Abstract: A method for analyzing a condition of a heart, comprises receiving a plurality of electric signals, which are acquired by non-invasive measurement on the skin of a person or animal, each signal representing electrical activity in a respective region of the heart of the person or animal; calculating a derivative value of each signal at a plurality of time instances; selecting a plurality of the calculated derivative values of a first signal and determining a first point in time of a first event based on the selected derivative values; selecting a plurality of the calculated derivative values of a second signal and determining a second point in time of a second event, corresponding to the first event, based on the selected derivative values of the second signal, and calculating at least one measure based on a difference of the first point in time and the second point in time.

Abstract: A method for analyzing a condition of a heart, comprises receiving a plurality of electric signals, which are acquired by non-invasive measurement on the skin of a person or animal, each signal representing electrical activity in a respective region of the heart of the person or animal; calculating a derivative value of each signal at a plurality of time instances; selecting a plurality of the calculated derivative values of a first signal and determining a first point in time of a first event based on the selected derivative values; selecting a plurality of the calculated derivative values of a second signal and determining a second point in time of a second event, corresponding to the first event, based on the selected derivative values of the second signal, and calculating at least one measure based on a difference of the first point in time and the second point in time.

Abstract: A method, system, stethoscope and server for classifying a cardiovascular sound recorded from a living subject. The method comprises the steps of: identifying diastolic and/or systolic segments of the cardiovascular sound; dividing at least one of the identified diastolic and/or systolic segments into a number of sub-segments comprising at least a first sub-segment and at least a second sub-segment; extracting from the first sub-segment at least a first signal parameter characterizing a first property of the cardiovascular sound, extracting from the second sub-segment at least a second signal parameter characterizing a second property of the cardiovascular sound; and classifying the cardiovascular sound using the at least first signal parameter and the at least second signal parameter in a multivariate classification method.

Abstract: This invention describes a method for dividing a substantial cycli cardiovascular signal into segments by determining the characteristics of said cyclic signal, wherein each cycle in said signal comprises at least two characteristic segments and wherein the method comprises the steps o identifying segments in a cycle based on prior knowledge of said segment characteristics and the step of verifying said identified segments based on a number of statistical parameters obtained from prior knowledge relating to said cyclic signal. Furthermore, the invention describes a system adapted to perform the above-described method.

Abstract: A system and a method for analysis of ECG curvature, which system involves a mathematical analysis comprising the following features where a number of different parameters are isolated and stored in a computer, where a first number of parameters are selected from at least one main group, where the selected parameters are combined in at least a first mathematical analysis. It is the object of the invention to improve mathematical analysis of ECG curvature particular for complex parts of the curvature such as notches or concavities. This can be achieved by selecting parameters from groups of symmetry, flatness, duration and/or complexity, using the parameters as input to an algorithm, where concavity intervals are evaluated on subsegments of the ECG segment and form the basis of up and downwards concavity quantification, where the system based on an algorithm detects and quantifies concavity on ECG curvatures.

Abstract: The present invention relates to a system or method for analyzing drug influence on ECG curvature and Long QT Syndrome. The system has an input means connected to an ECG source, where different parameters of a received ECG curvature are indicated and/or isolated for indicating possible symptoms which relate to certain diseases that influence the ECG curvature. The aim of the invention is to achieve a system and a method for diagnosing Long QT Syndrome in an objective, fast and effect way by indication of a number of symptoms derivable from an ECG curve. Further aim is to achieve an effective test of drug influence on ECG curvature. The system analyzes the QT curvature of the ECG curvature for indicating Long QT Syndrome.

Abstract: A method for evaluating an electrocardiogram is disclosed herein. The method includes measuring an electrical activity of a patient, processing the measured electrical activity to form a multi-lead signal, and extracting a segment of the multi-lead signal. The method for evaluating an electrocardiogram also includes transforming the segment of the multi-lead signal into a synthesized signal that is most representative of the patient's electrical activity, and evaluating the synthesized signal. A corresponding system for evaluating an electrocardiogram is also disclosed.

Abstract: The present invention relates to a method for classifying a cardiovascular sound recorded from a living subject. The method comprises the steps of: identifying diastolic and/or systolic segments of said cardiovascular sound; dividing at least one of said identified diastolic and/or systolic segments into a number of sub-segments comprising at least a first sub-segment and at least a second sub-segment; extracting from said first sub-segment at least a first signal parameter characterizing a first property of said cardiovascular sound, extracting from said second sub-segment at least a second signal parameter characterizing a second property of said cardiovascular sound; classifying said cardiovascular sound using said at least first signal parameter and said at least second signal parameter in a multivariate classification method.

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.

Abstract: A backlight of the present invention (illumination device) 2 includes: light sources (5); light guide plates (7) for causing surface emission of light from the light sources (5); and a diffusing plate (8) for diffusing light from the light guide plates (7), the diffusing plate (8) facing a light-emitting surface (7a) of each of the light guide plates (7) at a predetermined distance. Each light guide plate (7) includes: a light-emitting section (7b) having the light-emitting surface (7a); and a light guide section (7c) for guiding, to the light-emitting section (7b), light from a corresponding light source (5), where the light-emitting section of one of any adjacent two light guide plates is placed over the light guide section (7c) of the other light guide plate (7). The illumination device further includes at least one maintaining section between the light-emitting surface (7a) and the diffusing plate (8), the maintaining section (10) maintaining the predetermined distance.

Abstract: This invention describes a method for dividing a substantial cycli cardiovascular signal into segments by determining the characteristics of said cyclic signal, wherein each cycle in said signal comprises at least two characteristic segments and wherein the method comprises the steps o identifying segments in a cycle based on prior knowledge of said segment characteristics and the step of verifying said identified segments based on a number of statistical parameters obtained from prior knowledge relating to said cyclic signal. Furthermore, the invention describes a system adapted to perform the above-described method.

Abstract: The present invention relates to a system and a method for analysis of ECG curvature, which system involves a mathematical analysis, which analysis comprises the following features where a number of different parameters are isolated and stored in computer means, where a first number of parameters are selected from at least one main group, where the selected parameters are combined in at least a first mathematical analysis. It is the object of the invention to improve mathematical analysis of ECG curvature particular for complex parts of the curvature such as notches or concavities. It is a further object of the invention to improve automatic quantification of symmetry, flatness and durations of ECG curvature.

Abstract: A system or a method for analysing ECG curvature wherein at least one among a number of different parameters is isolated, for indicating symptoms of diseases having influence on the ECG curvature. The system and method provides for objective, fast and effective indication of a number of symptoms derivable from an ECG curve which may be indicative of one or more diseases. This can be achieved when a first number of selected parameters are combined in at least a first mathematical analysis, where the result of the analysis can be represented as a point in a coordinate system comprising at least two axes where the system can compare the actual placement in the coordinate system with a number of reference parameters stored in the system for indicating diseases having influence on the ECG curvature.

Abstract: A method for evaluating an electrocardiogram is disclosed herein. The method includes measuring an electrical activity of a patient, processing the measured electrical activity to form a multi-lead signal, and extracting a segment of the multi-lead signal. The method for evaluating an electrocardiogram also includes transforming the segment of the multi-lead signal into a synthesized signal that is most representative of the patient's electrical activity, and evaluating the synthesized signal. A corresponding system for evaluating an electrocardiogram is also disclosed.

Abstract: The present invention relates to a system or a method for analysing drug influence on ECG curvature and Long QT Syndrome where at least one among a number of different parameters is isolated, which system has a input means connected to an ECG source, where the different parameters of a received ECG curvature and indicated and/or isolated and for indicating possible symptoms which relates to or are indications of certain diseases, where said diseases are known to influence the ECG curvature. The aim of the invention is to achieve a system and a method for diagnosing Long QT Syndrome in an objective, fast and effective way by indication of a number of symptoms derivable from an ECG curve. Further aim of the invention is to achieve an effective test of drug influence on ECG curvature.

Abstract: A system or a method for analysing ECG curvature is provided, in which where at least one among a number of different parameters is isolated. The system has an input device connected to an ECG source, where the different parameters of a received ECG curvature are indicated and/or isolated and for indicating possible symptoms which relate to or are indications of certain diseases, where said diseases are known to influence the ECG curvature. The system and method provides for objective, fast and effective indication of a number of symptoms derivable from an ECG curve which may be indicative of one or more diseases.