Apparatus and method for non-invasive diagnosing of coronary artery disease

Abstract

A non-invasive diagnostic tool and method for detecting an obstruction in a coronary artery, the diagnostic tool including a signal processor adapted to receive signals corresponding to a heart beat from a plurality of acoustic sensors attached to the chest of a patient. The signal processor is programmed to identify a diastolic portion of the signals for a plurality of heartbeats and conduct a wavelet transform analysis on the diastolic signals for determining the existence of, as well as the severity and the location of, an obstruction in a coronary artery of the patient.

1 . A method for monitoring a severity of coronary artery disease in a patient, the method comprising: 
 receiving, with one or more acoustic sensors, acoustic energy emitted from a coronary artery in the patient;    producing one or more digital signals in response to the acoustic energy received by the one or more acoustic sensors;    performing wavelet transforms on portions of the one or more digital signals, the wavelet transforms comprising wavelet coefficients; and    calculating a diagnostic number from the wavelet coefficients;    wherein the diagnostic number provides information corresponding to a degree of blockage in the coronary artery of the patient.    
   
   
       2 . The method of  claim 1 , wherein the portions of the digital signals comprise at least a portion of a diastolic portion of at least one heartbeat.  
   
   
       3 . The method of  claim 1 , further comprising outputting the diagnostic number.  
   
   
       4 . The method of  claim 1 , wherein the act of outputting further comprises displaying the diagnostic number with a user interface.  
   
   
       5 . The method of  claim 4 , where the user interface is a real time user interface.  
   
   
       6 . The method of  claim 1 , further comprising attaching the one or more acoustic sensors to the patient.  
   
   
       7 . The method of  claim 6 , wherein the one or more sensors are attached to the chest of the patient.  
   
   
       8 . The method of  claim 6 , wherein the act of calculating a diagnostic number is performed while the one or more sensors are attached to the patient.  
   
   
       9 . The method of  claim 8 , wherein the act of calculating a diagnostic number is performed in real time.  
   
   
       10 . The method of  claim 6 , further comprising removing the one or more acoustic sensors from the patient.  
   
   
       11 . The method of  claim 1 , wherein the act of calculating a diagnostic number further comprises: 
 calculating a variance of the wavelet coefficients with respect to a frequency scale parameter; and    calculating the diagnostic number from a slope of the variance with respect to the frequency scale parameter    
   
   
       12 . The method of  claim 11 , wherein the slope is a logarithmic slope.  
   
   
       13 . The method of  claim 11 , wherein the slope is calculated from a regression analysis.  
   
   
       14 . The method of  claim 11 , wherein the frequency scale parameter is in a range from about 62 Hz to about 2 kHz.  
   
   
       15 . The method of  claim 1 , further comprising using an R-wave sensor.  
   
   
       16 . The method of  claim 15 , wherein the R-wave sensor is used for calibration.  
   
   
       17 . The method of  claim 1 , further comprising storing the digital signals, the wavelet coefficients, or the diagnostic number in a storage medium.  
   
   
       18 . The method of  claim 17 , wherein the storage medium comprises a flash memory device.  
   
   
       19 . The method of  claim 1 , wherein the one or more acoustic sensors comprise four acoustic sensors.  
   
   
       20 . The method of  claim 1 , wherein the diagnostic number is compared with results from an angiogram performed on the patient.