Method, device and computer product for EEG monitoring, analysis and display

• US 8,708,905 B2
• Filed: 06/12/2009
• Issued: 04/29/2014
• Est. Priority Date: 06/12/2009
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Sarkela, Mika
• Primary Examiner(s): Jackson, Gary
• Assistant Examiner(s): Archer, Marie
• Application Number:
  US12/483,404
• Publication Number:
  US 20100317931A1
• Time in Patent Office: 1,782 Days
• Field of Search: 600300-301
• US Class Current: 600/301
• CPC Class Codes: A61B 2505/01 Emergency care
• CPC Class Codes: A61B 2505/03 Intensive care
• CPC Class Codes: A61B 2505/05 Surgical care
• CPC Class Codes: A61B 5/372 Analysis of electroencephalograms
• CPC Class Codes: A61B 5/384 Recording apparatus or displays specially adapted therefor
• CPC Class Codes: A61B 5/72 Signal processing specially adapted for physiological signals or for diagnostic purposes character recognition, recognising digital ink, document-oriented image-based pattern recognition G06V30/00; recognition or understanding of postal images G06V30/424
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take precedence
• CPC Class Codes: A61B 5/7235 Details of waveform analysis A61B5/349 takes precedence
• CPC Class Codes: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: Y10S 128/923 by comparison of patient data to other data
• CPC Class Codes: Y10S 128/925 Neural network

Abstract

A method, device, and computer program product for monitoring the physiological state of a subject is disclosed. A first plurality of physiological signals are acquired from the subject and a second plurality of signal parameters are determined based on the first plurality of physiological signals. Relevant signal information is selected from among the signal information produced and at least one screen page is displayed at a time, thereby to make at least part of the signal information visible to a user. The signal information visible to the user on the at least one screen page may then be revised based on the selection and without user interaction, thereby to accelerate clinical decision-making and to diminish the possibility of undetected changes in the state of the subject.

Claims

1. A method for monitoring the physiological state of a subject, the method comprising:

acquiring EEG signals from a subject, wherein a first plurality of EEG signals are acquired from a left hemisphere and a second plurality of EEG signals are acquired from a right hemisphere;

determining a third plurality of EEG signal parameters and a fourth plurality of EEG signal parameters, wherein the third plurality of EEG signal parameters are based on the first plurality of EEG signals and the fourth plurality of EEG signal parameters are based on the second plurality of EEG signals;

producing signal information comprising at least one type of signal information selected from a group including (1) time series representatives for each of the third plurality of EEG signal parameters and for each of the fourth plurality of EEG signal parameters; and

(2) signal waveforms of the first plurality of EEG signals and of the second plurality of EEG signals;

selecting relevant signal information from the signal information by comparing the third plurality of EEG signal parameters with each other and by comparing the fourth plurality of EEG signal parameters with each other, wherein at least one EEG signal parameter is selected as the relevant signal information, wherein the selected at least one EEG signal parameter belongs to the third plurality of EEG signal parameters or to the fourth plurality of EEG signal parameters;

defining a set of optimal parameters from the third plurality of EEG signal parameters and from the fourth plurality of EEG signal parameters based on subject-specific patient data;

examining whether the set of optimal parameters is consistent with the at least one EEG signal parameter selected as the relevant signal information;

displaying a primary screen page, thereby to make at least part of the signal information visible to a user; and

revising the signal information visible to the user on the primary screen page to display the selected relevant signal information, wherein the revising is performed in response to the examining and without user interaction.

2. The method according to claim 1, wherein the revising includes changing at least one time series currently visible to the user.

3. The method according to claim 1, wherein the revising includes making at least one signal waveform visible to the user.

4. The method according to claim 1, wherein the revising includes changing the primary screen page currently displayed.

5. The method according to claim 1, wherein the selecting includes comparing at least some of the third plurality of EEG signal parameters and at least some of the fourth plurality of EEG signal parameters with predetermined threshold values.

6. The method according to claim 1, wherein the revising includes changing appearance of the signal information currently visible to the user on the primary screen page.

7. The method according to claim 1, wherein the selecting further includes selecting relevant signal information by comparing the third plurality of EEG signal parameters and the fourth plurality of EEG signal parameters with each other.

8. The method according to claim 1, wherein

the determining includes determining a fifth plurality of EEG signal parameters based on EEG signals of a particular area of the left hemisphere and the right hemisphere;

the producing includes producing signal information comprising time series representatives for each of the fifth plurality of EEG signal parameters; and

the selecting includes selecting relevant signal information by comparing the third plurality of EEG signal parameters, the fourth plurality of EEG signal parameters and the fifth plurality of EEG signal parameters with each other.

9. A monitoring device for monitoring the physiological state of a subject, the monitoring device comprising:

a parameter determination unit configured to determine a third plurality of EEG signal parameters from a first plurality of EEG signals acquired from a left hemisphere of a subject and a fourth plurality of EEG signal from a second plurality of EEG signals acquired from a right hemisphere of the subject;

a data processing unit configured to produce signal information comprising at least one type of signal information selected form a group including (1) time series representative for each of the third plurality of EEG signal parameters and for each of the fourth plurality of EEG signal parameters; and

(2) signal waveforms of the first plurality of EEG signals and of the second plurality of EEG signals;

a selection unit configured to select relevant signal information from the signal information by comparing the third plurality of EEG signal parameters with each other and by comparing the fourth plurality of EEG signal parameters with each other,

wherein the selection unit is further configured to select at least one EEG signal parameter as the relevant signal information,

wherein at least one EEG signal parameter belongs to the third plurality of EEG signal parameters or the fourth plurality of EEG signal parameters;

wherein the selection unit is further configured to define a set of optimal parameters from the third plurality of EEG signal parameters and from the fourth plurality of EEG signal parameters based on subject-specific patient data and to examine whether the set of optimal parameters is consistent with the at least one EEG signal parameter selected as the relevant signal information;

a display control unit configured to revise, without user interaction, the signal information visible to the user on the primary screen page,

wherein the display control unit is responsive to the selection unit.

10. The monitoring device according to claim 9, wherein the display control unit is configured to change at least one time series currently visible to the user.

11. The monitoring device according to claim 9, wherein the display control unit is configured to change the primary screen page currently displayed.

12. The monitoring device according to claim 9, wherein the selection unit is configured to compare at least some of the third plurality of EEG signal parameters and at least some of the fourth plurality of EEG signal parameters with predetermined threshold values.

13. The monitoring device according to claim 9, wherein the display control unit is configured to change appearance of the signal information currently visible to the user on the primary screen page.

14. A non-transitory computer program product for monitoring the physiological state of a subject, the computer program product comprising:

a first program product portion configured to define a set of optimal parameters from a third plurality of EEG signal parameters and from a fourth plurality of EEG signal parameters based on subject-specific patient data, wherein the third plurality of EEG signal parameters are derived from a first plurality of EEG signals obtained from a left hemisphere of the subject and the fourth plurality of EEG signal parameters are derived from a second plurality of EEG signals obtained from a right hemisphere of the subject;

a second program product portion responsive to the first program product portion, configured to examine whether any of the set of optimal parameters from the third plurality of EEG signal parameters or any of the set of optimal parameters from the fourth plurality of EEG signal parameters are indicative of a relevant change in the state of the subject, wherein the third plurality of EEG signal parameters are derived from a first plurality of EEG signals obtained from a left hemisphere of the subject and the fourth plurality of EEG signal parameters are derived from a second plurality of EEG signals obtained from a right hemisphere of the subject; and

a third program product portion, responsive to the second program product portion, configured to revise, without user interaction, signal information currently visible to a user, wherein the signal information comprises at least one type of information selected from a group including (1) time series representatives for each of the set of optimal parameters from the third plurality of EEG signal parameters and for each of the set of optimal parameters from the fourth plurality of EEG signal parameters; and

(2) signal waveforms of the first plurality of EEG signals and of the second plurality of EEG signals obtained from the subject.

15. The non-transitory computer program product according to claim 14, further comprising a fourth program product portion configured to determine at least some of the third plurality of EEG signal parameters from the first plurality of EEG signals and at least some of the fourth plurality of EEG signal parameters from the second plurality of EEG signals.