Categorizing automatically generated physiological data based on industry guidelines

Abstract

Methods and systems for mapping a physiological signal into clinical guideline parameters are disclosed. A physiological signal having a characteristic that may represent an anomaly is received and mapped to a clinical guideline condition space. Probabilities are determined that the mapped signal with which the anomaly may be associated represents a first clinical guideline condition corresponding to a referral indication or a second clinical guideline condition corresponding to an absence of the referral indication. The determined probability is presented and a referral decision is made responsive to the determined probability that the anomaly is associated with the first clinical guideline condition.

1 . A method for mapping a physiological signal into clinical guideline parameters, the method comprising:
 receiving the physiological signal, the physiological signal having a characteristic that may represent an anomaly;   mapping the received physiological signal to a clinical guideline condition space;   determining a probability that the mapped signal with which the anomaly is associated represents one of a first clinical guideline condition corresponding to a referral indication or a second clinical guideline condition corresponding to an absence of the referral indication; and   presenting the determined probability to a user,   
       whereby a referral decision is made responsive to the determined probability that the anomaly is associated with the first clinical guideline condition. 
     
     
         2 . The method according to  claim 1 , wherein the determined probability is presented as a measure of a sensitivity of the determined probability to variations in the physiological signal. 
     
     
         3 . The method according to  claim 2 , wherein the measure of the sensitivity includes a range variance indicative of a confidence measure. 
     
     
         4 . The method according to  claim 1 , wherein the step of presenting the determined probability presents derived features relative to a probability surface including a first region representing the first clinical guideline condition and a second region representing the second guideline condition. 
     
     
         5 . The method according to  claim 4 , wherein the step of presenting the determined probability further presents the derived features relative to at least one predetermined probability threshold between the first region and second region. 
     
     
         6 . A method for mapping a physiological signal into clinical guideline parameters for distinguishing between a first condition corresponding to a referral indication and a second condition corresponding to an absence of the referral indication, the method comprising the steps of:
 receiving the physiological signal, the physiological signal including a characteristic that may contain an anomaly representing a referral indication, the anomaly being within at least one predetermined physiological event of the physiological signal;   computing a normalized energy profile for the at least one predetermined physiological event representative of the anomaly;   mapping the normalized energy profile to a clinical guideline condition space;   determining probabilities that the mapped normalized energy profile is associated with each of the first condition and the second condition; and   presenting the determined probabilities.   
     
     
         7 . The method according to  claim 6 , wherein the physiological signal includes a phonocardiogram signal and the predetermined physiological event includes at least one of a systolic interval and a diastolic interval. 
     
     
         8 . A method for assisting in a referral indication of heart murmurs, the method comprising the steps of:
 receiving an acoustic signal representing heart sounds;   parsing the received acoustic signal into predetermined physiological events including a plurality of systolic intervals and a plurality of diastolic intervals;   computing a first normalized mid-range energy representative of a median systolic interval and a second normalized mid-range energy representative of a median diastolic interval, respectively, the first and second normalized mid-range energies computed from the parsed acoustic signal;   characterizing the median systolic interval based on the first normalized mid-range energy;   determining probabilities relative to a first condition associated with the referral indication and a second condition associated with an absence of the referral indication based on the characterized median systolic interval; and   presenting the first normalized mid-range energy, the second normalized mid-range energy and the determined probabilities,   
       whereby the presented first normalized mid-range energy, the second normalized mid-range energy and the determined probabilities may be used to determine whether a referral is indicated. 
     
     
         9 . The method according to  claim 8 , the method including the steps of:
 characterizing the median diastolic interval based on the second normalized mid-range energy;   determining further probabilities relative to a diastolic murmur condition and a non-diastolic murmur condition; and   the step of presenting further includes presenting the further determined probabilities.   
     
     
         10 . A computer readable carrier including computer program instructions that cause a computer to perform the method according to  claim 8 . 
     
     
         11 . The method according to  claim 8 , wherein the first and second normalized mid-range energies are each between 150 and 600 Hz. 
     
     
         12 . The method according to  claim 8 , wherein the first and second normalized mid-range energies are converted to respective murmur grades and the step of presenting the first and second normalized mid-range energies presents the respective murmur grades. 
     
     
         13 . The method according to  claim 8 , wherein the first condition includes systolic murmurs selected from the group consisting of a holo-systolic murmur, a late-systolic murmur and a mid-systolic murmur equal or greater than a murmur grade 3. 
     
     
         14 . The method according to  claim 8 , wherein the step of characterizing the median systolic interval computes a focal point of energy using a maximum first normalized mid-range energy and systolic interval temporal center of a normalized mid-range energy concentration to generate a model of the median systolic interval. 
     
     
         15 . The method according to  claim 8 , wherein the step of presenting the determined probabilities includes presenting a range variance representing an uncertainty measure. 
     
     
         16 . The method according to  claim 8 , wherein the step of presenting the determined probabilities presents derived features relative to a probability surface, the probability surface including a first region representing the first condition and a second region representing the second condition. 
     
     
         17 . The method according to  claim 16 , wherein the probability surface includes a predetermined threshold between the first region and the second region, the predetermined threshold selected according to a predetermined sensitivity and a predetermined specificity. 
     
     
         18 . The method according to  claim 17 , wherein the probability surface is presented as a function of a duration of the median systolic interval and the first normalized mid-range energy associated with the median systolic interval. 
     
     
         19 . The method according to  claim 8 , the step of computing the first normalized mid-range energy and second normalized mid-range energy includes the steps of: dividing each of the median systolic interval and median diastolic intervals into a plurality of subintervals; and
 calculating the first normalized mid-range energy and second normalized mid-range energy for each of the subintervals of the respective median systolic interval and median diastolic interval.   
     
     
         20 . The method according to  claim 19  wherein:
 the step of dividing each of the median systolic interval and median diastolic intervals into a plurality of subintervals includes the steps of:   subdividing the median systolic interval into at least thirty intervals;   subdividing the median diastolic interval into at least thirty intervals, and   the step of presenting the first and second normalized mid-range energies includes the step of graphically displaying the calculated normalized mid-range energy for each of the plurality of sub-intervals.   
     
     
         21 . The method according to  claim 8 , including the step of detecting heart murmurs using the parsed audio signal and the first normalized mid-range energy and second normalized mid-range energy. 
     
     
         22 . The method according to  claim 21 , the step of detecting heart murmurs calculates Bayesian statistics for the parsed audio signal and the first and second normalized mid-range energies. 
     
     
         23 . A system for mapping a heart sound signal to clinical guideline referral indicators, the system comprising:
 an input terminal for receiving the heart sound signal including systolic intervals and diastolic intervals;   a murmur detector for computing a statistic that a murmur is present from the heart sound signal;   a normalized mid-range energy calculator for computing a normalized mid-range energy profile from the heart sound signal, the normalized mid-range energy profile representative of a median systolic interval of the heart sound signal;   a clinical guideline referral converter for mapping the normalized mid-range energy profile to a first clinical guideline condition associated with a referral indication and a second clinical guideline condition associated with an absence of the referral indication and determining probabilities that the normalized mid-range energy profile is associated with the first or the second clinical guideline conditions; and   a display for displaying the normalized mid-range energy profile, the murmur detection statistic, and the determined probabilities.   
     
     
         24 . The system according to  claim 23 , wherein the normalized mid-range energy calculator computes a further normalized mid-range energy profile from the heart sound signal, the further normalized mid-range energy profile representative of a median diastolic interval of the heart sound signal,
 the system includes a diastolic murmur converter for mapping the further normalized mid-range energy profile to a diastolic murmur condition and a non-diastolic murmur condition and determining further probabilities that the further normalized mid-range energy profile is associated with the diastolic murmur condition or the non-diastolic murmur condition, and   the display displays the further normalized mid-range energy profile and the determined further probabilities.   
     
     
         25 . A display for a clinical device, the display comprising:
 a first normalized mid-range energy profile associated with a median systolic interval of a heart sound signal;   a second normalized mid-range energy profile associated with a median diastolic interval of the heart sound signal;   at least one probability indicator which indicates that the median systolic interval represents a first clinical guideline condition associated with a referral indication and a second clinical guideline condition associated with an absence of the referral indication; and   murmur detection indicators indicating the detection of murmurs in the heart sound signal.   
     
     
         26 . The display according to  claim 25 , wherein the display includes a representation of the heart sound signal and the murmur detection indicator is presented relative to the representation of the heart sound signal. 
     
     
         27 . The display according to  claim 25 , wherein the display includes hemodynamic parameter information. 
     
     
         28 . The display according to  claim 25 , wherein the display includes auscultation recording information including at least one of a predetermined recording location and a predetermined posture. 
     
     
         29 . The display according to  claim 25 , wherein the first and second normalized mid-range energy profiles are presented as respective bar graphs. 
     
     
         30 . The display according to  claim 25 , wherein the at least one probability indicator includes a range variance representing an uncertainty measure. 
     
     
         31 . The display according to  claim 25 , wherein the display includes a further probability indicator which indicates that the median diastolic interval represents a diastolic murmur condition and a non-diastolic murmur condition. 
     
     
         32 . The display according to  claim 25 , wherein the at least one probability indicator includes a probability surface configured for the median systolic interval, the probability surface including at least one probability threshold between predetermined regions representing the first clinical guideline condition and second clinical guideline conditions, respectively. 
     
     
         33 . The display according to  claim 32 , wherein the probability surface is presented as a function of a duration of the median systolic interval and a first normalized mid-range energy from the first normalized mid-range energy profile. 
     
     
         34 . The display according to  claim 33 , wherein the at least one probability indicator includes a focal center of energy intensity indicator representing a temporal and energy position of the median systolic interval relative to the probability surface.