Time domain-based methods for noninvasive brain-machine interfaces
A noninvasive brain computer interface (BCI) system includes an electroencephalography (EEG) electrode array configured to acquire EEG signals generated by a subject. The subject observes movement of a stimulus. A computer is coupled to the EEG electrode array and configured to collected and process the acquired EEG signals. A decoding algorithm is used that analyzes low-frequency (delta band) brain waves in the time domain to continuously decode neural activity associated with the observed movement.
1. A method of decoding neural activity for a brain computer interface (BCI) system, comprising the steps of:
recording noninvasively acquired electroencephalography (EEG) signals of a subject in a time domain when the subject observes movement of a stimulus while the subject is simultaneously imagining movement of a limb tracking the movement of the stimulus;
continuously decoding only the recorded EEG signals having a frequency of less than 4 Hz and in the time domain associated with the observed movement and the imagined movement; and
correlating fluctuations in amplitude of the decoded recorded EEG signals with an intent of the subject.
2. The method of claim 1 , comprising a further step of generating command signals for controlling movement of a device operably associated with the BCI system, wherein the command signals are associated with the intent of the subject.
3. The method of claim 2 , wherein the device is a cursor displayed on a display, the cursor movable in two dimensions on the display based on EEG signals of the subject.
4. The method of claim 2 , wherein the device is a prosthetic device movable in three dimensions based on EEG signals of the subject.
5. The method of claim 1 , wherein the subject is imagining movement of the limb in at least two dimensions when tracking the movement of the stimulus.
6. The method of claim 5 , wherein the decoded EEG signals are associated with observed or imagined hand movement in a human subject.
7. The method of claim 5 , wherein the decoded EEG signals are associated with observed or imagined bipedal movement in a human subject.
8. A method of identifying a neural biomarker of a movement condition, comprising the steps of:
recording noninvasively acquired electroencephalography (EEG) signals of a subject in a time domain when the subject observes movement of a stimulus while the subject is simultaneously imagining movement of a limb tracking the movement of the stimulus;
continuously decoding only the recorded EEG signals having a frequency of less than 4 Hz and in the time domain associated with the observed movement and the imagined movement; and
correlating fluctuations in amplitude of the decoded recorded EEG signals with a biomarker of a movement condition.
9. The method of claim 8 , wherein the movement condition is associated with a movement disorder due to a neurological condition, a developmental disorder, or abnormal aging.
10. The method of claim 8 , wherein the subject is imagining movement of the limb in at least two dimensions when tracking the movement of the stimulus.
11. The method of claim 10 , wherein the decoded EEG signals are associated with observed or imagined hand movement in a human subject.
12. The method of claim 10 , wherein the decoded EEG signals are associated with observed or imagined bipedal movement in a human subject.