EEG control of devices using sensory evoked potentials
An EEG control of devices using Sensory Evoked Potentials (SEPs) (e.g., visually-evoked potentials), is disclosed. In some embodiments, a system receives a plurality of EEG signal samples; generates a stimulus locked average signal using the plurality of EEG signal samples; and determines whether the plurality of EEG signal samples are evoked in response to a pattern of stimulus.
1. A system, comprising:
a processor configured to:
generate a stimulus-locked average signal of a plurality of EEG signal samples; and
determine whether the plurality of EEG signal samples are evoked in response to a pattern of stimulus events, wherein the determination of whether the plurality of EEG signal samples are evoked in response to a pattern of stimulus events is performed by multiplying the stimulus-locked average by a previously created prototype average; and
a memory coupled to the processor and configured to provide the processor with instructions.
2. The system recited in claim 1 , wherein the pattern of stimulus events includes a plurality of light sources emitting light flashes periodically at a fixed frequency.
3. The system recited in claim 1 , wherein the pattern of stimulus events includes a plurality of light sources emitting light flashes periodically, including a first light source emitting light flashes a first fixed frequency and a second light source emitting light flashes at a second fixed frequency.
4. The system recited in claim 1 , wherein the pattern of stimulus events includes a light source emitting light flashes periodically at a plurality of frequencies, including a first light flash at a first frequency and a second light flash at a second frequency.
5. The system recited in claim 1 , wherein the pattern of stimulus events includes a plurality of light sources emitting light flashes at non-periodic frequencies.
6. The system recited in claim 1 , wherein the pattern of stimulus events includes one or more of the following: a pattern of visual stimulus events, a pattern of audio stimulus events, and a pattern of tactile stimulus events.
7. The system recited in claim 1 , wherein the pattern of stimulus events includes a plurality of light sources that each provides independent flashing light events.
8. The system recited in claim 1 , wherein the plurality of EEG signal samples are evoked as an involuntary response of a user of the system.
9. The system recited in claim 1 , wherein the plurality of EEG signal signals include voluntary EEG signal responses.
10. The system recited in claim 1 , wherein each of the plurality of EEG signal samples includes a plurality of sample points.
11. The system recited in claim 1 , wherein each of the plurality of EEG signal samples is a time series of EEG signal samples.
12. The system recited in claim 1 , wherein the stimulus-locked average signal includes a flash-locked average signal.
13. The system recited in claim 1 , wherein the determination of whether the plurality of EEG signal samples are evoked in response to a pattern of stimulus events is performed by comparing the stimulus-locked average to a threshold.
14. The system recited in claim 1 , wherein the determination of whether the plurality of EEG signal samples are evoked in response to a pattern of stimulus events is performed by multiplying the stimulus-locked average by the prototype average that adapts to the user's EEG signals.
15. The system recited in claim 1 , wherein the determination of whether the plurality of EEG signal samples are evoked in response to a pattern of stimulus events is performed by integrating the EEG signal data to generate a result, and comparing the result to a threshold.
16. The system recited in claim 1 , wherein the determination of whether the plurality of EEG signal samples are evoked in response to a pattern of stimulus events is performed using a time domain classifier.
17. The system recited in claim 1 , wherein the determination of whether the plurality of EEG signal samples are evoked in response to a pattern of stimulus events is performed in real-time.
18. The system recited in claim 1 , wherein the processor is further configured to:
determine whether a user of the system is looking at a first light source.
19. The system recited in claim 1 , wherein the processor is further configured to:
calculate a first peak value of the stimulus-locked average signal, wherein the first peak value is determined based on maximum value minus a minimum value of the stimulus-locked average signal; and
compare the first peak value with a threshold.
20. The system recited in claim 1 , wherein the processor is further configured to:
correlate the plurality of EEG signal samples with the pattern of stimulus events using a time offset based on stimulus timing.
21. The system recited in claim 1 , wherein the processor is further configured to:
train based on a first user to determine a first signature signal to assist in correlating the plurality of EEG signal samples with the pattern of stimulus events for the first user.
22. The system recited in claim 1 , further comprising:
a plurality of electrodes including an active EEG electrode and a reference EEG electrode, wherein the plurality of electrodes detect the plurality of EEG signal samples.
23. The system recited in claim 1 , wherein the processor is further configured to:
provide a control signal based on a determination of whether the plurality of EEG signal samples are evoked in response to the pattern of stimulus events.
24. The system recited in claim 1 , wherein the processor is further configured to:
provide a control signal to a device based on a determination of whether the plurality of EEG signal samples are evoked in response to the pattern of stimulus events, wherein the device includes one or more of the following: an entertainment system, an educational system, a medical system, an automobile system, and a computer executing an application.
25. A method, comprising:
measuring a plurality of EEG signal samples using a bio-signal sensor;
generating a stimulus-locked average signal using the plurality of EEG signal samples using a processor; and
determining whether the plurality of EEG signal samples are evoked in response to a stimulus using the processor, wherein the determination of whether the plurality of EEG signal samples are evoked in response to a pattern of stimulus events is performed by multiplying the stimulus-locked average by a previously created prototype average.
26. The method recited in claim 25 , wherein the determination of whether the plurality of EEG signal samples are evoked in response to a pattern of stimulus events is performed by multiplying the stimulus-locked average by the prototype average that adapts to the user's EEG signals.
27. A computer program product, the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for:
record a plurality of EEG signal samples;
generate a stimulus-locked average signal using the plurality of EEG signal samples; and
determine whether the plurality of EEG signal samples are evoked in response to a stimulus, wherein the determination of whether the plurality of EEG signal samples are evoked in response to a pattern of stimulus events is performed by multiplying the stimulus-locked average by a previously created prototype average.
28. The computer program product recited in claim 27 , wherein the determination of whether the plurality of EEG signal samples are evoked in response to a pattern of stimulus events is performed by multiplying the stimulus-locked average by the prototype average that adapts to the user's EEG signals.