SYSTEM AND METHOD OF MORPHOLOGY FEATURE ANALYSIS OF PHYSIOLOGICAL DATA

• US 20090228298A1
• Filed: 03/04/2008
• Published: 09/10/2009
• Est. Priority Date: 03/04/2008
• Status: Abandoned Application

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Xue, Joel Q.
• Application Number:
  US12/042,192
• Publication Number:
  US 20090228298A1
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/352 Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/366 Detecting abnormal QRS complex, e.g. widening
• CPC Class Codes: G06F 18/2178 based on feedback of a supervisor
• CPC Class Codes: G06F 2218/12 Classification; Matching
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A system and method of analyzing physiological data morphology includes a first physiological data source. A morphological segment detection module receives first physiological data from the first physiological data source and applies at least one algorithm to identify at least one morphological segment of the first physiological data. A segment feature rating module applies at least one algorithm to the at least one identified morphological segment to identify at least one segment feature to produce rating of the severity of the at least one segment feature.

Claims

1. A system for the analysis of morphological features of physiological data, the system comprising:

a first physiological data source;

a morphological segment detection module that receives first physiological data from the first physiological data source and applies at least one algorithm to identify at least one morphological segment of the first physiological data; and

a segment feature rating module that applies at least one algorithm to the at least one identified morphological segment to identify at least one segment feature and produce a first rating of the severity of the at least one segment feature.

2. The system of claim 1, further comprising:

a display that receives the first physiological data and the first rating of the severity of the at least one segment feature and presents the first physiological data and the first rating to a clinician;

an input device operable to receive from a clinician a selection of the first rating and a modification to the first rating according to the clinician'"'"'s interpretation of the first physiological data; and

a storage device wherein the modified first rating is stored.

3. The system of claim 1 further comprising:

a second physiological data source comprising second physiological data that includes at least one second rating of the severity of at least one segment feature of the second physiological data;

a physiological comparison module that receives the second physiological data from the second physiological data source and the first physiological data from the segment feature rating module, the physiological comparison module applying at least one algorithm to compare the first physiological data with the second physiological data, the physiological comparison module producing an output indicative of the results of the comparison.

4. The system of claim 3, wherein the at least one algorithm applied by the physiological comparison module comprises a sum of squares algorithm that provides a comparison between the first rating of the first physiological data and the second rating of the second physiological data.

5. The system of claim 1 further comprising:

a physiological database populator that receives the first physiological data and the first rating; and

a physiological database comprising a plurality of physiological data and a plurality of segment feature ratings, the physiological database storing the first physiological data in the plurality of physiological data and the first rating in the plurality of segment feature ratings;

wherein the first physiological data is stored in the physiological database according to the first rating.

6. The system of claim 5, wherein plurality of physiological data is stored in the physiological database as a look up table according to the plurality of segment feature ratings.

7. The system of claim 6 further comprising a data mining module connected to the physiological database such that the plurality of physiological data stored according to the plurality of segment feature ratings may be accessed as a data set wherein all the physiological data in the data set comprises a specified segment feature rating.

8. The system of claim 1, wherein the first physiological data source is a patient monitor that measures physiological signals from a patient.

9. The system of claim 1, wherein the first physiological data source is a database of stored physiological data.

10. A system for the analysis of the morphology of electrocardiographic (ECG) data, the system comprising:

a first ECG data source;

a morphological segment detection module that receives first ECG data from the first ECG data source and applies at least one algorithm to detect at least one morphological segment of the first ECG data; and

a segment feature rating module that applies at least one algorithm to the at least one detected morphological segment to identify at least one segment feature and produce a first rating of the severity of the at least one segment feature.

11. The system of claim 10 further comprising:

a display that receives the first ECG data and the first rating and presents the first ECG data and the first rating to a clinician;

an input device operable to receive from a clinician, upon review of the first rating on the display, a selection of the first rating and a modification to the first rating according to the clinician'"'"'s interpretation of the first ECG data; and

a storage device wherein the modified first rating is stored.

12. The system of claim 10 further comprising:

a second ECG data source comprising second ECG data that includes at least one second rating;

an ECG comparison module that receives the second ECG data from the second ECG data source and the first ECG data from the segment feature rating module, the ECG comparison module applying at least one algorithm to compare the first ECG data with the second ECG data, the ECG comparison module producing an output indicative of the results of the comparison.

13. The system of claim 12 wherein the output is a hyperdistance comprising the difference between the first rating of the first physiological data and the second rating of the second physiological data.

14. The system of claim 10 further comprising:

an ECG database populator that receives the first ECG data and the first rating;

an ECG database comprising a plurality of ECG data and a plurality of segment feature ratings, the ECG database storing the first ECG data as part of the plurality of ECG data and the first rating as part of the plurality of segment feature ratings, the first ECG data being stored in the ECG database according to the first rating; and

a data mining module connected to the ECG database such that the plurality of ECG data may be accessed as a data set wherein all of the ECG data in the data set comprises a specified segment feature rating.

15. A method of analyzing physiological data morphology, the method comprising the steps of:

receiving first physiological data;

identifying at least one morphological segment of the first physiological data;

identifying at least one segment feature of each identified morphological segment; and

determining a segment feature severity level for each identified segment feature.

16. The method of claim 15 wherein the first physiological data is electrocardiographical (ECG) data.

17. The method of claim 16 further comprising the steps of:

presenting the ECG data;

presenting the at least one segment feature severity level;

receiving a modification to at least one segment feature severity level; and

saving the modified segment feature severity level.

18. The method of claim 16 further comprising the steps of:

receiving second ECG data, the second ECG data having at least one identified segment feature and at least one determined segment feature severity level;

comparing the first ECG data and second ECG data based on the identified segment features and determined segment feature severity levels; and

producing an output indicative of the results of the comparison between the first ECG data and the second ECG data.

19. The method of claim 16 further comprising the steps of:

grouping the ECG data according to the identified at least one segment feature and the determined segment feature severity level; and

creating a database with the ECG data stored according to the groups in which the ECG data was placed.

20. The method of claim 19 further comprising the steps of:

retrieving a data set from the database, the data set comprising a plurality of ECG data comprising a specified segment feature and segment feature severity level; and

applying at least one data mining technique to the retrieved data set.