ARTIFACT DETECTION AND CORRECTION SYSTEM FOR ELECTROENCEPHALOGRAPH NEUROFEEDBACK TRAINING METHODOLOGY

• US 20090062680A1
• Filed: 08/27/2008
• Published: 03/05/2009
• Est. Priority Date: 09/04/2007
• Status: Abandoned Application

• Current Assignee: Brain Train
• Original Assignee: Brain Train
• Inventors: SANDFORD, JOSEPH A.
• Application Number:
  US12/198,972
• Publication Number:
  US 20090062680A1
• Time in Patent Office: Days
• US Class Current: 600/544
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/398 Electrooculography [EOG], e.g. detecting nystagmus; Electroretinography [ERG]
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7455 characterised by tactile indication, e.g. vibration or electrical stimulation

Abstract

The method for simultaneously and concurrently identifying and quantifying a wide variety of types of facial electromyographic (EMG) and eye movement electrooculargraphic (EOG) activity, which naturally contaminate electroencephalographic (EEG) waveforms in order to significantly improve the accuracy of the calculation in real-time of the amplitude and/or coherence of any brainwave activity for any chosen frequency bandwidth for any number of electrode placements. This multi-level, widely or universally applicable, pre-defined pattern recognition artifact detection and correction system provides a method for enhancing EEG biofeedback training by detecting and eliminating any brief, contaminated epoch of EEG activity from being included in the calculation and analysis of the EEG signal. The method and apparatus disclosed herein make it possible to provide without any interruption visual, auditory and/or tactile feedback of a “true” EEG signal that through operant conditioning learning principles enables individuals to more quickly and easily learn to control their brainwave activity using neurofeedback.

Claims

1. A method for identifying and correcting the occurrence of any of a wide variety of different types of concurrent EOG and/or EMG artifacts of one or more EEG signals during EEG monitoring of an individual, the method comprising

collecting each of one or more individual signals from one or more specified EEG frequency bandwidths;

passing the signal as a data sample to an artifact detection system, the artifact detection system

applying a first wide bandpass filter to the data sample;

applying a digital spectrum analyzer to the filtered data sample;

testing for possible EOG and EMG artifacts; and

applying selected bandpass for each filter;

performing analysis to test for an artifact for each filter;

storing the last known value that does not represent an artifact;

determining whether an artifact is present in the data sample;

in the event an artifact is detected, substituting the last known value that does not reflect an artifact for the data containing the artifact;

forwarding the data sample to a signal corrector, the signal corrector calculating RMS amplitude; and

displaying a raw amplitude graph and a corrected amplitude graph.

2. The method of claim 1, further comprising the step of setting cutoff thresholds used in determining the occurrence of EOG artifacts to take into account the different signal strengths of the amplitude and variance of EOG activity in different bandwidths involving the naturally spontaneous and volitionally occurring activity of the monitored individual.

3. The method of claim 1, further comprising the step of setting cutoff thresholds used in determining the occurrence of EOG artifacts to take into account the different signal strengths of the amplitude and variance of EOG activity in different bandwidths of the monitored individual, the activity selected from the group comprising eye blinks, eye strain, eye closure and eye movement.

4. The method of claim 1, further comprising the step of setting cutoff thresholds used in determining the occurrence of EMG artifacts to take into account the different signal strengths of the amplitude, a ratio and variance of EMG activity in different bandwidths related to the naturally spontaneous and volitionally occurring activity of the monitored individual.

5. The method of claim 1, further comprising the step of setting cutoff thresholds used in determining the occurrence of EMG artifacts to take into account the variance of different signal strengths of the amplitude of EMG activity in a specific bandwidth of the monitored individual, the activity selected from the group comprising raising of the individual'"'"'s eyebrows and furrowing of the individual'"'"'s brow.

6. The method of claim 1, further comprising the step of setting cutoff thresholds used in determining the occurrence of EMG artifacts to take into account the ratio of the variance of the different signal strengths of the amplitude of EMG activity in different bandwidths related to the naturally spontaneous and volitionally occurring activity of the monitored individual, the activity selected from the group comprising squinting by the individual and straining of the muscles which surround the individual'"'"'s eyes.

7. The method of claim 1, further comprising the step of setting cutoff thresholds used in determining the occurrence of EMS artifacts to take into account the different signal strengths of the amplitude of EMG activity for a specific bandwidth related to the naturally spontaneous and volitionally occurring activity of the temporomandibular joint muscles.

8. The method of claim 1, further comprising the steps of identifying and correcting the EEG signal in real-time for any sudden or significant change in the amplitude or coherence of any one of more EEG signals during a brief epoch that does not naturally occur in the EEG waveform based on a cutoff threshold in order to take into account the occurrence of distortions and artifacts that could possibly occur related to external environmental electrical signals, EOG, EMG or other types of physiologically or environmentally based electrical signal activity.

9. The method of claim 1, wherein the step of applying a digital spectrum analyzer to the filtered data sample further comprises the step of analyzing the EEG signals using a Fast Fourier transform in order to compute signal amplitude values, variances and a ratio of the amplitude values or signal variances for specified bandwidths that are used in determining whether predetermined threshold values are exceeded that indicate the occurrence of an artifact.

10. The method of claim 1, further comprising the step of using pre-defined, universally applicable pattern recognition algorithms derived from the empirical observation of the natural and volitional occurrence of the at least one relative amplitude, ratio or variance of at least one pattern of different EEG bandwidths for different types of possible EOG and EMG artifacts.

11. A method for identifying and correcting the occurrence of any of a wide variety of different types of concurrent EOG and/or EMS artifacts of one or more EEG signals during EEG monitoring of an individual, the method comprising

collecting each of one or more individual signals from one or more specified EEG frequency bandwidths;

passing the signal as a data sample to an artifact detection system, the artifact detection system applying a first wide bandpass filter to the data sample;

applying a digital spectrum analyzer to the filtered data sample;

testing for possible EOG and EMG artifacts;

determining whether an artifact is present in the data sample;

in the event an artifact is detected, substituting the last known value that does not reflect an artifact for the data containing the artifact;

forwarding the data sample to a signal corrector, the signal corrector calculating RMS amplitude; and

displaying a raw amplitude graph and a corrected amplitude graph.

12. The method of claim 11, further comprising the step of setting cutoff thresholds used in determining the occurrence of EOG artifacts to take into account the different signal strengths of the amplitude and variance of EOG activity in different bandwidths involving the naturally spontaneous and volitionally occurring activity of the monitored individual.

13. The method of claim 11, further comprising the step of setting cutoff thresholds used in determining the occurrence of LOG artifacts to take into account the different signal strengths of the amplitude and variance of EOG activity in different bandwidths of the monitored individual, the activity selected from the group comprising eye blinks, eye strain, eye closure and eye movement.

14. The method of claim 11, further comprising the step of setting cutoff thresholds used in determining the occurrence of EMG artifacts to take into account the different signal strengths of the amplitude, a ratio and variance of EMG activity in different bandwidths related to the naturally spontaneous and volitionally occurring activity of the monitored individual.

15. The method of claim 11, further comprising the step of setting cutoff thresholds used in determining the occurrence of EMG artifacts to take into account the variance of different signal strengths of the amplitude of EMG activity in a specific bandwidth of the monitored individual, the activity selected from the group comprising raising of the individual'"'"'s eyebrows and furrowing of the individual'"'"'s brow.

16. The method of claim 11, further comprising the step of setting cutoff thresholds used in determining the occurrence of EMG artifacts to take into account the ratio of the variance of the different signal strengths of the amplitude of EMG activity in different bandwidths related to the naturally spontaneous and volitionally occurring activity of the monitored individual, the activity selected from the group comprising squinting by the individual and straining of the muscles which surround the individual'"'"'s eyes.

17. The method of claim 11, further comprising the step of setting cutoff thresholds used in determining the occurrence of EMG artifacts to take into account the different signal strengths of the amplitude of EMG activity for a specific bandwidth related to the naturally spontaneous and volitionally occurring activity of the temporomandibular joint muscles.

18. The method of claim 11, wherein the step of applying a digital spectrum analyzer to the filtered data sample further comprises the step of analyzing the EEG signals using a Fast Fourier transform in order to compute signal amplitude values, variances and a ratio of the amplitude values or signal variances for specified bandwidths that are used in determining whether predetermined threshold values are exceeded that indicate the occurrence of an artifact.

19. The method of claim 11, further comprising the step of using pre-defined, universally applicable pattern recognition algorithms derived from the empirical observation of the natural and volitional occurrence of the at least one relative amplitude, ratio or variance of at least one pattern of different EEG bandwidths for different types of possible EOG and EMG artifacts.

20. A method for identifying and correcting the occurrence of any of a wide variety of different types of concurrent EOG, EMI and/or environmentally generated artifacts of one or more EEG signals during EEG monitoring of an individual, the method comprising

collecting each of one or more individual signals from one or more specified EEG frequency bandwidths;

passing the signal as a data sample to an artifact detection system, the artifact detection system applying a selected bandpass for each filter;

performing analysis to test for an artifact for each filter;

storing the last known value that does not represent an artifact;

determining whether an artifact is present in the data sample;

in the event an artifact is detected, substituting the last known value that does not reflect an artifact for the data containing the artifact;

forwarding the data sample to a signal corrector, the signal corrector calculating RMS amplitude; and

displaying a raw amplitude graph and a corrected amplitude graph.

21. The method of claim 20, further comprising the steps of identifying and correcting the EEG signal in real-time for any sudden or significant change in the amplitude or coherence of any one of more EEG signals during a brief epoch that does not naturally occur in the EEG waveform based on a cutoff threshold in order to take into account the occurrence of distortions and artifacts that could possibly occur related to external environmental electrical signals, EOG, EMG or other types of physiologically or environmentally based electrical signal activity.