METHOD OF PHYSIOLOGICAL DATA ANALYSIS AND MEASUREMENT QUALITY CHECK USING PRINCIPAL COMPONENT ANALYSIS

• US 20080132799A1
• Filed: 11/30/2006
• Published: 06/05/2008
• Est. Priority Date: 11/30/2006
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Xue, Joel Quizhen
• Granted Patent: US 7,769,434 B2
• Time in Patent Office: Days
• US Class Current: 600/509
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

In a method of analyzing patient physiological data, the data is subjected to principal component analysis and compared to a model physiological data principal component analysis. The comparison is used to identify correlations present in the morphology of the patient physiological data. The present invention further includes determining a confidence interval for the detection of a morphological feature and utilizing this confidence interval for improving the quality of the detection of morphological features of the patient physiological data, including automated morphological feature identification.

Claims

1. A method of analyzing patient physiological data collected as part of a pharmacological study, the method comprising the steps of:

collecting patient physiological data;

normalizing the patient physiological data;

performing a principal component analysis of the normalized patient physiological data;

comparing the analysis of the patient physiological data to a model patient physiological data principal component analysis;

using the comparison to identify morphology of the patient physiological data.

2. The method of claim 1 further comprising the step of creating the model patient physiological data principal component analysis.

3. The method of claim 2 wherein the physiological data is patient ECG signal data.

4. The method of claim 3 wherein the model patient physiological data principal component analysis is a composite analysis of a plurality of ECG signal data.

5. The method of claim 4 wherein a model patient physiological data principal component analysis is created using a plurality of edited normal and abnormal ECG signals.

6. The method of claim 1 wherein the principal component analysis is a six-vector principal component analysis.

7. The method of claim 3 further as using the comparison to identify the morphology of a specific ECG signal characteristic.

8. The method of claim 7 wherein the specific ECG signal characteristic is T-wave characteristic.

9. The method of claim 8 wherein the specific ECG signal characteristic is at least one of the T-wave duration and Q-T interval.

10. The method of claim 3 further comprising the step of sorting the ECG signals into morphological bins based upon the comparison of the ECG signal principal component analysis to the model principal component analysis.

11. The method of claim 10 further comprising the step of performing a statistical analysis on the ECG signals in each bin to determine the quality of an individual signal within the bin.

12. The method of claim 10 further comprising the step of determining a confidence interval for each bin.

13. The method of claim 12 further comprising the step of rejecting a signal based upon its deviation from the other signals within the same bin.

14. The method of claim 10 further comprising the step of learning identifying characteristics of each bin and using the learned identifying characteristics to automatically detect and identify desired predetermined selected signal morphology in the analysis of an ECG signal.

15. A method of analyzing an ECG signal collected as part of a pharmacological drug trial, the method comprising the steps of:

collecting ECG signal data;

performing principal component analysis on the collected data;

identifying characteristics of the ECG signal using the principal component analysis;

sorting the ECG signals into groups based upon the identified characteristics;

performing a statistical analysis on the ECG signal groups to determine an indication of signal quality;

using the indication of signal quality to improve the detection of a morphological feature of the ECG signal comprising one detecting a morph feature of ECG signal data using the indication of segment quality to improve detection of the morph feature, the morph feature comprising one indicative of a drug induced condition.

16. The method of claim 15 wherein the step of collecting ECG signal data comprises receiving the ECG signal data from a database of collected ECG signal data.

17. The method of claim 15 wherein the indication of signal quality is a confidence interval for a morphological feature of an ECG signal.

18. The method of claim 15 wherein the detection of a morphological feature of the ECG signal is performed automatically.

19. The method of claim 15 wherein the drug-induced condition is Torsade-de-Pointes.

20. A computer program embodied on a computer readable medium having computer logic for enabling at least one processor in a computer system to facilitate analyzing an ECG signal collected as part of a pharmacological drug trial, the computer readable medium comprising:

a first computer readable program code portion for collecting ECG signal data;

a second computer readable program code portion for identifying characteristics of the ECG signal;

a third computer readable program code portion for creating a model of the ECG signal data based on the characteristic of the ECG signal; and

a fourth computer readable program code portion for using the model to detect a morphological feature of a future ECG signal.