System and device for multi-scale analysis and representation of electrocardiographic data

• US 6,389,308 B1
• Filed: 05/30/2000
• Issued: 05/14/2002
• Est. Priority Date: 05/30/2000
• Status: Expired due to Term

• Current Assignee: Vladimir Shusterman
• Original Assignee: Vladimir Shusterman
• Inventors: Shusterman, Vladimir
• Primary Examiner(s): Getzow, Scott M.
• Application Number:
  US09/583,668
• Time in Patent Office: 714 Days
• Field of Search: 600/509, 600/512, 600/523
• US Class Current: 600/509
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/7232 involving compression of the physiological signal, e.g. to extend the signal recording period

Abstract

System comprised of a portable medical device and method for registering electrocardiographic (ECG) signals, extracting and representing the most significant parameters at different levels of detail using the color-coded scales which are understandable to a lay person and a medical professional. Low, intermediate and high-resolution scales are defined according to the corresponding software and hardware resources. A low-resolution Scale I represents a small number of primary elements such as intervals between the heart beats, duration of PQ, QRS, and QT-intervals, amplitudes of P-, Q-, R-, S-, and T-waves. This real-time analysis is implemented in a portable device that requires minimum computational resources. The set of primary elements and their search criteria are adjusted for each ECG using intermediate or high-resolution levels. At the intermediate-resolution Scale II, serial changes in each of the said elements are determined using a mathematical decomposition into series of orthogonal basis functions and their coefficients. This scale is implemented using a specialized processor or a computer organizer. At the high-resolution Scale II, combined serial changes in all elements of the ECG are determined to provide complete information about the dynamics of the signal. This scale is implemented using a powerful processor, a network of computers or the Internet. The system can be used for personal or group self-evaluation, emergency or routine ECG analysis, or continuous event, stress-test or bed-side monitoring.

Claims

1. A method for dynamic analysis of electrocardiographic (ECG) data in at least two levels of detail, said method comprising:

analyzing a limited number of primary elements in said ECG data in low resolution to detect one-time changes in such primary elements and thereby identify abnormal or unstable primary elements;

analyzing said ECG data in high resolution using orthogonal mathematical decomposition to provide detailed characterization of serial changes in said abnormal or unstable primary elements; and

adjusting said analyzing in low resolution based on said detailed characterization of serial changes in the primary elements.

2. A method as set forth in claim 1 in which said analyzing in high resolution further includes:

combining a plurality of said serial changes in the abnormal or unstable primary elements and analyzing the combined changes using orthogonal mathematical decomposition; and

selecting a combination of parameters for tracking the changes in said abnormal or unstable elements and sending information respecting the selected combination to said low-resolution analysis for adjustment of monitoring parameters.

3. A method as set forth in claim 1 in which said analyzing in high resolution comprises:

forming a time series from said serial changes;

characterizing said time series using Principal Component Analysis (PCA) and generating PCA-coefficients indicative of both linear and nonlinear changes in the individual pattern; and

determining the magnitude of said linear and nonlinear changes by using time varying mean and variance of said PCA-coefficients and determining the complexity of said linear and nonlinear changes by calculating the number of PCA-coefficients that exhibit substantially simultaneous changes.

4. A method as set forth in claim 1 in which said analyzing in high resolution comprises:

forming time series from said serial changes;

characterizing said time series using Principal Component Analysis (PCA) and generating PCA-coefficients indicative of both linear and nonlinear changes in the individual pattern;

presenting said PCA-coefficients as a vector in n-dimensional space wherein n is the number of variables analyzed; and

determining the magnitude and direction of the combined changes in the characteristic variables by the changes in the magnitude and direction of said n-dimensional vector.

5. A method as set forth in claim 1 in which said low level resolution includes comparing said primary elements with normal values for such primary elements, and representing deviation of primary elements from the normal values in a form understandable to a lay person.

6. A method as set forth in claim 5 that further comprises representing deviations of said primary elements from said normal values in a quantitative form for use by a medical professional.

7. A method as set forth in claim 1 which includes sounding an alarm when said low resolution detects an abnormal or unstable primary element.

8. A method as set forth in claim 1 in which said analyzing in high resolution comprises:

forming a time series from said serial changes;

characterizing said time series using Principal Component Analysis (PCA) and generating eigenvectors and eigenvalues indicative of both linear and nonlinear changes in the individual pattern; and

determining the magnitude and complexity of said linear and nonlinear changes by comparing the corresponding eigenvectors and eigenvalues.

9. An electrocardiographic (ECG) system for detection and analysis of serial changes in ECG signals for use by both lay persons and medical professionals, said system comprising:

an acquisition unit for collecting ECG signals from a subject over a period of at least several seconds;

a first analysis and processing unit for detecting a plurality of primary elements from said ECG signals and processing said primary elements to generate data respecting time intervals or amplitudes of said primary elements;

a storage unit for storing reference values of said plurality of primary elements;

a comparative unit for comparing said reference values with data newly received from said first analysis and processing unit and producing qualitative indicators and quantitative data of differences between said recorded data and said newly received data;

an output unit for displaying said qualitative indicators in a form understandable by lay persons and quantitative data for medical professionals; and

a communications unit for sending quantitative data of said primary elements to a second analysis unit for processing and detailed analysis of serial changes in said ECG signals, said second analysis unit includes means for assessing small changes in serial ECG signal, comprising;

means for characterizing time series of at least one primary element or index in said set of primary elements and indexes using Principal Component Analysis (PCA) and generating PCA coefficients indicative of both linear and nonlinear changes in the individual pattern;

means for determining the magnitude of said changes in the characteristic variables by using time varying mean and variance of said PCA coefficients and determining the complexity of said changes by calculating the number of PCA coefficients that exhibit substantially simultaneous changes;

means for presenting of said combination of PCA coefficients as a vector in n-dimensional space wherein n is the number of variables analyzed; and

means for determining the magnitude and complexity of the changes in the combination of the characteristic variables by the changes in said n-dimensional vector.

10. An ECG system as set forth in claim 9 in which said first analysis unit includes means for receiving commands from said second analysis unit to adjust the primary elements to be detected from ECG signals.

11. An ECG system as set forth in claim 10 in which said output unit includes a screen for displaying said qualitative indicators of a minimal set of most significant indexes to indicate a substantially abnormal ECG and a screen for quantitative representation that represents a complete set of characteristic fragments and their parameters.

12. An ECG system as set forth in claim 9 in which said output unit for qualitative representation includes a static screen for one-time ECG presentation and a dynamic screen for presenting changes in serial ECG recordings.

13. An ECG system as set forth in claim 9 in which said set of primary elements includes a complete set of characteristic fragments of the ECG signals and their parameters, said set of characteristic fragments including P, Q, R, S, T and U waves, ST-segment, PR, QRS and QT-intervals, said parameters including the amplitude and duration of said waves and segments, and the time intervals between the heart beats.

14. An ECG system as set forth in claim 9 in which said set of primary elements includes the amplitudes of the T-wave and U-wave combined into a single index for patients with known electrolyte abnormalities.

15. An ECG system as set forth in claim 9 in which said first analysis and processing unit includes means for decomposing the ECG signal into a plurality of elements, and said decomposing means performs an orthogonal decomposition to extract the most significant information about the ECG signal.

16. An ECG system as set forth in claim 9 in which said first analysis and processing unit, storage unit and comparative unit are combined in one pocket size unit connected to said communication unit.

17. An ECG system as set forth in claim 16 in which said communication unit is wireless.

18. An ECG system as set forth in claim 16 in which said storage unit includes storage for a physiologic range of the primary elements and detector of error and noise to reject the data upon detection of the primary elements or the indexes beyond the physiologic range.

19. An ECG system as set forth in claim 9 in which said output unit includes a display for viewing the ECG signal.

20. An ECG system as set forth in claim 9 in which said means for characterizing time series of at least one primary element or index also generates eigenvectors and eigenvalues.

21. A portable electrocardiograph for self-examination comprising:

means for collecting and storing ECG signal from a subject;

an analysis unit for processing the ECG signal in dependence upon a predetermined set of primary elements comprising a complete set of characteristic fragments of the ECG signals and their parameters, said set of characteristic fragments including P, Q, R, S, T; and

U waves, ST-segment, PR, QRS and QT-intervals, said parameters including the amplitude and duration of the said waves and segments, and the time intervals between the heart beats, said analysis unit further characterizing time series of at least one primary element in said set of primary elements and indexes using Principal Component Analysis (PCA) and generating PCA coefficients indicative of both linear and non-linear changes in the individual pattern, determining the magnitude of said changes in the variables by using time varying means and variance of said PCA coefficients, determining the complexity of said changes by calculating the number of PCA coefficients that exhibit substantially simultaneous changes, presenting said combination of PCA coefficients as a vector in n-dimensional space wherein n is the number of variables analyzed, and determining the magnitude and complexity of the changes in combination of the characteristic variables by changes in said n-dimensional vector, and comparing stored ECG signals with newly collected signals;

means for representing the results of said analysis unit including a screen for qualitative representation with respect to a set of reference values, said screen for qualitative representation including a set of indicators understandable by a lay person and a screen for displaying quantitative data for use by medical professionals; and

means for changing thresholds of said primary elements for the detection of said parameters by said means for collecting and storing ECG signals.

22. A portable electrocardiograph as set forth in claim 21 in which said means for collecting and storing is a pocket-size unit having wireless communication with the rest of the portable electrocardiograph.

23. A medical device as set forth in claim 21 in which said set of reference values includes characteristic values for said set of primary elements and indexes previously stored or default characteristic values.

24. An ECG system as set forth in claim 21 in which said means for representing includes an LCD display for viewing the ECG signal, said LCD display representing a range of normal or previously stored values for plurality of characteristic points and segments.

25. An electrocardiographic (ECG) monitoring system having at least two levels of detail (or resolution) for displaying changes detected in ECG signals, said system comprising:

an acquisition unit for receiving ECG signals generated by monitoring a subject for at least several seconds;

an analysis module for detecting a plurality of primary elements from said ECG signals to detect one-time changes in such primary elements and thereby identify abnormal or unstable primary elements;

a storage unit for storing said plurality of primary elements;

a comparative unit for comparing said plurality of primary elements from said storage unit with a plurality of primary elements newly received from said analysis module and producing both qualitative and quantitative information representing the differences in the data;

an output unit for displaying qualitative information understandable by a lay person and quantitative information useful to medical professionals; and

a communications unit for exchanging data with a remote analysis and comparison unit for high level analysis of said ECG signals, said remote analysis and comparison unit using orthogonal mathematical decomposition to provide detailed characterization of serial changes in said abnormal or unstable primary elements and wherein said analysis unit includes means for receiving commands from said remote analysis and comparison unit to reprogram said analysis units.

26. An ECG system as set forth in claim 25 in which said analysis module and said comparative unit analyze and compare data in at least three levels of detail.

27. An ECG system as set forth in claim 26 in which said analysis module includes means for using said commands from said remote analysis unit to modify the primary elements to be detected from said ECG signals.

28. A portable electrocardiographic (ECG) monitoring system having at least two levels of detail (or resolution) for displaying changes detected in ECG signals, said portable system comprising:

an acquisition unit for receiving ECG signals generated by monitoring a subject for at least several seconds;

an analysis unit for detecting a plurality of primary elements from said ECG signals to detect one-time changes in such primary elements and thereby identify abnormal or unstable primary elements, storing said plurality of primary elements, comparing said plurality of primary elements from said storage unit with a plurality of primary elements newly received from said analysis nodule and producing both qualitative and quantitative information representing the differences in the data, and using orthogonal mathematical decomposition to provide detailed characterization of serial changes in said abnormal or unstable primary elements in both low and high level resolution and adjusting said characterization in low level resolution based on the characterization of the serial changes in high level resolution;

an output unit for displaying qualitative information understandable by lay persons and quantitative information useful to medical professionals; and

a communications unit for sending data to a remote processing unit for analysis by medical professionals.

29. A monitoring system as set forth in claim 28 forms a time series from said serial changes, characterizes said time series using Principal Component Analysis (PCA) and generates PCA-coefficients indicative of both linear and nonlinear changes in the individual pattern, determines the magnitude of said linear and nonlinear changes by using time varying mean and variance of said PCA-coefficients and determines the complexity of said linear and nonlinear changes by calculating the number of PCA-coefficients that exhibit substantially simultaneous changes.