Hover detection for touchscreens

1. A method, comprising:

in response to receiving measured signal data detected by a sensor array of a device, creating a generated representation from the measured signal data;

comparing the generated representation with a measured representation of the measured signal data to create a correlation coefficient corresponding to a correlation between the generated representation and the measured representation of the measured signal data;

in response to the correlation coefficient exceeding a first threshold, detecting a hover event for the device; and

in response to the correlation coefficient not exceeding the first threshold, determining that the measured signal data is not indicative of the hover event.

2. The method of claim 1 , wherein creating the generated representation comprises:

creating the generated representation in real-time during operation of the sensor array detecting objects proximate a display of the device.

3. The method of claim 1 , comprising:

in response to detecting the hover event, transmitting a signal to the device to indicate that the hover event occurred.

4. The method of claim 3 , wherein the signal triggers the device to perform an operation determined based upon the hover event occurring.

5. The method of claim 1 , wherein:

creating the generated representation comprises creating a generated curve from the measured signal data, the measured representation comprises a measured curve corresponding to a plot of the measured signal data, and

comparing the generated representation to the measured representation comprises determining a similarity between the generated curve and the measured curve to create the correlation coefficient.

6. The method of claim 1 , comprising:

in response to the correlation coefficient not exceeding the first threshold, determining that the measured signal data comprises noise.

7. The method of claim 1 , comprising:

in response to detecting the hover event, performing position filtering using the measured signal data to determine a hover position associated with the hover event.

8. The method of claim 1 , comprising:

filtering the measured signal data to remove noise from the measured signal data to create filtered measured signal data;

performing a baseline update for the sensor array to create baseline sensor information;

modifying the filtered measured signal data based upon the baseline sensor information to create modified measured signal data; and

generating the measured representation using the modified measured signal data.

9. The method of claim 8 , comprising:

comparing an average of the modified measured signal data with a second threshold; and

in response to the average of the modified measured signal data exceeding the second threshold, performing hover and position detection to determine whether the hover event occurred and to identify a position of the hover event.

10. The method of claim 8 , comprising:

comparing an average of the modified measured signal data with a second threshold; and

in response to the average of the modified measured signal data not exceeding the second threshold, determining that the measured signal data is not indicative of the hover event.

11. The method of claim 8 , comprising:

comparing an average of the modified measured signal data with a second threshold;

in response to the average of the modified measured signal data not exceeding the second threshold, comparing the average of the modified measured signal data to a third threshold; and

in response to the average of the modified measured signal data exceeding the third threshold, determining and transmitting to the device a proximity of an object detected by the sensor array as the measured signal data.

12. The method of claim 8 , comprising:

comparing an average of the modified measured signal data with a second threshold;

in response to the average of the modified measured signal data not exceeding the second threshold, comparing the average of the measured signal data to a third threshold; and

in response to the average of the modified measured signal data not exceeding the third threshold, determining that no object has been detected by the sensor array as the measured signal data.

13. The method of claim 1 , comprising:

in response to the correlation coefficient not exceeding the first threshold, determining and transmitting to the device a proximity of an object detected by the sensor array as the measured signal data.

14. The method of claim 1 , wherein creating the generated representation comprises:

creating the generated representation based upon a best-fit Gaussian curve relative to the measured signal data.

15. A non-transitory machine-readable storage medium comprising machine executable code, which when executed by a machine, causes the machine to:

construct a Gaussian distribution using measured signal data detected by a sensor array of a device;

calculate a Pearson correlation coefficient between the Gaussian distribution and a measured signal profile of the measured signal data, wherein the Pearson correlation coefficient represents a similarity between the Gaussian distribution and the measured signal profile;

in response to the Pearson correlation coefficient exceeding a first threshold, detect a hover event of an object with respect to the sensor array; and

in response to the Pearson correlation coefficient not exceeding the first threshold, determine that the measured signal data is not indicative of the hover event.

16. The non-transitory machine-readable storage medium of claim 15 , wherein the machine executable code causes the machine to:

identify a first set of sensors that detected a subset of the measured signal data;

identify a second set of sensors that did not detect the measured signal data;

form an extended vector of measured signal data by mirroring the subset of the measured signal data as a mirrored subset of the measured signal data for association with the second set of sensors; and

utilize the extended vector as the measured signal profile.

17. The non-transitory machine-readable storage medium of claim 15 , wherein the machine executable code causes the machine to:

in response to determining that the measured signal data was detected by a threshold number of edge sensors of the sensor array, calculate one or more virtual sensors with virtual sensor signal data to include within the measured signal data.

18. The non-transitory machine-readable storage medium of claim 15 , wherein the machine executable code causes the machine to:

utilize a shape criterion and a mass criterion to identify a candidate for a global maximum search to identify a global maximum value of the measured signal profile, wherein the candidate for the global maximum is determined as an index of a sensor with a largest mass of signals around the sensor using the mass criterion and the shape criterion.

19. A system, comprising:

a sensor array of sensors configured to measure capacitance signal values as sets of measured signal data; and

a hover detection module configured to:

receive a set of measured signal data detected by the sensor array;

create a generated representation from the set of measured signal data;

compare the generated representation with a measured representation of the set of measured signal data to create a correlation coefficient corresponding to a correlation between the generated representation and the measured representation of the set of measured signal data;

in response to the correlation coefficient exceeding a first threshold, detect a hover event of an object hovering relative to the sensor array; and

in response to the correlation coefficient not exceeding the first threshold, determine that the set of measured signal data is not indicative of the hover event.

20. The system of claim 19 , wherein the hover detection module calculates a position of the hover event as a vertex of a generated representation in response to the correlation coefficient exceeding the first threshold.