System and method for prediction of adverse events during treatment of psychological and neurological disorders

• US 20060167370A1
• Filed: 01/12/2006
• Published: 07/27/2006
• Est. Priority Date: 01/12/2005
• Status: Active Grant

• Current Assignee: Covidien LP (Medtronic Plc)
• Original Assignee: Aspect Medical Systems, Inc. (Medtronic Plc)
• Inventors: Sigl, Jeffrey C., Devlin, Philip H., Greenwald, Scott D.
• Granted Patent: US 8,005,534 B2
• Time in Patent Office: Days
• US Class Current: 600/544
• CPC Class Codes: A61B 5/16 Devices for psychotechnics using teaching or educational appliances G09B1/00 - G09B7/00; Testing reaction times ; Devices for evaluating the psychological state
• CPC Class Codes: A61B 5/165 Evaluating the state of mind, e.g. depression, anxiety
• CPC Class Codes: A61B 5/374 Detecting the frequency distribution of signals, e.g. detecting delta, theta, alpha, beta or gamma waves
• CPC Class Codes: G16H 20/70 relating to mental therapies, e.g. psychological therapy or autogenous training

Abstract

The present invention is a system and method of deriving and computing features and indices that predict the likelihood of psychological and neurological adverse events such as suicidal thoughts and/or actions. The method of the present invention further predicts the likelihood of suicidal thoughts and/or actions prior to and or during treatment for psychological disease. To obtain such features and indices, power spectrum and time domain values are derived from biopotential signals acquired from the subject being tested. The system and method identify people who are likely to experience changing, especially worsening, symptoms of psychological and neurological adverse events such as suicidal thoughts or actions and who therefore may be at risk (e.g. suicide).

Claims

1. A method of predicting psychological and neurological adverse events from biopotential signals comprising the steps of:

acquiring biopotential signals from a subject being evaluated,

computing at least one parameter from said biopotential signals,

deriving at least one biopotential feature from said at least one parameter, and

predicting the adverse event through the use of said at least one biopotential feature.

2. The method of claim 1, wherein said adverse events are suicidal thoughts.

3. The method of claim 1, wherein said adverse events are suicidal actions.

4. The method of claim 1, wherein said at least one feature is relative theta frequency band power.

5. The method of claim 1, wherein said at least one feature is relative theta+alpha frequency band asymmetry.

10. The method of predicting psychological and neurological adverse events from biopotential signals of claim 1 wherein said at least one parameter is computed using a combination of relative EEG theta power and relative combined theta+alpha asymmetry.

15. The system for predicting psychological and neurological adverse events from biopotential signals of claim 1, wherein said at least one feature is relative theta+alpha frequency band asymmetry.

6. A method of predicting adverse events psychological and neurological adverse events from biopotential signals comprising the steps of:

acquiring biopotential signals from a subject being evaluated,

computing at least one parameter from said biopotential signals,

deriving a first biopotential feature and a second biopotential feature from said parameters, and

creating an index for predicting the adverse event, said index being derived from a combination of said at least two biopotential features.

7. A method of predicting adverse events psychological and neurological adverse events from biopotential signals comprising the steps of:

acquiring biopotential signals from a subject being evaluated,

computing at least one parameter from said biopotential signals,

deriving from said parameters a first biopotential feature at a first time point and a second biopotential feature at a second time point, and

creating an index for predicting the adverse event, said index being derived from a combination of said at least two biopotential features.

8. A method of predicting psychological and neurological adverse events from biopotential signals, comprising the steps of:

acquiring biopotential signals from a subject being evaluated,

computing at least one parameter from said biopotential signals,

measuring a first biopotential feature at a pre-treatment condition,

measuring a second biopotential feature from said parameter after an initiation of treatment of the subject,

creating an index by combining said first biopotential feature and said second biopotential feature, and

predicting the adverse event through the use of said index.

9. The method of claim 8, wherein said index combining said first and second features is the distance from the origin of the point represented by said two features.

11. A system for predicting psychological and neurological adverse events from biopotential signals comprising:

a data acquisition unit for acquiring biopotential signals from a subject being evaluated,

a processor for computing at least one parameter from said biopotential signals and for deriving at least one biopotential feature from said at least one parameter, and

analysis device for predicting the adverse event through the use of said at least one biopotential feature.

12. The system for predicting psychological and neurological adverse events from biopotential signals of claim 11, wherein said adverse events are suicidal thoughts.

13. The system for predicting psychological and neurological adverse events from biopotential signals of claim 11, wherein said adverse events are suicidal actions.

14. The system for predicting psychological and neurological adverse events from biopotential signals of claim 11, wherein said at least one feature is relative theta frequency band power.

20. The system for predicting psychological and neurological adverse events from biopotential signals or claim 11 wherein said at least one parameter is computed using a combination of relative EEG theta power and relative combined theta+alpha asymmetry.

16. A system for predicting psychological and neurological adverse events from biopotential signals comprising:

a data acquisition unit for acquiring biopotential signals from a subject being evaluated,

a processor for computing at least one parameter from said biopotential signals, for deriving a first biopotential feature and a second biopotential feature from said parameters, and for creating an index for predicting the adverse event.

17. A system for predicting psychological and neurological adverse events from biopotential signals comprising:

a data acquisition unit for acquiring biopotential signals from a subject being evaluated,

a processor for computing at least one parameter from said biopotential signals, for deriving from said parameters a first biopotential feature at a first time point and a second biopotential feature at a second time point, and for creating an index for predicting the adverse event, said index being derived from a combination of said at least two biopotential features, and for creating an index for predicting the adverse event, said index being derived from a combination of said first and second biopotential features.

18. A system for predicting psychological and neurological adverse events from biopotential signals comprising:

a data acquisition unit for acquiring biopotential signals from a subject being evaluated,

a processor for computing at least one parameter from said biopotential signals, for measuring a first biopotential feature at a pre-treatment condition, for measuring a second biopotential feature from said parameter after an initiation of treatment of the subject, and for creating an index for predicting the adverse event through the use of said index by combining said first biopotential feature and said second biopotential feature.

19. The system for predicting psychological and neurological adverse events from biopotential signals of claim 18, wherein said index combining said first and second features is the distance from the origin of the point represented by said two features.