ELECTRODE CONTACT QUALITY

1 . A device comprising:

at least one electrode configured to be attached to a user and to detect brainwave activity from the user; and

a hardware processor comprising an electroencephalogram (EEG) application configured to measure a voltage of the electrode, to compute a derivative of the voltage of the electrode, to compute a coefficient of variation from the derivative of the voltage, and to determine a quality of contact of the electrode to the user based on the coefficient of variation.

2 . The device of claim 1 , wherein the hardware processor is configured to determine a maximum coefficient of variation and a minimum coefficient of variation for the electrode.

3 . The device of claim 2 , wherein the hardware processor is configured to determine that the coefficient of variation is between the minimum coefficient of variation and the maximum coefficient of variation, and to identify the voltage as valid and a contact of the electrode as good quality in response to determining that the coefficient of variation is between the minimum coefficient of variation and the maximum coefficient of variation.

4 . The device of claim 2 , wherein the hardware processor is configured to determine that the coefficient of variation is between the minimum coefficient of variation and the maximum coefficient of variation, and to identify the voltage as not valid and a contact of the electrode as bad quality in response to determining that the coefficient of variation outside a range between the minimum coefficient of variation and the maximum coefficient of variation.

5 . The device of claim 1 , wherein the hardware processor is configured to compute the standard deviation of the derivative of the voltage of the electrode, to compute the mean of the derivative of the voltage of the electrode, and to compute the coefficient of variation of the electrode by dividing the standard deviation of the derivative of the voltage of the electrode by the mean of the derivative of the voltage of the electrode.

6 . The device of claim 1 , wherein the quality of contact includes a Boolean value, the Boolean value including a good quality and a bad quality.

7 . The device of claim 6 , wherein the hardware processor is configured to determine a minimum false time duration as a time for a good contact quality of the electrode before identifying a bad contact quality of the electrode.

8 . The device of claim 7 , wherein the hardware processor is configured to identify the bad contact quality of the electrode in response to identifying bad contact quality for a period of time exceeding a predefined number of voltage computation cycles.

9 . The device of claim 1 , further comprising:

a camera configured to capture a reference identifier from a physical object,

wherein the processor further comprises an augmented reality application configured to identify a virtual object associated with the reference identifier, to display the virtual object in a display of the device, in response to a relative movement between the device and the physical object caused by a user, to modify the virtual object based on the quality of contact of the electrode to the user.

10 . The device of claim 1 , wherein the EEG application is configured to identify a change in a state of mind of the user of the device, wherein the augmented reality application is configured to modify the virtual object based on the change in the state of mind of the user of the device.

11 . A method comprising:

measuring a voltage of an electrode attached to a user, the electrode configured to detect brainwave activity of the user;

computing a derivative of the voltage of the electrode, using a hardware processor;

computing a coefficient of variation from the derivative of the voltage; and

determining a quality of contact of the electrode to the user based on the coefficient of variation.

12 . The method of claim 11 , further comprising:

determining a minimum coefficient of variation and a maximum coefficient of variation for the electrode.

13 . The method of claim 12 , further comprising:

determining that the coefficient of variation is between the minimum coefficient of variation and the maximum coefficient of variation; and

identifying the voltage as valid and a contact of the electrode as good quality in response to determining that the coefficient of variation is between the minimum coefficient of variation and the maximum coefficient of variation.

14 . The method of claim 12 , further comprising:

determining that the coefficient of variation is between the minimum coefficient of variation and the maximum coefficient of variation; and

identifying the voltage as not valid and a contact of the electrode as bad quality in response to determining that the coefficient of variation outside a range between the minimum coefficient of variation and the maximum coefficient of variation.

15 . The method of claim 11 , further comprising:

computing the standard deviation of the derivative of the voltage of the electrode;

computing the mean of the derivative of the voltage of the electrode; and

computing the coefficient of variation of the electrode by dividing the standard deviation of the derivative of the voltage of the electrode by the mean of the derivative of the voltage of the electrode

16 . The method of claim 11 , wherein the quality of contact includes a Boolean value, the Boolean value including a good quality and a bad quality.

17 . The method of claim 16 , further comprising:

determining a minimum false time duration as a time for a good contact quality of the electrode before identifying a bad contact quality of the electrode.

18 . The method of claim 17 , further comprising:

identifying the bad contact quality of the electrode in response to identifying bad contact quality for a period of time exceeding a predefined number of voltage computation cycles.

19 . The device of claim 11 , further comprising:

a camera configured to capture a reference identifier from a physical object,

wherein the processor further comprises an augmented reality application configured to identify a virtual object associated with the reference identifier, to display the virtual object in a display of the device, in response to a relative movement between the device and the physical object caused by a user, to modify the virtual object based on the quality of contact of the electrode to the user.

20 . A non-transitory machine-readable medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising:

detecting brainwave activity from the user with at least one electrode connected to a user; and

computing a voltage of the electrode using a hardware processor;

computing a derivative of the voltage of the electrode;

computing a coefficient of variation from the derivative of the voltage; and

determining a quality of contact of the electrode to the user based on the coefficient of variation.