is a first phase  286  that represents an absolute dead-space. A second phase  288  between vertical lines  282  and  284  generally occurs over a relatively short period of time with the gas concentration rapidly changing as a function of time. A third phase  290 , to the right of vertical line  284 , represents that area of a breath cycle wherein the concentration plateaus or only slowly increases while volume continues to accumulate. Vertical line  292 , generally between vertical lines  282  and  284  delineating phase II  288  from phase I  286  and phase III  290 , represents the Aitkin dead-space. The volume, that point where vertical line  292  intersects abscissa  294 , represents the breath dead-space and is a combination of absolute and physiologic dead-space. 
     The respiratory quotient (RQ) as explained above is represented on plot  276  at line  296 . RQ  296  represents the ratio of carbon dioxide volume to oxygen volume for the breath represented in plot  276 . Analyzer  32  continually monitors RQ  296  with respect to the detected values of oxygen  278  and carbon dioxide  280  such that an anomaly in either of oxygen trend  278  or carbon dioxide trend  280  would be represented in a time-aligned anomaly in RQ  296 . Upon the detection of an anomaly in RQ  296 , analyzer  32  verifies the accuracy of oxygen value  278  and carbon dioxide value  280  to auto-correct an oxygen value or a carbon dioxide value that does not correspond to the RQ value as determined from the time aligned physiological mirror of the corresponding breath oxygen value and carbon dioxide values. 
     In addition to the physiological mirror, dead-space, and response time enhancements discussed above, analyzer  32  includes a flow reversal protocol (FRP) as graphically represented in  FIG. 16 . Comparing  FIGS. 1 and 16 , it is shown that analyzer  32  performs a flow reversal synchronization of the trends associated with flow  298  and a gas concentration value  300 . As shown in  FIG. 16 , pulsatile effects  302  monitored by the flow generally correspond to pulsatile effects  304  monitored in the gas value  300 . Accordingly, temporally-aligning the pulsatile effects  302  in the flow  298  with the pulsatile effects  304  in the gas value  300  provides for temporal alignment of the respective trends associated with both flow and gas concentration value. As will be described further below with respect to  FIG. 21 , such alignment provides a well-organized and readily understandable flow and concentration output as compared to that which is generally shown in  FIG. 1 . 
     As disclosed further below with respect to  FIGS. 22-26 , situations can exist wherein pulsatile effects  302  are so minimally represented in the acquired and calculated flow and composition data that an alternate approach is desired to ensure the accuracy of the time domain flow and composition data. As disclosed below with respect to  FIGS. 22-26 , when desired, analyzer  32  introduces an extraneous signal to respective breath respiration flows associated with the respective sensor such that the acquired respiration flow information includes information that is indicative of the extraneous alignment signal. As disclosed further below, this non-patient originated alignment signal is introduced to the respiration flow via the sensor at desired intervals such that the information associated with the alignment signal can be easily ascertained from the respiration flow and composition data acquired by analyzer  32  to effectuate a time-wise or time domain alignment between the respiration flow and respiration composition information. 
     Analyzer  32  also includes a number of other calibration and operation procedures as shown in  FIGS. 17-20 . Referring to  FIG. 17 , analyzer  32  includes a threshold confirmation protocol  306  wherein, during operation, analyzer  32  receives a plurality of inputs  308  associated with a carbon dioxide value  310 , an oxygen value  312 , a time value  314 , a system temperature value  316  and a signal input value  318 . Understandably, other inputs could also be provided to analyzer  32 . Threshold confirmation protocol  306  automatically checks to confirm that thresholds associated with any of the inputs  308  do not exceed or otherwise not satisfy desired threshold values. It is further understood that each of the thresholds associated with threshold confirmation protocol  306  can be configured by a user to a desired value. Threshold confirmation protocol  306  determines if any of the checked thresholds  320  are exceeded  322 . If any of the desired thresholds are exceeded  324 , protocol  306  delivers an offset command to a user  326  and/or performs an automatic offset calibration  328  as described further below. In the event that no threshold is exceeded during operation of the analyzer  32 , the analyzer updates the offset health display  332  associated with the checked thresholds  330 . 
     Referring to  FIG. 18 , analyzer  32  calculates a sample aspiration rate  334 , detects an analyzer pressure  336 , an atmospheric pressure  338 , determines a sample gas transport delay time, and implements the flow reversal synchronology  340  as described above with respect to  FIG. 16 . Analyzer  32  then generates a gas value offset  342  which is utilized for time alignment of gas data with flow data  344 . Analyzer  32  detects a carbon dioxide value  346 , an oxygen value  348  and a nitrous oxide value  350  in conjunction with the dynamic gas time alignment offsets  352  as discussed above with respect to  FIGS. 12-15 , finds the gas data  354  and communicates the time aligned gas data  354  and the flow data  356  to time align the gas and flow data  344 . Preferably, analyzer  32  updates the breath data buffers sample every five milliseconds  358  and updates the waveforms  360  associated with the time aligned gas and flow data  344  for every sample as well. It is appreciated that other breath data buffer update and time alignment schedules may be utilized that are more or less frequent than the preferable five millisecond and every breath sample intervals disclosed above. 
     Approximately every 32 samples, analyzer  32  optionally updates the numerics associated with the raw gas and flow data  362  as a service performance monitoring function to allow background monitoring of the performance of analyzer  32 . The information associated the system performance monitoring function may occur at any given interval and may be hidden from a user and accessible only in an analyzer service or monitoring window separate from the respiration data window associated with display  36 . Analyzer  32  next performs a mode determination  364 . As shown in  FIGS. 19 a    and  19   b,  mode determination  364  includes a determination  366  as to whether the analyzer  32  is collecting data. During collection of data  368 , mode determination  364  monitors an inspired/expired flag  370  to determine a flow transition from an expired to an inspired flow direction  372 . If the flow is transitioning from an expired to an inspired flow direction  374 , mode determination  364  provides a delay  376  to wait for an inspired value. The flow is not transitioning from an expired to an inspired flow  378 , mode determination  364  determines whether flow is transitioning from inspired to an expired flow  380 . If the flow is transitioning from an inspired to an expired flow  382 , mode determination  364  enters an expired waiting state  384 . And if the flow is not transitioning from inspired to expired flow  386 , mode determination  364  confirms a collecting state  388 . 
     When mode determination  364  is not in a collecting state  390 , mode determination  364  determines whether it is an expired waiting state  392  and, if so,  394  monitors a sample time as compared to a gas offset time  396  associated with an inputted gas offset  398 . If the sample time is greater than a gas offset time  400 , mode determination  364  associates the state as expired  402  and directs operation of analyzer  32  to expired breath handling  404  as shown in  FIGS. 20 a    and  20   b.  When the sample time is not greater than the gas offset time  406 , mode determination  364  is directed to an expired waiting  408  state. If mode determination  364  is not in a collecting state  390  and is not in an expired waiting state  392 , mode determination  364  determines an inspired waiting state  410 . And if the mode determination  364  is in an inspired waiting state  410 ,  412 , mode determination  364  determines whether a sample time is greater than or equal to a gas offset time  414  as determined by gas offset  416 . The sample time is greater than the gas offset time  418 , mode determination  364  confirms an inspired state  420  and directs operation of analyzer  32  to inspired breath handling  422  mode as shown in  FIG. 20   b.  If the sample time is not greater than or equal to the gas offset time  424 , mode determination  364  maintains an inspired waiting state  426 . 
     If analyzer  32  is not in a collecting state  390 , not in an expired waiting state  391 , and not in an inspired waiting state  428 , mode determination  364  automatically checks a Douglas collecting state  430 . When analyzer  32  detects the connection to a Douglas bag collecting system  432 , analyzer  32  collects gas from the Douglas bag  434  and performs a Douglas breath detect algorithm and increment breath count  436  to mimic a breath cycle when analyzer  32  is connected to a Douglas bag. When Douglas collecting state  430  is activated, analyzer  32  determines whether a desired number of breaths have been collected  438  and, if so,  440  directs mode determination  364  to Douglas bag breath handling  442  as shown in  FIG. 20   a.  Analyzer  32  maintains Douglas collecting state  430 ,  444  until a desired number of breaths have been collected. Upon confirmation of a no collection mode determination  364 , analyzer  32  further includes a number of offset calibration options  446 ,  448  utilized to not process breath data during offset calibration of analyzer  32 . Such a configuration allows analyzer  32  to be configured for operation with offset calibrations as may be required by any particular patient. 
       FIGS. 20 a  and 20 b    show the initialization calibration procedure associated with expired breath handling  404 , inspired breath handling  422  and Douglas bag breath handling  442 . When analyzer  32  begins in expired breath handling  404 , analyzer  32  determines expiration start and end points associated with the breath data buffers  450 . Analyzer  32  determines a breath rate  452  and calculates a plurality of parameters associated with an acquired sample value  454 . Analyzer  32  then calculates the sample values  454 , patient or respiration path dead-space  456 , and dynamically aligns the gas offset  458  using the calculated RQ and the calculated dead-space  456 . During expired breath handling  404 , analyzer  32  determines a dead-space confidence  460  determined by a number of dead-space values for each associated sample. Having adjusted for dead-space variations, expired breath handling  404  corrects gas data with time alignment  462  utilizing any of the methods discussed hereabove and then calculates  464  volumes and pressures associated with the constituents of the sample acquired. 
     Comparatively, inspired breath handling  422  determines an inspired start and end points in breath data of the sample acquired, calculates  464  the volume and pressure of the constituents of the acquired sample  466 , stores the calculated values and performs a rebreathe operation to remove previously acquired calculations  468 . Inspired breath handling  422  stores an inspired carbon dioxide value  470  and adjusts the inspired carbon dioxide value from the dead-space calculation as previously described with respect to  FIG. 15 . Inspired breath handling  422  confirms a collecting state  472  and proceeds to correct gas data time alignment  462  and calculations  464 . 
     During Douglas bag breath handling  442 , analyzer  32  performs a minimal carbon dioxide slope check  474  and if the acquired carbon dioxide value is valid  476 , Douglas bag breath handling  442  proceeds to calculations  464 . If the carbon dioxide slope data check  474  is invalid or below a desired threshold  478 , Douglas bag breath handling  442  maintains slope error data and disregards the determined Douglas bag data in proceeding to the correct gas data time alignment  462  and calculation  464 . Accordingly, regardless of where in a respiration cycle analyzer  32  begins data acquisition, analyzer  32  auto-corrects for various parameters that can be acquired during any given phase of the respiration cycle. 
     As previously mentioned, collecting a patient&#39;s expired gases allows analyzer  32  to perform time-independent analysis of a gas source. When connected to a Douglas bag and a sensor  34 , analyzer  32  periodically switches from measuring the patient to measuring the gases from a collection vessel for a brief time, thereby performing a time independent RQ determination. Any error between the instantaneously calculated or real-time RQ value and the Douglas Bag RQ value can be used to make finer adjustment to the instantaneously calculated RQ value. The collection vessel can simply be connected to the exit port of a ventilator, connected directly to a patient flow thereby circumventing any ventilator mixing, or other adequately purged collection vessels. It is further envisioned that analyzer  32  be configured to automatically acquire the Douglas bag sample thereby eliminating any clinician intervention and rendering very accurate trend Douglas bag RQ data. 
     Still referring to  FIGS. 20 a    and  20   b,  analyzer  32  further includes several breath alignment correction procedures and calibration procedures. A first breath alignment correction is a flow aspiration correction procedure. A sample gas flow being, aspirated from the flow path of sensor  34  is calculated by analyzer  32  and the corresponding breath parameters are adjusted for the sensor aspirated gas values. The sensor aspirated gas causes an error in the patient flow measurement that must be corrected. Since the location of the sensor  34  gas sampling tube  48  (shown in  FIG. 6 a   ) is between the tubes  44 ,  46  (also shown in  FIG. 6 a   ) used for the flow measurement, the error is asymmetric and opposite in direction depending on whether the patient flow is an inhalation or an exhalation and is a function of the magnitude of the patient respiration flow. If the gas were removed further down stream after the flow ports, this correction to the flow measurement would not be necessary, but an additional time domain shift would be required. In either case, if the patient flow is not significantly greater than the aspiration flow, such as in the case of monitoring small infants, entrainment will occur which must also be addressed. 
     In the case where the gas is being aspirated between the flow measurement ports, the gas being aspirated produces a pressure drop that is unequal across the ports and is direction dependent that appears as patient flow. Also, the flow error, while proportional to the aspiration rate, is not the same as the aspiration rate. For example, if one is aspirating at 200 ml/min (0.2 lpm), simply adding 0.2 lpm back into the patient flow reading does not adequately reflect the required correction. The error, however, is proportional to the aspiration rate as well as the patient flow rate, and changes with patient flow direction. Analyzer  32  empirically determines the magnitude and direction of the necessary corrections needed to correct the flow readings for this sensor aspiration. 
     As the patient flow becomes small or approaches zero, the aspiration flow becomes more significant and a condition known as entrainment occurs. Here, the amplitude of the gas signals becomes diluted with other gasses. For example, if the patient gasses are being expired at a low flow rate compared with the aspiration rate, a portion of the sample being aspirated may be redirected into the analyzer. The measured patient flow and controlled and measured aspiration flow is used to determine the true concentration of the patient gas as communicated to the gas sensors. This type of flow correction generally only needs to be performed on infant and premature infant flow levels, as the transitions such pediatric breathing occurs too quickly to be determined by a digitizing sample rate of preferably 5 msec per sample acquisition. 
     Analyzer  32  includes a dead-space confidence qualifier procedure that is generally applicable with very high breath rates and low dead-space quantities, such as with infants, wherein the total time involved in measuring the dead-space is very short. In such a situation, the time from the flow crossing or start of expiration until the phase II  288  dead-space point  284  may be so short that the insufficient data samples are acquired. If very few data samples are captured during this time, the dead-space confidence qualifier provides feedback to the technician as to the level of confidence in the result. The confidence is based on how many samples, approximately 1 sample every 5 milliseconds, are captured within the dead-space time as calculated using the Aitkin method as shown in  FIG. 15 . Indicator colors such as green for a high or good level of confidence, yellow for caution, and red for warning may be utilized in display  36  as described below with respect to  FIG. 21 . It is envisioned that greater than 10 samples would produce a high or good level of confidence, 3 to 10 samples would warrant a caution, and less than 3 samples should produce a warning as to the quality of the dead-space qualifier. The color is used for either the display of the dead-space qualifier itself or as the background color highlighting the dead-space numerical display. 
     Analyzer  32  also includes a flow offset drift compensation procedure. Analyzer  32  monitors patient respiration flow using a differential pressure transducer connected to sensor  34 . The pressure transducer is generally sensitive to changes in temperature. A standard pressure/temperature calibration is performed which characterizes the transducer. In addition, a flow offset drift compensation is performed in an attempt to minimize the zero (offset) error due to changes in temperature between offset calibrations. The method used characterizes pressure vs. temperature using a second order polynomial. Using this equation, a prediction is made of what the pressure would be as temperature changes for the “zero” pressure from the zero pressure determined at the last offset calibration. The flow offset drift compensation procedure acquires an offset calibration temperature T 0  and acquires a second temperature TX during acquisition of the flow sample. Analyzer  32  calculates pressures P 0  and PX using T 0  and TX and then calculates an offset pressure, Poffset, as the difference between P 0  and PX. Analyzer  32  subtracts Poffset from the sampled pressure prior to calculating patient flow thereby correcting for flow offset drift. 
     Analyzer  32  is also configured for automatic calibration of operation of the analyzer  32  and sensors  62 ,  64 ,  66 . Preferably, sensors  62 ,  64 ,  66  are chosen to be inherently gain stable. The gain stability is due to the fact that the sensors have a high degree of resolution at the lower end of their measurement range and lesser resolution towards the upper end. This is desirable since most of the time measurements will be made in the lower part of the range of the respective sensors  62   64 ,  66 . Understandably, with higher resolution, sensor drift becomes more apparent. The present invention communicates atmospheric air through housing  58  of analyzer  32  to correct for offset drift automatically using an inexpensive calibration gas, i.e. room air. 
     The room air communicated through housing  58  is utilized as an inhalation sample and a mixed gas having a known composition and or respiratory quotient is communicated to analyzer  32  to provide an exhalation sample. The ambient oxygen concentration is calculated by correcting the ambient oxygen value measured by oxygen sensor  62  for ambient water vapor dilution through utilization of the information detected by temperature and humidity sensors  78 ,  80  shown in  FIG. 3 . The room air is also passed through a carbon dioxide scrubber to insure a zero carbon dioxide value. The concentration of the known gas is entered by an operator. Preferably, the concentration of the constituents of the mixed gas is selected such that a result respiratory quotient is within a normal physiological range. One of valves  72 ,  74 ,  76 ,  89 , or an additional valve, and pump  70 , or another supplemental pump, cooperate to switch the source of gas communicated to sensors  62 ,  64 ,  66  between the mixed gas and the room air. 
     Preferably the mixed gas is provided at a flow rate that is greater than a sample aspiration rate with the excess gas being vented. A pneumatic venturi device is connected between analyzer  32  and the inlet of the mixed gas and creates a pressure differential perceived by flow sensor  67 . According, analyzer  32  mimics a breath cycle with real-time operation feedback and detectable gas transitions. It is further understood that, by aligning the artificially developed flow indication with a measured patient flow level, the operability of flow sensor  67  can be confirmed as well as providing a confirmation that the flow of mixed gas is accurately detected by flow sensor  67 . 
     User selectable triggers perform offset calibrations of sensors  62 ,  64 ,  66  that include time from last calibration, temperature from last calibration, carbon dioxide inspired level, oxygen inspired level, and tidal volume imbalance (Ve/Vi) over a series of sample breaths. The tidal volume imbalance provides a parameter that is particularly useful for determining offset calibration. Determined over a reasonable period of breaths (for example, a 7 breath rolling buffer), the total inspired breath volume should correlate to the total expired breath volume. If the values do not correlate, the discrepancy provides indicia that analyzer  32  flow offset has drifted, or that a leak is present in the gas circuit. Also, as part of this feature, the display  36  includes a health meter indication for each trigger. 
     As shown in  FIG. 3 , flow leak valve  89  of analyzer  32  is configured to allow analyzer  32  to check for leaks in the gas sampling path and those in the patient flow measurement path. The gas sampling path is from the sensor  34  to the input  57 ,  59  as shown in  FIG. 1 . If a leak exists in the gas sampling path and is small, gas waveforms will still be present but will show up with a larger time fag from the patient flow signal. This will result in greater dead-space readings than what are actually present. If the leak in the sampling path is larger, the dead-space becomes very large and the system experiences difficulty attempting: to align the gas concentration with flow and presents a detectable error condition. 
     To detect small gas sampling leaks, valve  89  is used to close off the sampling line internal to the system immediately after the input to the housing. When closed, the sample pump is used to draw a vacuum to a lower pressure. When this pressure is reached, the pump is turned off and this pressure must be maintained for a desired time. If internal leaks are present, the lower pressure will quickly climb back to ambient pressure providing an indication of an internal leak condition. External leaks are detected as a flow error if either of tubes  44 ,  46  have a leak. The noticeable affect is an imbalance between inspired and expired volumes depending on location. During a leak check, a user is instructed to connect plugs to a flow sensor and analyzer  32  shuts off valve  72  to either input  57 ,  59  uses pump  70  to apply positive pressure to the system. As above, positive pressure above ambient must be maintained for a period of time to indicate a no-leak condition. 
     Analyzer  32  is further configured to automatically calibrate operation of sensors  62 ,  64 ,  66  for variable environmental factors including ambient gas concentrations and ambient temperature and humidity.  11 . Preferably, oxygen sensor  64  is an electrochemical device. Although such devices generally include an electrical or mechanical temperature compensation feature, such corrections are insufficient to address the parameters associated with respiration monitoring. That is, such corrective measures introduce errors of inherent to the corrective devices. Accordingly, analyzer  32  is constructed to operate in such a way as to address the inherent errors associated with operation of the sensor. Analyzer  32  also adjusts operation as a function of humidity variations associated with operation of the sensors  62 ,  64 ,  66 . 
       FIG. 21  shows an exemplary time-aligned respiration output  500  generated by analyzer  32 . Output  500  includes a trend window  502  configured to display a carbon dioxide concentration  504 , an oxygen concentration  506 , a flow value  508 , and a saturated blood oxygen value  510  in a common screen  512  on a common plot  514 . As discussed above, each of the respiration cycle concentration values  504 ,  506 ,  508 ,  510  are temporally aligned along the data trend. The carbon dioxide concentration  504  and the oxygen concentration  506  values are generally produced as mirror images of one another such that quick viewing and interpretation of the breath data is achieved. It is further appreciated that the oxygen concentration data could be acquired by scaling the respiration data by a factor such that it correlates to the carbon dioxide concentration value. Alternatively, it is understand that analyzer  32  be configured to monitor the oxygen content deficiency and that this value then be inverted to generally mimic the carbon dioxide concentration value. Both configurations provide a carbon dioxide and oxygen concentration displayed value generally similar to that shown in  FIG. 21 . 
     It will further be appreciated that the respiration flow value  508  is also time aligned with the carbon dioxide and oxygen concentrations  504 ,  506 . Output  500  also includes a dead-space trend display  515  configured to allow viewing of both the common plot  514  and a dead-space trace  517  that is utilized to calibrate and align the common trends of the common plot  514 . A plurality of value displays  516  are included in output  500  and provide exact values of any of the oxygen saturation value  518 , a carbon dioxide concentration  520 , an oxygen concentration  522 , a flow data  524 , and nitrous oxide concentration  526  associated with the data related with any given time along common plot  514 . During operation of analyzer  32 , any given time of acquisition along common plot  514  can be interrogated for the data associated therewith. 
     Output  500  also includes a volume and RQ display window  530  configured to display rolling tidal volume data  532  associated with inspired and expired volumes as well as rolling RQ data  534 . Analyzer  32  is configured to acquire and determine the oxygen concentration, carbon dioxide concentration, and nitrous oxide concentration on a breath-by-breath basis. Analyzer  32  temporally aligns that acquired data and display and corrects, the data as it is acquired. The compact and time aligned display of the data at output  500  provides a system wherein a technician can quickly ascertain the respiration performance of a patient as well as performance of the analyzer. Understandably, output  500  could be configured to allow various levels of operator interaction with the operation and performance of analyzer  32  as well as the various levels of data, calculation, modification, and calibration performed thereby. 
     As alluded to above,  FIGS. 22-26  relate to the generation and assessment of an extraneous alignment signal that is communicated to the respiration flow associated with a respective sensor  34 ,  550  and the information associated with which is subsequently acquired and assessed by analyzer  32  to achieve a desired time-domain alignment of the acquired respiration flow and respiration composition data. The extraneous alignment signal protocol has been shown to be particularly advantageous to achieving a desired time alignment of the respiration flow information and respiration composition information when the patient originating information associated with the reverse flow protocol (RFP), such as patient pulsatile effects  304 , are too small or fast for utilization of the pulsatile effects to achieve a desired data time alignment accuracy. It is however appreciated that the extraneous alignment signal protocol disclosed below can also be utilized as a verification of the intended alignment when the patient pulsatile effects are sufficient for achieving the desired alignment between the respiration flow information and the respiration composition information. 
     Referring to  FIG. 22 , extraneous alignment signal protocol  600  associated with monitoring system  30  can include an input  602  associated with analyzer  32  or controller  60  to allow selective operation of the alignment signal protocol  600 . For instance, when pulsatile effects  304  are sufficiently represented in the acquired respiration data samples, alignment signal protocol  600  can be disabled. When enabled, alignment signal protocol  600  associated with operation of analyzer  32  first determines when it would be desired to introduce an alignment signal  604  to the respective sensor  34 ,  550  associated with the respiration flow path. As disclosed below, the alignment signal is preferably introduced to the sensor at a time when the information associated with the alignment signal would be easily assessable from the information associated with respiration performance. The determination of when to introduce the alignment signal  604  is preferable based on previous respiration performance information and/or average values associated a selected number of proceeding breath cycles. 
     Once determined, an alignment signal is generated  606  by analyzer  32  and communicated to sensor  34 ,  550 . In a preferred embodiment, the alignment signal is a gas signal composed of atmospheric air communicated to sensor  34 ,  550  via one or more of lumens or tubes  44 ,  46 ,  48  associated with sensor  34 ,  550 . It is further appreciated that a dedicated tube and/or port could be provided between sensor  34 ,  550  and analyzer  32  to effectuate communication of the extraneous flow alignment signal  606  therebetween. Controller  60  and/or pump control  136  associated with analyzer  32  is configured to provide the instruction associated with the desired orientation of one or more of valves  72 ,  74 ,  76 ,  89  and operation of pump  70  to effectuate communication of the alignment signal  606  to sensor  34 ,  550 . After the alignment signal  606  has been communicated to the respective sensor  34 ,  550 , analyzer  32  continues operation of the breath-by-breath assessment of respiration performance via continued collection of a respiration sample and flow/flow pressure data  608 . The subsequently acquired respiration sample and flow/pressure information necessarily includes information associated with the alignment signal communicated to respiration flow via sensor  34 ,  550 . Alignment signal  606  has a duration and composition such that the effects of the alignment signal are imperceptible to the patient whose respiration is being monitoring but effects the respiration performance data in a manner wherein the alignment signal can be assessed from the subsequently acquired respiration data. 
     Referring to  FIGS. 22-25 , upon acquisition of each side-stream-respiration sample and flow signal that includes alignment signal  606 , extraneous flow signal alignment protocol  606  assesses the acquired data to determine  610  one or more of the start P 1  and center or peak P 2  associated with the acquired pressure data and one or more of the start G 1  or center G 2  associated with the composition with at least one of the constituents of the respiration gas sample. As shown in  FIGS. 23-25 , various parameters can be utilized to correlate or align the respiration flow data and the respiration composition data to achieve the desired alignment between the flow and composition information. It is further appreciated that the relative changes between one or more of the pressure, relative component concentrations, or alternate pressure or flow and composition information can be utilized to assess the relative or desired offset required to achieve the desired time-wise alignment of the data associated with the respiration flow and respiration composition. That is, information associated with the alignment signal can be assessed from one or more of the relative concentration of a constituent in the respiration flow, such as carbon dioxide relative to a first derivative or rate of change of the carbon dioxide flow as shown in  FIG. 23 , or a function of the pressure data associated with the flow as shown in  FIG. 25 , to determine the respective start or appearance of the alignment signal in the acquired data. It is further appreciated that a similar assessment can be provided by a comparison of the flow data relative to the pressure data as shown in  FIG. 24 . As the flow information is determined from a pressure differential, flow information could be used in place of or in addition to patient flow pressure to determine the desired time-wise alignment of the acquired respiration performance data as both the patient flow and pressure information change concurrently in response to introduction of the alignment signal with the respiration flow stream. 
     By way of example, as shown graphically in  FIG. 25 , when the alignment signal  606  is introduced during exhalation associated with a discrete breath cycle, evidence of the alignment signal  606  is reflected in the assessed pressure and/or flow information as a peak or surge relative to the patient respiration associated pressure and/or flow signal indicated by the trend deviation mirrored about vertical axis P 2 . Similarly, the concentration of carbon dioxide in the exhalation is somewhat constant until introduction of the alignment signal  606  which produces the discontinuity indicated by the trend deviation mirrored about vertical axis G 2 . Said in another, introduction of alignment signal  606  results in a deviation to the pressure signal that begins at P 1 , peaks at P 2 , and the returns to a generally steady state associated with the flow pressure during the discrete portion of the breath cycle. Introduction of the alignment signal  606  is also evidenced in the concentration of carbon dioxide associated with the acquired respiration sample. The alignment signal  606  is represented in the respiration flow sample as a deviation from the somewhat steady state associated with the exhalation sample due to the lower concentration of carbon dioxide associated with the ambient air alignment signal  606  relative to the concentration of carbon dioxide during exhalation. The concentration of carbon dioxide gradually reduces from an initial appearance at G 1  until the concentration achieves a minimum at G 2 , and then recovers to the generally steady state exhalation carbon dioxide concentration. It is appreciated that alignment signal  606  can be provided in a number of forms depending upon where during the respiration cycle the alignment signal is intended to be combined with the respiration flow associated with sensor  34 ,  550 . 
     Referring back to  FIG. 22 , once the breath sample that includes the alignment signal has been acquired and the information associated therewith has been assessed, alignment signal protocol  600  determines the value associated with one or more temporal or timewise offsets  612  between the composition, flow, and/or pressure data. Referring to  FIGS. 22 and 25 , a first offset  614  is determined as the duration between the appearance of the alignment signal in the pressure and/or flow signal P 1  and the appearance of the alignment signal in the carbon dioxide concentration signal G 1 . A second or alternative offset  616  is determined as the duration between the maximum pressure signal P 2  and the peak G 2  associated with the change to the carbon dioxide concentration signal. It is appreciated that one of offsets  614 ,  616  could be sufficient to determine and apply a desired offset to achieve the alignment of the respiration flow and respiration concentration data. It is further appreciated to any number of parameters associated with the flow, pressure, and discrete component concentrations could be used from the breath sample that includes at least a portion of the alignment signal to assess the relative alignment between the acquired flow and concentration data. 
     Referring to  FIGS. 22, 25, and 26 , protocol  606  preferably uses the values associated with first and second offsets  614 ,  616  to assess the accuracy  618  of the calculated offset and to determine  620  and output a desired offset value  622  to controller  60 . Controller  60  utilizes the output offset  622  to generate the time-aligned respiration flow and respiration composition data output  500 . It is appreciated that any of averaging and/or weighting of offsets  614 ,  616  can be implemented to achieve a output offset value  622  that accurately accommodates the discrepancy between the respiration flow and respiration composition data. It is further appreciated that such operation can be conveniently corroborated by conventional experimentational fixturing of system  30  as disclosed further above with respect to the various calibration protocols disclosed herein. 
       FIG. 26  shows approximately 5 seconds of one of the aligned breath cycles shown in  FIG. 21  wherein the temporal or time-wise alignment of the various pressure, flow, and composition trends. As shown in  FIG. 26 , the pressure trend line  626  includes a deviation  628  associated with the introduction of the alignment signal  606  to a respective sensor  34 ,  550 . The trend line associated with the concentration of carbon dioxide  630  also includes a deviation  632  which, when aligned with deviation  628  as indicated by vertical line  640  allow time-wise alignment of the composition and flow information associated with output  500  on a breath-by-breath basis and in a manner that does not require acquisition or assessment of changes to the respiration performance due to patient physiological events. It is appreciated that, if desired, the deviations associated with the effects of alignment signal  606  can be mathematically corrected by subtraction of the effects of the alignment signal from the flow and composition data displayed to a user. As alluded to above, when the physiologic events occur with sufficient intensity, duration, and repeatability, patient external alignment protocol  600  can be turned off or run as an additional confirmation that system  30  achieves the desired temporal alignment of the acquired respiration flow and respiration composition data. It is further appreciated that alignment signal  606  can be provided in any number of sequences including every breath cycle or an intermittent number of breath cycles, such as one every five breath cycles for instance. Accordingly, analyzer  32  is highly versatile, easy to operate, simple to configure for desired operation, and provides an output that allows for quick diagnosis and analysis of patient condition. Operation of analyzer  32  with the external alignment signal methodology disclosed immediately above further improves the accuracy associated with patient respiration and increases the class of users associated with such systems to include those whose physiologic performance may be insufficient to accommodate accurate assessment of the respiration performance as altered by patient physiologic performance. 
     Therefore, according to one embodiment of the invention, a side-stream respiration monitoring system includes an analyzer and a controller that is associated with the analyzer. The analyzer is configured to be fluidly connected to a flow sensor that is constructed to be disposed in a respiration flow path. The controller is configured to initiate delivery of an alignment signal generated by the analyzer to the flow sensor during a portion of at least one breath cycle. The controller is further configured to determine a respiration flow value and at least a portion of a composition of the respiration flow on a breath-by-breath basis and temporally associate in a time-domain the determined respiration flow value and the determined portion of the composition associated with the breath-by-breath basis as a function of information associated with the alignment signal delivered to the flow sensor by the analyzer during the portion of the at least one breath cycle. 
     Another embodiment of the invention useable with one or more of the aspects of the above embodiments discloses a method of monitoring patient respiration performance that includes measuring a patient respiration flow, acquiring a side-stream breath sample, and generating an alignment signal. At least a portion of the alignment signal is acquired with the side-stream breath sample and a flow of the side-stream breath sample and a concentration of oxygen, and a concentration of carbon dioxide in the acquired side-stream breath sample is determined and aligned with one another in a time domain with respect to their occurrence in the acquired side-stream breath sample as a function of information associated with the portion of the alignment signal that is acquired with the side-stream breath sample. 
     Another embodiment useable with one or more of the above embodiments includes a method of manipulating respiration performance data in a side-stream respiration monitoring system. The method includes introducing an alignment signal to a respiration flow passing through a sensor and determining a flow rate and at least a portion of a composition of a respiration flow passing through the sensor and aligning in a time domain the determined flow rate and the determined portion of the composition of the respiration flow from information attributable to the alignment signal. 
     It is further understood that specific details described above are not to be interpreted as limiting the scope of the invention, but are provided merely as a basis for teaching one skilled in the art to variously practice the present invention in any appropriate manner. Changes may be made in the details of the various methods and features described herein, without departing from the spirit of the invention