Sense position prediction for touch sensing methods, circuits and systems
View Patent ↗A method can include determining multiple sensed positions of an object path in a touch sense region; generating at least a first predicted position from the sensed positions; and filtering a sense position, including associating the sense position with the object path if it is within a first proximity to at least the first predicted position, and not associating the sense position with the object path if it is outside of at least the first proximity from the first predicted position.
1. A method, comprising:
determining multiple sensed positions of an object path in a touch sense region;
generating at least a first predicted position from the sensed positions; and
filtering a sense position, including
associating the sense position with the object path if it is within a first proximity to at least the first predicted position, and
not associating the sense position with the object path if it is outside of at least the first proximity from the first predicted position.
2. The method of claim 1 , wherein:
determining the multiple sensed positions includes generating Cartesian coordinates based on transmission electrodes and receiving electrodes of a mutual capacitance sense network.
3. The method of claim 1 , wherein:
generating the at least one predicted position includes
determining path vector values that project from one sensed position to a next sensed position,
generating a first prediction vector from the path vector values, and
determining the first predicted position by projecting the first prediction vector from one of the sensed positions.
4. The method of claim 3 , further including:
generating the at least one predicted position further includes
generating a second prediction vector that is a scalar of the first prediction vector, and
determining a second predicted position by projecting the second prediction vector from that last sensed position; and
associating the sense position with the object path if it is within a second proximity to the second predicted position, and
not associating the sense position with the object path if it is outside of the second proximity from the second predicted position.
5. The method of claim 1 , wherein:
generating at least a first predicted position from the sensed positions includes generating multiple predicted positions from the sensed positions;
associating the sense position with the object path if it is within predetermined proximities to the predicted positions; and
not associating the sense position with the object path if it is outside of the predetermined proximities to the predicted positions.
6. The method of claim 1 , wherein:
determining a velocity value for sensed objects; and
disabling the filtering of the sense position if the velocity if greater than a maximum velocity limit.
7. The method of claim 1 , wherein:
determining a velocity value for sensed objects; and
adjusting a speed of the filtering of the sense position according to the velocity value.
8. The method of claim 1 , wherein:
generating the at least one predicted position includes determining a predicted position based on at least one acceleration value derived from at least three sensed positions.
9. A touch sense system, comprising:
a processing section that includes
a sense section configured to receive object position data,
a prediction section configured to generate at least a first predicted position data from sensed object positions, and
a filter section configured to classify object position data according to a proximity to at least the first predicted position; and
a memory system configured to store at least the object position data and the predicted position data.
10. The system of claim 9 , wherein:
the processing section comprises
at least one processor configured to execute instructions stored in an instruction memory, and
an instruction memory configured to store instructions; wherein the prediction section comprises prediction instructions stored in the instruction memory, and
the filter section comprises filter instructions stored in the instruction memory.
11. The system of claim 9 , wherein:
the sense section comprises
a mutual capacitance interface having
a plurality of transmit outputs configured to output transmission signals, and
a plurality of receive inputs; and
a conversion section configured to generate object position coordinates in response to the transmission signals and values received on the receive inputs.
12. The system of claim 9 , wherein:
the filter section is configured to compare a value KL 2 to a value Δx 2 +Δy 2 ; wherein K is a constant, L is a proximity value, Δx is a difference between received sense position data and predicted position data along a first axis of a coordinate system, and Δy is a difference between the received sense position data and the predicted position data along a second axis of the coordinate system.
13. The system of claim 9 , wherein:
the prediction section is configured to generate at least one plurality of predicted position values based on an acceleration value derived from at least three previously sensed position values.
14. The system of claim 9 , wherein:
the filter section is configured to
associate a received sense position with an object path corresponding to previously received object position data if the received sense position is within a first proximity to the first predicted position, and
not associate the received sense position with the object path if the received sense position is not within the at least the first proximity to the first predicted position.
15. The system of claim 9 , further including:
a sensor array comprising a plurality of receive electrodes disposed in a first direction and a plurality of transmit electrodes disposed in a second direction.
16. A method, comprising:
determining multiple sensed positions of an object path in a touch sense region;
generating at least a first predicted position according to a non-linear function based on the sensed positions; and;
generating at least a first proximity value based on the sensed positions; and
classifying a new sense position according to at least the first predicted position and the first proximity value.
17. The method of claim 16 , wherein:
generating the first predicted position includes adding a length value to a last sensed position, the length value being based on at least a predicted difference; wherein
the predicted difference is a difference between two prior sensed positions, if the predicted difference is greater than or equal to a prior predicted difference, and
the predicted difference is a fraction of the difference between two prior sensed positions and the prior predicted difference, if the predicted difference is less than the prior predicted difference.
18. The method of claim 17 , wherein:
the length value is L i+1 2 , where
L i+1 2 =X i+1 2 +Y i+1 2
and X i+1 is a first predicted difference on an X-axis, Y i+1 is a second predicted difference on a Y-axis, and
X i+1 =Δx i , if Δx i ≧X i and X i+1 =K 1 *X i +K 2 *Δx i , if Δx i <X i ;
Y i+1 =Δy i , if Δy i ≧Y i and Y i+1 =K 1 *Y i +K 2 *Δy i , if Δy i <Y i ; and
Δx i is a difference between x coordinates of two prior sensed positions; Δy i is a difference between y coordinates of the two prior sensed positions; X i is a previous first predicted difference; Y i is a previous second predicted difference; and K 1 and K 2 are constants.
19. The method of claim 16 , wherein:
generating the first predicted position includes projecting a length value along a predicted angle from a last sensed position, the predicted angle being based on two previous path angles; wherein the previous path angles correspond to vectors between previous sensed positions.
20. The method of claim 16 , wherein:
generating the first predicted position includes calculating a predicted position based on an acceleration values derived from at least three prior sensed positions.