Multi parametric classification of cardiovascular sounds

Abstract

The present application relates to a method for classifying a cardiovascular sound recorded from a living subject. The method comprises the step of extracting at least two signal parameters ( 309 ) from said cardiovascular sound, said at least two signal parameters characterizes at least two different properties of at least a part of said cardiovascular sound. The method further comprises the step of classifying said cardiovascular sound using said at least two signal parameters in a multivariate classification method ( 310 ). Furthermore, the application relates to a system, stethoscope and server for classifying a cardiovascular sound recorded from a living subject, where the above-described method has been implemented.

1 . A method for classifying a cardiovascular sound recorded from a living subject, said method comprises the steps of:
 extracting at least two signal parameters from said cardiovascular sound, said at least two signal parameters characterizes at least two different properties of at least a part of said cardiovascular sound,   classifying said cardiovascular sound using said at least two signal parameters in a multivariate classification method.   
   
   
       2 . A method according to  claim 1  characterized in that at least one of said at least two signal parameters is a frequency parameter describing a property in the frequency domain of at least a part of said cardiovascular sound. 
   
   
       3 . A method according to  claim 1  characterized in that at least one of said at least two signal parameters describing a property in the time domain of at least a part of said cardiovascular sound. 
   
   
       4 . A method according to  claim 2  characterized in that at least one of said frequency parameters is a frequency level parameter describing a frequency level property of at least a part of said cardiovascular sound. 
   
   
       5 . A method according to  claim 2  characterized in that at least one of said at least two signal parameters is a frequency bandwidth parameter describing a frequency bandwidth property of at least a part of said cardiovascular sound. 
   
   
       6 . A method according to  claim 4  characterized in that at least one of said frequency level properties characterizes the most powerful frequency component of at least a part of said cardiovascular sound. 
   
   
       7 . A method according to  claim 5  characterized in that at least one of said frequency bandwidth properties characterizes the bandwidth of the most powerful frequency component of at least a part of said cardiovascular sound. 
   
   
       8 . A method according to  claim 3  characterized in that at least one of said time parameters is a property characterizing the mobility of at least a part of said cardiovascular sound. 
   
   
       9 . A method according to  claim 1  characterized in that said method further comprises the step of dividing said cardiovascular sound into at least one sub-segment and at least one of said signal parameters is extracted from said at least one sub-segment. 
   
   
       10 . A method according to  claim 1  characterized in that said method further comprises the step of modelling at least a part of said cardiovascular sound and at least one of said signal parameters is extracted from said model. 
   
   
       11 . A method according to  claim 1  characterized in that said multivariate classification method is a discriminant function. 
   
   
       12 . A system for classifying a cardiovascular sound recorded from a living subject, said system comprises:
 processing means for extracting at least two signal parameters from said cardiovascular sound, said at least two signal parameters characterizes at least two different properties of at least a part of said cardiovascular sound,   processing means for classifying said cardiovascular sound using said at least two signal parameters using a multivariate classification method.   
   
   
       13 . A system according to  claim 12  characterized in that said processing means for extracting at least two signal parameters from said cardiovascular sound is adapted to extract at least one frequency parameter describing a property in the frequency domain of at least a part of said cardiovascular sound. 
   
   
       14 . A system according to  claim 12  characterized in that said processing means for extracting at least two signal parameters from said cardiovascular sound is adapted to extract at least one time parameter describing a property in the time domain of at least a part of said cardiovascular sound. 
   
   
       15 . A system according to  claim 13  characterized in that said processing means adapted to extract at least one of said frequency parameters are further adapted to extract at least one frequency level parameter describing a frequency level property of at least a part of said cardiovascular sound. 
   
   
       16 . A system according to  claim 13  characterized in that said processing means adapted to extract at least one frequency parameter are further adapted to extract at least one frequency bandwidth parameter describing a frequency bandwidth property of at least a part of said cardiovascular sound. 
   
   
       17 . A system according to  claim 13  characterized in that said processing means adapted to extract at least one frequency level property are further adapted to extract the most powerful frequency component of at least a part of said cardiovascular sound. 
   
   
       18 . A system according to  claim 13  characterized in that said processing means adapted to extract at least one of said frequency bandwidth properties are further adapted to extract the bandwidth of the most powerful frequency component of at least a part of said cardiovascular sound. 
   
   
       19 . A system according to  claim 14  characterized in that said processing means for extracting at least one time parameters are further adapted to extract the mobility of at least a part of said cardiovascular sound. 
   
   
       20 . A system according to  claim 12  characterized in that said system further comprises processing means for dividing said cardiovascular sound into at least one sub-segment and at least one of said signal parameters is extracted from said at least one sub-segment. 
   
   
       21 . A system according to  claim 12  characterized in that said system further comprises processing means for modelling at least a part of said cardiovascular sound and in that said processing means for extracting at least two signal parameters from said cardiovascular sound are further adapted to extract at least one of said parameters from said model. 
   
   
       22 . A system according to  claim 12  characterized in that said multivariate classification method used by said processing means for classification of said cardiovascular sound is a discriminant function. 
   
   
       23 . A computer-readable medium having stored therein instructions for causing a processing unit to execute a method according to  claim 1 . 
   
   
       24 . A stethoscope comprising:
 recording means adapted to record a cardiovascular sound from a living subject,   storing means adapted to store said recorded cardiovascular sound,   a computer-readable medium and a processing unit, said computer-readable medium having stored therein instructions for causing said processing unit to execute a method according to  claim 1  and thereby classify said recorded cardiovascular sound.   
   
   
       25 . A server device connected to a communication network comprising:
 receiving means adapted to receive a cardiovascular sound recorded from a living subject through said communication network,   storing means adapted to store said received cardiovascular sound,   a computer-readable medium and a processing unit, said computer-readable medium having stored therein instructions for causing said processing unit to execute a method according to  claim 1  and thereby classify said received cardiovascular sound.   
   
   
       26 . A server device according to  claim 25  characterized in that said receiving means are further adapted to receive said cardiovascular sound from a client connected to said communication network. 
   
   
       27 . A server device according to  claim 25  characterized in that said server device further comprises means for sending said classification of said cardiovascular sound to at least one client unit connected to said communication network.