METHOD AND SYSTEM FOR ANALYZING BODY SOUNDS

• US 20100087746A1
• Filed: 12/11/2007
• Published: 04/08/2010
• Est. Priority Date: 12/11/2006
• Status: Abandoned Application

• Current Assignee: Deep Breeze, Ltd.
• Original Assignee: Deep Breeze, Ltd.
• Inventors: Papyan, Surik, Radzievsky, Naira
• Application Number:
  US12/448,135
• Publication Number:
  US 20100087746A1
• Time in Patent Office: Days
• US Class Current: 600/528
• CPC Class Codes: A61B 7/003 Detecting lung or respiration noise
• CPC Class Codes: A61B 7/026 comprising more than one sound collector
• CPC Class Codes: A61B 7/04 Electric stethoscopes microphones, acoustic transducers therefor H04R

Abstract

The invention provides a method and system for analyzing body sounds from one or more body organs. An array of transducers is fixed to the body surface over the organs from which body sounds are to be recorded. Analysis of the recorded sound signals includes dividing each signal into one or more time intervals and calculating an average of the signal in each time interval. A difference signal is calculated for each interval, where the difference signal is the difference of the recorded signal in the interval and the interval average. An energy assessment signal is then calculated in each interval using the difference signal. In an embodiment, the energy assessment signal is a standard deviation signal. The subject matter may be used to record and analyze cardiovascular sounds for diagnosing abnormal cardiovascular function, or for calculating an ejection fraction.

Claims

1-67. -67. (canceled)

68. A system for analyzing body sounds from one or more body organs, comprising:

(a) an integer N of transducers, each transducer configured to be fixed on a region of a surface of the individual, a transducer i being fixed at a location x_i and generating a signal S(x_i,t) indicative of pressure waves at the location x_i;

for i=1 to N; and

(b) a processor receiving the signals S(x_i,t) configured, for each of one or more of the signals S(x_i,t) and for each of one or more time intervals k, to;

(i) calculate an average S_k of the signal S(x_i,t) in the interval k; and

(ii) for one or more times t_j in the interval k, calculate a difference S(x_i,t_j)−

S_k, and

(iii) calculate an energy assessment signal in a calculation involving the one or more differences S(x_i,t_j)−

S_k

69. The system according to claim 68, wherein the processor is configured to filter from one or more of the signals S(x_i,t) to remove one or more components of the signals S(x_i,t) not arising from the body organ or organs.

70. The system according to claim 68, wherein the calculation of the energy assessment signal involves calculation of a standard deviation signal from one or more of the signals S(x_i,t).

71. The system according to claim 70, wherein the standard deviation signal is obtained from the signal S(x_i,t) or from a signal derived from the signal S(x_i,t) in a process comprising:

dividing the filtered signal into time intervals by a time window; and

calculating the standard deviation σ

(k) for each interval using the algebraic expression

$\mathrm{\sigma <br><br>}<br><br>\left(k\right)={\left(\frac{1}{n}<br><br>\underset{j=1}{\overset{n}{\sum <br><br>}}<br><br>{\left(S<br><br>\left(x_i,t_j\right)-{\stackrel{\_}{S}}_k\right)}^2\right)}^{\frac{1}{2}}$

wherein k is an interval number, t_j is a time sample in the interval, n is the number of samples in the interval, and S_k is the average value of the signal in the interval;

${\stackrel{\_}{S}}_k=\frac{1}{n}<br><br>\underset{j=1}{\overset{n}{\sum <br><br>}}<br><br>S<br><br>\left(x_i,t_j\right).$

72. The system according to claim 70, wherein the energy assessment signal is calculated as a sum of squares of components of the standard deviation signals, before or after normalization, before or after median filtering, and before or after smoothing.

73. The system according to claim 68, wherein the processor is further configured to interpolate the plurality of energy assessment signals to obtain energy assessment signals at one or more locations between transducers in the transducer array.

74. The system according to claim 68, configured to analyze cardiovascular sounds.

75. The system according or claim 74, wherein the processor is further configured to identify one or more of events E1, E2, E3 and E4 of a cardiac cycle.

76. The system according to claim 75, wherein the processor is further configured to identify one or more transducers overlying a heart apex.

77. The system according to claim 76, wherein the processor is further configured to compare any one or more of the acoustic energies at any one or more of the cardiac cycle events E1, E2, E3, and E4 to a predetermined threshold.

78. The system according to claim 77, wherein the processor is further configured to make a diagnosis of abnormal heart function based upon any one or more of the comparisons.

79. The system according to claim 68, wherein the processor is further configured to calculate an ejection fraction from the energy assessment signal.

80. The system according to claim 79, wherein the ejection fraction is calculated in a calculation involving a volume ratio

$\frac{{\mathrm{Volume}}_{(E}}{}$



3 , E 



4 ) Volume ( E 



1 , E 



2 ) ,

wherein Volume_(E3,E4) is an acoustic energy at E3 or E4, and Volume_(E1,E2) is an acoustic energy at E1 or E2.

81. A method for analyzing body sounds from one or more body organs, comprising:

(a) affixing an integer N of transducers on a region of a surface of the individual, a transducer i being fixed at a location x_i, each transducer and generating a signal S(x_i,t) indicative of pressure waves at the location x_i;

for i=1 to N; and

(b) for each of one or more of the signals S(x_i,t) and for each of one or more time intervals k;

(i) calculating an average S_k of the signal S(x_i,t) in the interval k; and

(ii) for one or more times t_j in the interval k, calculating a difference S(x_i,t_j)−

S_k; and

(iii) calculating an energy assessment signal in a calculation involving the one or more differences S(x_i,t_j)−

S_k.

82. The method according to claim 81, further comprising filtering one or more of the signals S(x_i,t) to remove one or more components of the signals S(x_i,t) not arising from the body organ or organs.

83. The method according to claim 81, wherein the calculation of the energy assessment signal involves calculation of a standard deviation signal from one or more of the signals S(x_i,t).

84. The method according to claim 83, wherein the standard deviation signal is obtained from the signal S(x_i,t) or from a signal derived from the signal S(x_i,t) in a process comprising dividing the filtered signal into time intervals by a time window and calculating the standard deviation σ

(k) for each interval using the algebraic expression

$\mathrm{\sigma <br><br>}<br><br>\left(k\right)={\left(\frac{1}{n}<br><br>\underset{j=1}{\overset{n}{\sum <br><br>}}<br><br>{\left(S<br><br>\left(x_i,t_j\right)-{\stackrel{\_}{S}}_k\right)}^2\right)}^{\frac{1}{2}}$

wherein k is an interval number, t_j is a time sample in the interval, n is the number of samples in the interval, and S_k is the average value of the signal in the interval;

${\stackrel{\_}{S}}_k=\frac{1}{n}<br><br>\underset{j=1}{\overset{n}{\sum <br><br>}}<br><br>S<br><br>\left(x_i,t_j\right).$

85. The method according to claim 81, wherein the energy assessment signal is calculated as a sum of squares of components of the standard deviation signals, before or after normalization, before or after median filtering, and before or after smoothing.

86. The method according to claim 81, further comprising interpolating the plurality of energy assessment signals to obtain energy assessment signals at one or more locations between transducers in the transducer array.

87. The method according to claim 81, wherein the body sounds are cardiovascular sounds.

88. The method according to claim 87, further comprising identifying one or more transducers overlying a heart apex.

89. The method according to claim 88, further comprising comparing any one or more of the acoustic energies at any one or more of the cardiac cycle events E1, E2, E3, and E4 to a predetermined threshold.

90. The method according to claim 89, further comprising making a diagnosis of abnormal heart function based upon any one or more of the comparisons.

91. The method according to claim 81, further comprising calculating an ejection fraction from the energy assessment signal.

92. The method according to claim 91 wherein the ejection fraction is calculated in a calculation involving a volume ratio

$\frac{{\mathrm{Volume}}_{(E}}{}$



3 , E 



4 ) Volume ( E 



1 , E 



2 ) ,

wherein Volume_(E3,E4) is an acoustic energy at E3 or E4, and Volume_(E1,E2) is an acoustic energy at E1 or E2.

93. A computer program comprising computer program code means for performing all the steps of claim 81 when said program is run on a computer.

94. A computer program as claimed in claim 93, embodied on a computer readable medium.