Patent Document

CROSS-REFERENCE TO RELATED APPLICATION 
       [0001]    This non-provisional application claims priority under 35 U.S.C. §119(a) on Patent Application No(s). 100147510 filed in Taiwan, R.O.C. on Dec. 20, 2011, the entire contents of which are hereby incorporated by reference. 
       FIELD OF TECHNOLOGY 
       [0002]    The present invention relates to a system and method for evaluating cardiovascular performance in real time and characterized by the conversion of a surface potential into multi-channels, the reconstruction of electrocardiographic signals (ECG signals) with a reconstruction algorithm, and the calculation of the degree of discreteness of the ECG signals with a parameter computation and assessment algorithm. 
       BACKGROUND 
       [0003]    Among cardiovascular diseases (CVD), coronary artery disease (CAD) is regarded as the main cause of a sudden death. The pathological changes caused by coronary artery disease (CAD) include stenosis and even occlusion of coronary arteries for supplying oxygen and nutrients to the heart, thereby damaging cardiac tissues. Depending on the degree of severity, coronary artery disease (CAD) has different manifestations, namely angina, myocardial infarction, and sudden cardiac death. Angina is chest pain due to ischemia (a lack of blood, thus a lack of oxygen supply) of the heart muscle and typically occurs when the weather is cold or when the patient is mentally or physically overburdened or has an overstretched stomach. Myocardial infarction is worse than angina, because the underlying pathological change typical of myocardial infarction is irreversible damage of the heart muscle. Myocardial infarction ends up in a heart failure, when it is severe. In a worst-case scenario, the consequence of myocardial infarction is a sudden cardiac death, wherein the victim goes into shock and dies as soon as arrhythmia halts the heart and decreases the cardiac output greatly. Hence, coronary artery disease (CAD) is dubbed an invisible killer because of its symptomless insidious course. Coronary artery disease (CAD) is seldom diagnosed with a static electrocardiogram (static ECG), as it starts to alert a patient only when cardiac hypoxia happens to the patient. 
         [0004]    At present, diagnosis tools in wide use for diagnosing coronary artery disease (CAD) include treadmill ECG, Thallium scan, and CT-angio. However, the application of the aforesaid diagnosis tools is limited by size, costs, and methodology of measurement, regardless of whether the diagnosis tools are used at hospital or at home. In this regard, the prognosis of coronary artery disease (CAD) is often evaluated by means of conventional ECG signals, albeit with a drawback—providing just 12 channels which are restricted to longitudinal cross-sections and transverse cross-sections of the heart. Although the equipment required for providing the 12-channel ECG signals is simple and easy to operate, its spatial resolution is inadequate, not to mention that it provides a limited amount of information pertaining to the analysis and identification of related symptoms, thereby restricting its application and analysis. Furthermore, although high-resolution magnetocardiography (MCG) provides sufficient spatial information, it is not in wide use because of its high prices and large size. 
       SUMMARY 
       [0005]    It is an objective of the present invention to increase spatial resolution of ECG signals, cut device-related costs, and downsize related devices by measuring multi-channel electrocardiographic signals (ECG signals) and reconstructing multi-dimensional mapping and by making reference to the results of research on the application of magnetocardiography (MCG) in coronary artery disease (CAD). 
         [0006]    Another objective of the present invention is to develop a system for evaluating cardiovascular performance in real time and characterized by conversion of a surface potential into multi-channels, wherein the system operates in conjunction with an algorithm that proves effective in performing MCG-based verification. 
         [0007]    Yet another objective of the present invention is to develop a system for evaluating cardiovascular performance in real time and characterized by conversion of a surface potential into multi-channels, wherein the system is not only portable and free of radioactivity, but also enables real-time analysis and early prediction. 
         [0008]    In order to achieve the above and other objectives, the first aspect of the present invention provides a system for evaluating cardiovascular performance in real time and characterized by conversion of a surface potential into multi-channels. The system comprises: an electrocardiographic signal measuring unit comprising at least one channel located at different spatial positions, the electrocardiographic signal measuring unit recording electrocardiographic signals (ECG signals) measured with the channels, the ECG signals each comprising a P wave, a Q wave, a R wave, a S wave, and a T wave; a reconstruction unit electrically connected to the electrocardiographic signal measuring unit, the reconstruction unit having a reconstruction algorithm for calculating eigenvectors of the ECG signals and using the eigenvectors as a base for calculating an eigenvalue matrix, the reconstruction unit calculating at least one reconstructed ECG signal at other different spatial positions with the eigenvalue matrix and the ECG signals of the channels, the at least one reconstructed ECG signal comprising a reconstructed P wave, a reconstructed Q wave, a reconstructed R wave, a reconstructed S wave, and a reconstructed T wave; and a parameter computation and assessment unit electrically connected to the reconstruction unit and having a parameter computation and assessment algorithm, wherein the parameter computation and assessment unit receives the ECG signals and the at least one reconstructed ECG signal, calculates an interval from a starting point of the Q wave to an ending point of the T wave of the ECG signals, calculates variation in a reconstruction interval from a starting point of the reconstructed Q wave to an ending point of the reconstructed T wave of the at least one reconstructed ECG signal against time at different spatial positions, and evaluates the degree of discreteness of the ECG signals and the at least one reconstructed ECG signal with the parameter computation and assessment algorithm. 
         [0009]    The second aspect of the present invention provides a method for evaluating cardiovascular performance in real time and characterized by conversion of a surface potential into multi-channels. The method comprising the steps of: measuring, by the electrocardiographic signal measuring unit, electrocardiographic signals (ECG signals) at different spatial positions with at least one channel, the ECG signals each comprising a P wave, a Q wave, a R wave, a S wave, and a T wave; calculating, by a reconstruction unit, eigenvectors of the ECG signals with a reconstruction algorithm, an eigenvalue matrix with the eigenvectors being used as a base, and at least one reconstructed ECG signal at other different spatial positions with the eigenvalue matrix and the ECG signals of the channels, the at least one reconstructed ECG signal comprising a reconstructed P wave, a reconstructed Q wave, a reconstructed R wave, a reconstructed S wave, and a reconstructed T wave; and receiving the ECG signals and the at least one reconstructed ECG signal by a parameter computation and assessment unit, calculating an interval from a starting point of the Q wave to an ending point of the T wave of the ECG signals, calculating variation in a reconstruction interval from a starting point of a reconstructed Q wave to an ending point of a reconstructed T wave of the at least one reconstructed ECG signal against time at different spatial positions, and evaluating a degree of discreteness of the at least one reconstructed ECG signal and the ECG signals with the parameter computation and assessment algorithm. 
     
    
     
       BRIEF DESCRIPTION 
         [0010]      FIG. 1  is a block diagram of a system according to an embodiment of the present invention; 
           [0011]      FIG. 2  is a schematic view of the positions of multi-channel electrodes according to an embodiment of the present invention; 
           [0012]      FIG. 3A  is an electrocardiogram (ECG) at a spatial position and with a full cycle according to an embodiment of the present invention; 
           [0013]      FIG. 3B  is an electrocardiogram (ECG) at multiple spatial positions with a full cycle according to an embodiment of the present invention; 
           [0014]      FIG. 4  is a schematic view of a process flow of a reconstruction algorithm according to an embodiment of the present invention; 
           [0015]      FIG. 5A  is a schematic view of distribution of QTc at a spatial position under normal condition according to an embodiment of the present invention; 
           [0016]      FIG. 5B  is a schematic view of distribution of QTc at a spatial position under abnormal condition according to an embodiment of the present invention; and 
           [0017]      FIG. 6  is a flow chart of a method according to an embodiment of the present invention. 
       
    
    
     DETAILED DESCRIPTION 
       [0018]    Referring to  FIG. 1 , there is shown a block diagram of a system  100  for evaluating cardiovascular performance in real time according to the first aspect of the present invention. As shown in  FIG. 1 , the system  100  for evaluating cardiovascular performance in real time comprises an electrocardiographic signal measuring unit  110 , a reconstruction unit  120 , and a parameter computation and assessment unit  130 . As shown in  FIG. 1 , for an illustrative purpose, the electrocardiographic signal measuring unit  110  comprises three channels  1182 ,  1184 ,  1186 . The quantity of the channels is subject to changes. For example, the electrocardiographic signal measuring unit  110  can comprise 12 channels. 
         [0019]    Referring to  FIG. 2 , there is shown a schematic view of the positions of multi-channel electrodes according to an embodiment of the present invention. As shown in the diagram, electrodes VR, VL, and VF measure electrocardiographic signals (ECG signals) which originates from a plurality of spatial positions on the surface of a human body  200 . Hence, the electrodes VR, VL, and VF are located at different spatial positions, respectively. The channels  1182 ,  1184 ,  1186  capture ECG signals S 1 , S 2  and S 3  from different spatial positions on the surface of the human body  200  by means of the electrodes VR, VL, and VF, respectively. 
         [0020]    Referring to  FIG. 1 ,  FIG. 2 ,  FIG. 3A  and  FIG. 3B , an electrocardiogram (ECG) at a spatial position and with a full cycle according to an embodiment of the present invention is shown in  FIG. 3A , and an electrocardiogram (ECG) at multiple spatial positions with a full cycle according to an embodiment of the present invention is shown in  FIG. 3B . As shown in the diagrams, the electrocardiographic signal measuring unit  110  retrieves and records the ECG signals S 1 , S 2  and S 3  measured by channels  1182 ,  1184 ,  1186 . As shown in the diagrams, the ECG signals each comprise P wave, Q wave, R wave, S wave, and T wave. The reconstruction unit  120  is electrically connected between the electrocardiographic signal measuring unit  110  and the parameter computation and assessment unit  130 . The electrocardiographic signal measuring unit  110  comprises a signal buffer  112 , an amplifier  113 , and a filter  114 . The amplifier  113  is electrically connected between the signal buffer  112  and the filter  114 . The signal buffer  112  is electrically connected to the channels  1182 ,  1184 ,  1186  for receiving the ECG signals S 1 , S 2  and S 3  retrieved by the electrodes VR, VL and VF (as shown in  FIG. 2 ) at different spatial positions, respectively. 
         [0021]    The signal buffer  112  protects the electrocardiographic signal measuring unit  110  against electrical surges. The signal buffer  112  provides an input impedance that is high enough to forward weak ECG signals measured on the human body surface to the amplifier  113 . After receiving the ECG signals, the amplifier  113  amplifies them. The filter  114  eliminates protects the ECG signals by preventing baseline shift, reducing high-frequency noise, and blocking interference from power signals. The filter  114  operates at a band-pass frequency of 0.5 Hz˜150 Hz and a band-stop frequency of 60 Hz. The electrocardiographic signal measuring unit  110  further comprises an analog-to-digital converter  115 . The analog-to-digital converter  115  is electrically connected to the filter  114 . The ECG signals are filtered by the filter  114  and then sent to the analog-to-digital converter  115  for conversion into digital signals for use in analysis and computation performed by the reconstruction unit  120  subsequently. 
         [0022]    Referring to  FIG. 1  and  FIG. 4 , a schematic view of a process flow of a reconstruction algorithm according to an embodiment of the present invention is shown in  FIG. 4 . As shown in the diagrams, the reconstruction unit  120  comprises a reconstruction algorithm for calculating orthogonal eigenvectors φ of measured multi-channel ECG signals by principal component analysis (PCA), as shown in  FIG. 4(   a ). With PCA, the ECG signals measured are expressed linearly in terms of variables independent of each other as follows: 
         [0000]        X=k   1 φ 1   +k   2 φ 2   +k   3 φ 3   + . . . +k   n φ n  
 
         [0023]    where X denotes an original signal, φ denotes variables independent of each other, and k denote a variable weight coefficient for combining the variables linearly so as to express the original signal. 
         [0024]    All the eigenvectors in a related matrix can be treated as a base to form matrix Φ, where column vector φ i  is known as eigenvector. 
         [0000]    
       
         
           
             
               Φ 
               = 
               
                 [ 
                 
                   
                     
                        
                     
                     
                        
                     
                     
                       
                           
                       
                     
                     
                        
                     
                   
                   
                     
                       
                         ϕ 
                         1 
                       
                     
                     
                       
                         ϕ 
                         2 
                       
                     
                     
                       … 
                     
                     
                       
                         ϕ 
                         L 
                       
                     
                   
                   
                     
                        
                     
                     
                        
                     
                     
                       
                           
                       
                     
                     
                        
                     
                   
                 
                 ] 
               
             
             ; 
           
         
       
       
         
           
             
               
                 ϕ 
                 i 
               
               = 
               
                 [ 
                 
                   
                     
                       
                         
                           ϕ 
                           i 
                         
                          
                         
                           [ 
                           0 
                           ] 
                         
                       
                     
                   
                   
                     
                       
                         
                           ϕ 
                           i 
                         
                          
                         
                           [ 
                           1 
                           ] 
                         
                       
                     
                   
                   
                     
                       ⋮ 
                     
                   
                   
                     
                       
                         
                           ϕ 
                           i 
                         
                          
                         
                           [ 
                           
                             L 
                             - 
                             1 
                           
                           ] 
                         
                       
                     
                   
                 
                 ] 
               
             
             , 
             
               
 
             
              
             
               i 
               = 
               1 
             
             , 
             
               2 
                
               
                   
               
                
               … 
             
              
             
                 
             
             , 
             L 
           
         
       
       
         
           
             X 
             = 
             
               
                 
                   [ 
                   
                     
                       
                          
                       
                       
                          
                       
                       
                         
                             
                         
                       
                       
                          
                       
                     
                     
                       
                         
                           ϕ 
                           1 
                         
                       
                       
                         
                           ϕ 
                           2 
                         
                       
                       
                         … 
                       
                       
                         
                           ϕ 
                           L 
                         
                       
                     
                     
                       
                          
                       
                       
                          
                       
                       
                         
                             
                         
                       
                       
                          
                       
                     
                   
                   ] 
                 
                  
                 
                   [ 
                   
                     
                       
                         
                           k 
                           1 
                         
                       
                     
                     
                       
                         
                           k 
                           2 
                         
                       
                     
                     
                       
                         ⋮ 
                       
                     
                     
                       
                         
                           k 
                           L 
                         
                       
                     
                   
                   ] 
                 
               
               = 
               
                 Φ 
                  
                 
                     
                 
                  
                 k 
               
             
           
         
       
     
         [0025]    Afterward, eigenvector ψ i  is treated as a base for calculating an eigenvalue matrix k corresponding to channels at other different spatial positions, as shown in  FIG. 4(   b ). Hence, k denotes a matrix that consists of related coefficients. Multi-channel ECG signals are treated as input signals and then decomposed by PCA into a polynomial, where every term is created by multiplying a PCA-enabled base with a coefficient related thereto. Then, with PCA, eigenvector significance is determined by the eigenvalue to select the most important eigenvector to function as the reconstruction base for reconstructing multi-channel ECG signals. 
         [0000]    
       
         
           
             
               
                 S 
                 R 
               
               = 
               
                 
                   S 
                   T 
                 
                 * 
                 k 
               
             
             , 
             
               
 
             
              
             
               S 
               = 
               
                 [ 
                 
                   
                     
                        
                     
                     
                        
                     
                     
                       
                           
                       
                     
                     
                        
                     
                   
                   
                     
                       
                         S 
                         1 
                       
                     
                     
                       
                         S 
                         2 
                       
                     
                     
                       … 
                     
                     
                       
                         S 
                         k 
                       
                     
                   
                   
                     
                        
                     
                     
                        
                     
                     
                       
                           
                       
                     
                     
                        
                     
                   
                 
                 ] 
               
             
             , 
             
               
 
             
              
             
               
                 S 
                 i 
               
               ∈ 
               
                 ϕ 
                 i 
               
             
           
         
       
     
         [0026]    Finally, the reconstruction unit  120  calculates a reconstructed ECG signal S R  at the other different spatial positions with the eigenvalue matrix k and the ECG signals S 1 , S 2  and S 3  of channels  1182 ,  1184 ,  1186  as shown in  FIG. 4(   c ). The reconstructed ECG signal S R  comprises a reconstructed P wave, a reconstructed Q wave, a reconstructed R wave, a reconstructed S wave, and a reconstructed T wave. The parameter computation and assessment unit  130  comprises a parameter computation and assessment algorithm. Due to differences in transmission direction and intrinsic impedance of the human body, different vector projections take place at the spatial positions of the channels in the course of the measurement of the ECG signals; as a result, periodic signals of different waveforms are captured. For example, a conventional 12-channel ECG is performed with six limb channels and six thoracic channels for providing signals specific to longitudinal cross-sections and transverse cross-sections of the heart. 
         [0027]    The reconstruction algorithm of the reconstruction unit  120  is for use in calculating the eigenvalue matrix and the eigenvalues by means of the ECG signals measured with the electrodes VR, VL and VF. The product of the multiplication of the amplitude of the ECG signals of the channels and the eigenvalue matrix is used by the reconstruction algorithm of the reconstruction unit  120  to calculate indirectly a reconstructed ECG signal at the other different spatial positions, so as to overcome spatial resolution inadequacy and the lack of information required for analyzing and identifying signs and symptoms of diseases. 
         [0028]    The parameter computation and assessment unit  130  comprises a parameter computation and assessment algorithm. Given an evaluation parameter SI QTc , the parameter computation and assessment algorithm for the parameter SI QTc  is: 
         [0000]    
       
         
           
             
               
                 SI 
                 QTc 
               
               = 
               
                 
                   ( 
                   
                     1 
                     / 
                     S 
                   
                   ) 
                 
                  
                 
                   
                     ∑ 
                     S 
                   
                    
                   
                       
                   
                    
                   
                     { 
                     
                       
                         ( 
                         
                           1 
                           / 
                           n 
                         
                         ) 
                       
                        
                       
                         
                           ∑ 
                           n 
                         
                          
                         
                             
                         
                          
                         
                            
                           
                             
                               
                                 ( 
                                 
                                   QT 
                                   c 
                                 
                                 ) 
                               
                               k 
                             
                             - 
                             
                               
                                 ( 
                                 
                                   QT 
                                   c 
                                 
                                 ) 
                               
                               n 
                             
                           
                            
                         
                       
                     
                     } 
                   
                 
               
             
             , 
           
         
       
     
         [0000]    where SI QTc  denotes the degree of discreteness of the ECG signals S 1 , S 2  and S 3  and the reconstructed ECG signal S R , S denotes the total number of points of measurement of the ECG signals and the reconstructed ECG signals, k denotes a fixed spatial position, n denotes the number of points of measurement at the fixed spatial positions, and QTc denotes the interval of the ECG signals at the different spatial positions and a multi-dimension space defined by the reconstruction interval of the reconstructed ECG signals. The multi-dimension space QTc is defined by an interval QT from the Q wave to the T wave of the ECG signals and an interval QT from a reconstructed Q wave to a reconstructed T wave of the reconstructed ECG signals, and is calculated by the following equation: 
         [0000]    
       
         
           
             
               
                 QT 
                 c 
               
               = 
               
                 QT 
                 
                   RR 
                 
               
             
             , 
           
         
       
     
         [0000]    where QT denotes the interval from the Q wave to the T wave of the ECG signals or the interval from the Q wave to the T wave of a reconstructed ECG signal, and RR denotes the interval between two adjacent R waves or the interval between two adjacent reconstructed R waves. 
         [0029]    Referring to  FIG. 5A  and  FIG. 5B , a schematic view of distribution of QTc at a spatial position under normal condition according to an embodiment of the present invention is shown in  FIG. 5A , and a schematic view of distribution of QTc at a spatial position under abnormal condition according to an embodiment of the present invention is shown in  FIG. 5B . As shown in the diagrams, the parameter computation and assessment unit  130  receives the ECG signals S 1 , S 2  and S 3  measured with the channels  1182 ,  1184 ,  1186  of the electrocardiographic signal measuring unit  110 , receives the at least one reconstructed ECG signal S R  calculated by the reconstruction unit  120 , calculates the starting point of the Q wave to the ending point of the T wave of the ECG signals, calculates the variation in the reconstruction interval from the starting point of the reconstructed Q wave to the ending point of the reconstructed T wave of the at least one reconstructed ECG signal against time at different spatial positions, and evaluates the degree of discreteness (i.e., SI QTc ) of the ECG signals S 1 , S 2  and S 3  and the at least one reconstructed ECG signal S R  with the parameter computation and assessment algorithm. The parameter computation and assessment unit  130  identifies an eigenvalue larger than a normal value according to SI QTc , so as to determine whether the patient generating the ECG signals has a cardiovascular disease by making reference to the degree of discreteness SI QTc . The parameter computation and assessment unit  130  calculates the variations of the T wave at different spatial positions with a T-wave propagation algorithm, so as to locate the lesion(s) of the cardiovascular disease. 
         [0030]    In another embodiment, the electrocardiographic signal measuring unit  110  further comprises a communication unit  140  electrically connected to the electrocardiographic signal measuring unit  110 , the reconstruction unit  120 , and the parameter computation and assessment unit  130 . The communication unit  140  is connected to a service platform  180  at a remote end through a network  170  by wireless or wired communication so as to send the ECG signals, reconstructed ECG signals, and data related to the degree of discreteness (i.e., SI QTc ) synchronously to the service platform  180  for use in medical services and distance diagnosis. 
         [0031]    The reconstruction algorithm and the parameter computation and assessment algorithm of the present invention can be implemented by a physical circuit or software. 
         [0032]    The second aspect of the present invention provides a method for evaluating cardiovascular performance in real time and characterized by conversion of a surface potential into multi-channels. Referring to  FIG. 1  through  FIG. 6 , a flow chart of a method according to an embodiment of the present invention is shown in  FIG. 6 . The method is applicable to the system  100  for evaluating cardiovascular performance in real time as described above. Hence, the elements, structures, and circuits of the system  100  for evaluating cardiovascular performance in real time are not described again below for the sake of brevity. The method for evaluating cardiovascular performance in real time comprises the steps as follows: 
         [0033]    Step S 602 : measuring the ECG signals S 1 , S 2  and S 3  at different spatial positions with channels  1182 ,  1184  and  1186  by the electrocardiographic signal measuring unit  110 , wherein the ECG signals each comprise P wave, Q wave, R wave, S wave, and T wave. 
         [0034]    Step S 604 : calculating orthogonal eigenvectors of measured multi-channel ECG signals by performing principal component analysis (PCA) thereon with a reconstruction algorithm by the reconstruction unit  120 , and calculating an eigenvalue matrix by using the eigenvectors as a base. 
         [0035]    The reconstruction unit  120  calculates and reconstructs at least one reconstructed ECG signal S R  at the other different spatial positions with the eigenvalue matrix and the ECG signals S 1 , S 2  and S 3  of the channels  1182 ,  1184  and  1186 . The reconstructed ECG signal S R  comprises a reconstructed P wave, a reconstructed Q wave, a reconstructed R wave, a reconstructed S wave, and a reconstructed T wave. 
         [0036]    Step S 606 : receiving, by the parameter computation and assessment unit  130 , the ECG signals S 1 , S 2  and S 3  measured by the electrocardiographic signal measuring unit  110  and the reconstructed ECG signal S R  calculated by the reconstruction unit  120 , calculating the interval from the starting point of the Q wave to the ending point of the T wave of the ECG signals S 1 , S 2  and S 3 , calculating variation in the reconstruction interval from the starting point of a reconstructed Q wave to the ending point of a reconstructed T wave of the reconstructed ECG signal S R  against time at different spatial positions, and evaluating the degree of discreteness of the ECG signals S 1 , S 2  and S 3  and the at least one reconstructed ECG signal S R  with a parameter computation and assessment algorithm to determine whether the patient has a cardiovascular disease. 
         [0037]    The present invention uses a reconstruction algorithm in enhancing spatial resolution of ECG signals by means of multi-channel ECG signals measured at different spatial positions, and uses a parameter computation and assessment algorithm to evaluate cardiovascular performance, so as to locate the lesions of cardiovascular diseases and evaluate cardiovascular performance in real time. 
         [0038]    The present invention is disclosed above by preferred embodiments. However, persons skilled in the art should understand that the preferred embodiments are illustrative of the present invention only, but should not be interpreted as restrictive of the scope of the present invention. Hence, all simple equivalent variations and modifications made to the aforesaid embodiments should fall within the scope of the present invention. Accordingly, the legal protection for the present invention should be defined by the appended claims.

Technology Category: a