System and method to measure capacitance of capacitive sensor array

Information

  • Patent Grant
  • 8321174
  • Patent Number
    8,321,174
  • Date Filed
    Friday, September 26, 2008
    16 years ago
  • Date Issued
    Tuesday, November 27, 2012
    12 years ago
Abstract
A system and method for measuring capacitance of a capacitive sensor array is disclosed. Upon measuring the capacitance, position information with respect to the sensor array may be determined. A column, a first row, and a second row of a capacitive sensor array may be selected. The first row and the second row intersect with the column of the capacitive sensor array. A differential capacitance between the first row and the second row may be measured. The differential capacitance may be utilized in determining a location of an object proximate to the capacitive sensor array.
Description
RELATED U.S. APPLICATIONS

This application is related to commonly assigned, co-pending patent application Ser. No. 12/167,552, filed on Jul. 3, 2008, entitled “Method For Normalizing Signal From A High-Impedance Array of Capacitive Sensors,” and hereby incorporated by reference in its entirety.


This application is related to commonly assigned, co-pending patent application Ser. No. 12/167,494, filed on Jul. 3, 2008, entitled “Method For Improving Scan Time And Sensitivity In Touch Sensitive User Interface Device,” and hereby incorporated by reference in its entirety.


FIELD OF INVENTION

Embodiments of the present invention generally relate to capacitive sensor arrays.


BACKGROUND OF THE INVENTION

As computing technology has developed, user interface devices have advanced correspondingly. User interfaces have become increasingly significant in the usability of a computing device.


One particular user interface becoming increasingly popular is the touch screen or track pad which uses an array of capacitive sensors using high impedance capacitance substrates. The current, based on the change of the capacitance at the intersection of a row and a column of the array, which varies depending on the presence or absence of a touch, e.g., a finger, etc., is measured.


Row and/or columns are scanned sequentially and independently, one by one across the array by a microprocessor. The microprocessor may start by measuring the capacitance at a first column and a first row, then measure the capacitance for the intersection of the first column and a second row, and then measure each subsequent intersection in the capacitive sensor array. Thus, if there are 10 rows and 10 columns, a total of 100 measurements of capacitance may be obtained and stored by microprocessor. Based on the measurements, a centroid corresponding to the finger location is then determined by the microprocessor.


The measuring of each intersection of each row and column may result in the measurements being subject to variations in the physical properties of the sensor array. For example, temperature changes can increase or decrease the capacitance.


Further, measuring capacitance means that the measured range includes the absolute value of the capacitance. For example, if the capacitance is 8 picofarads (pF) without a finger present and a capacitance of 8.1 pF indicates a touch, the measurement circuit may be calibrated to measure a range of 1 to 10 pF for instance while the dynamic range is only 0.1, this leads to low resolution. The centering of the measurement window by using current compensation may avoid this low resolution. The current compensation involves using a current source to balance out or subtract the base capacitance. The current source is used to provide a current based on the baseline capacitance and thereby subtract out the baseline capacitance from capacitance measurements. The microprocessor accesses and loads the baseline values into a programmable current source before each measurement of each row and column intersection. This current compensation uses extra hardware which increases costs and is slower as additional operations and settling times increase the time for each scan.


Thus, capacitive sensor systems may be susceptible to capacitive variations and utilize absolute value capacitive measurements resulting in less accurate position information.


SUMMARY OF THE INVENTION

Accordingly, embodiments of the present invention are directed to a system and method for determining position information e.g., with respect to a touch sensitive array. Position information is determined based on differential capacitance measurements in one embodiment. The differential capacitance measurements may be with respect to adjacent rows and/or columns of the array and are substantially immune to variations (e.g., temperature changes, dielectric changes, etc.) of a capacitive sensor array. The differential capacitive measurements further facilitate increased resolution and require fewer measurements thereby making scans employing a capacitive sensor array faster and more precise.


More specifically, an embodiment of the present invention is directed to a method for determining position information. The method includes selecting a column, a first row, and a second row of a capacitive sensor array. The first row and second row intersect with the column of the capacitive sensor array. Further, the first and second row may be selected as an adjacent pair or a distant pair (e.g., separated by at least one other row). The method further includes measuring a differential capacitance between the first row and the second row and utilizing the differential capacitance in determining a location of an object proximate to the capacitive sensor array. The location of the object may be determined by computing capacitance values for each row and column intersection based on the differential capacitance measurements.


Another embodiment of the present invention is directed to a circuit or electronic system for determining position information. The system includes a sensor array controller for selecting each of a plurality of rows and each of a plurality of columns for measuring a differential capacitance. The differential capacitance may include the difference in capacitance between two adjacent rows and thus variations (e.g., temperature effects, dielectric variations, etc.) in the capacitive sensor array may be substantially removed. The capacitive sensor array is operable to be controlled by the sensor array controller for detecting a presence of an object proximate to the sensor array. The system further includes a data storage module for storing a plurality of differential capacitive measurements and a data processing module for processing the plurality of differential capacitive measurements to determine the position of an object proximate to a capacitive sensor array.


In one embodiment, the circuit for measuring the capacitance across two rows or columns is differential in nature thereby leading to a direct differential measurement which is supplied to a processor for position determination. By eliminating the base capacitance of the array in this fashion, more resolution applied via the capacitive sensor to the expected dynamic range for a touch. In another embodiment, however, absolute capacitance measurements can be taken and supplied to the processor which computes the different values via software.


In this fashion, embodiments of the present invention facilitate more precise capacitance measurements and therefore more accurate object location detection. Embodiments of the present invention further facilitate simplified capacitive sensor array systems by removing the necessity for current compensation circuitry. Moreover, embodiments of the present invention allow more frequent scans by reducing the number of measurements performed for each column.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 shows block diagram of an exemplary system for determining position information, in accordance with another embodiment of the present invention.



FIG. 2 shows block diagram of an exemplary capacitive sensor array, in accordance with another embodiment of the present invention.



FIG. 3 shows block diagram of an exemplary implementation of a system for determining position information, in accordance with an embodiment of the present invention.



FIG. 4 shows an exemplary graph of capacitance measurements, in accordance with an embodiment of the present invention.



FIG. 5 shows an exemplary system for determining position information, in accordance with an embodiment of the present invention.



FIG. 6 shows a flowchart of an exemplary method for determining position information, in accordance with an embodiment of the present invention.





DESCRIPTION OF THE INVENTION

Reference will now be made in detail to embodiments of the claimed subject matter, examples of which are illustrated in the accompanying drawings. While the invention will be described in conjunction with embodiments, it will be understood that they are not intended to limit the claimed subject matter to these embodiments. On the contrary, the claimed subject matter is intended to cover alternatives, modifications and equivalents, which may be included within the spirit and scope of the claimed subject matter as defined by the claims. Furthermore, in the detailed description of the present invention, numerous specific details are set forth in order to provide a thorough understanding of the claimed subject matter. However, it will be obvious to one of ordinary skill in the art that the claimed subject matter may be practiced without these specific details. In other instances, well known methods, procedures, components, and circuits have not been described in detail as not to unnecessarily obscure aspects of the claimed subject matter.


EXAMPLE SYSTEMS


FIGS. 1, 3, and 5 illustrate example components used by various embodiments of the present invention. Although specific components are disclosed in circuits or systems 100, 300, and 500 it should be appreciated that such components are examples. That is, embodiments of the present invention are well suited to having various other components or variations of the components recited in systems 100, 300, and 500. It is appreciated that the components in systems 100, 300, and 500 may operate with other components than those presented, and that not all of the components of systems 100, 300, and 500 may be used to achieve the goals of systems 100, 300, and 500.


Further, systems 100, 300, and 500 include components or modules that, in various embodiments, are carried out by software, e.g., a processor under the control of computer-readable and computer-executable instructions. The computer-readable and computer-executable instructions reside, for example, in data storage features such as computer usable memory, removable storage, and/or non-removable storage. The computer-readable and computer-executable instructions are used to control or operate in conjunction with, for example, a processing unit. It should be appreciated that the aforementioned components of systems 100, 300, and 500 can be implemented in hardware or software or in a combination of both.



FIG. 1 shows block diagram of an exemplary system for determining position information, in accordance with another embodiment of the present invention. System 100 includes clock source 102, buffer 142, inverter 140, row multiplexers 104 and 130, column multiplexers 106 and 132, row capacitors 108 and 128, column capacitors 110 and 126, measurement capacitors 112 and 124, current sampler 116, current to voltage converter 118, analog to digital converter (ADC) 120, and microprocessor 122. Circuit 100 measures the differential current based on the difference in capacitance of measurement capacitors 112 and 124.


Clock source 102 is coupled to buffer 142, inverter 140, and current sampler 116. Buffer 142 is coupled to row multiplexer 104. Inverter 140 is coupled to row multiplexer 130. Row multiplexers 104 and 130 thus receive clock signals. The selection of rows and columns via row multiplexers 130 and 104 and column multiplexers 106 and 132 allows current sampler 116 to measure a differential current between two rows of a capacitive sensor array. It is appreciated that clock source 102, buffer 142, and inverter 140 may be interchanged with a component having an inverting and non-inverting stage. It is further appreciated that the coupling of current sampler 116 and clock source 102 may be optional or current sampler 116 may be coupled to a microprocessor (e.g., microprocessor 122) or some external control.


In one embodiment, current sampler 116 provides synchronous rectification which is represented by a switch which becomes closed only on the positive transition of a clock signal from clock source 102. Current sampler 116 may be a switching circuit. Current to voltage converter 118 converts the measured current to a voltage for input to ADC 120. ADC 120 converts the analog voltage to a digital signal for input to microprocessor 122.


Microprocessor 122 controls row multiplexers 104 and 130 and column multiplexers 106 and 132, sets conversion times and collects the data from the capacitive sensor array. Microprocessor 122 may utilize column multiplexers 106 and 132 to select a single column of capacitive sensor array (e.g., an indium tin oxide (ITO) sensor array) and utilizes row multiplexers 104 and 130 to select a pair of rows. Of course the role of columns and rows can be switched in accordance with embodiments of the present invention and any discursion herein regarding a particular scan order is merely a convenience for illustration. The selection of two different rows in combination with the clock signal and inverted clock signal (e.g., via inverter 140) allows current to flow in opposite directions though measurement capacitors 112 and 124. The opposite current flow results in a current difference flowing into current sampler 116. That is, current sampler 116 receives the summation of the currents (e.g., in opposite directions) or a differential current. This differential current reflects the difference in the capacitance of measurement capacitors 112 and 124. For example, if the capacitance of capacitor 112 is greater than the capacitance of capacitor 124, there may be a net positive current remaining and measured by the current sampler 116.


The differential current measured is independent of physical variations on the capacitive sensor array that are common to both measured capacitors. For example, a temperature variation which uniformly impacts the capacitive sensor arrays may be substantially cancelled because both measurements capacitors 112 and 124 may be affected by the temperature change which thereby may be subtracted out. Similarly, other physical variations (e.g., dielectric changes, changes in pressure, etc.) that impact the array in general are substantially removed from the differential current measurements.


The measuring of differential currents thereby reduces the corresponding dynamic range of the measurement chain. Due to the differential nature of the current measurements only the differences are measured which means the total dynamic range of the measurement circuit may be much smaller and more finely tuned to the range of expected capacitance variations of a touch. That is, embodiments of the present invention provide for zero current centered measurements. For example, where the difference in capacitance (as measured based on the current) is 0.1 pF to register a touch instead of an absolute measurement of 8.1 pF, the dynamic range can be tuned to measure small variations (e.g., a range of 0-0.5 pF instead of 0-10 pF). It is appreciated that the differential measurements of embodiments of the present invention thereby remove the necessity of a current source and additional circuitry for providing current compensation. Embodiments of the present invention may thus be simpler and more reliable with increase resolution.


Further, the more finely tuned dynamic range facilitates much higher resolution. For example, if ADC 120 has 10 output bits for communicating a value to microprocessor, with embodiments of the present invention the 10 bits may be used to communicate values with a range of 1 pF instead of a range of 5 or 10 pF. Accordingly, embodiments of the present invention facilitate increased accuracy and resolution of measurements.


In one embodiment, the pairs of rows may be adjacent as microprocessor 122 goes through each column of a capacitive sensor array. That is, microprocessor 122 may select pairs of adjacent rows for making differential measurements. For example, microprocessor 122 may select column C0, then obtain differential measurements between rows R0 and R1, then R1 and R2, the R2 and R3, all the way up to R(N−1) and R(N).


However, row measurements may not necessarily be across adjacent rows. In another embodiment, the pairs of rows may be distant (e.g., separated by at least one other row) as microprocessor 122 goes through each column of a capacitive sensor array. That is, microprocessor 122 may select a first row and measure a differential capacitance between the first row and each of the other rows of the capacitive sensor array for each column. For example, microprocessor may select column C0, then get differential measurements between row R0 and R1, then rows R0 and R2, then rows R0 and R3, all the way up to rows R0 and RN. Embodiments of the present invention may further include an extra row and column to be used as a control (e.g., baseline) for differential measurements, e.g., a dummy row.


The scanning of the rows in pairs results in N−1 measurements per each column in a capacitive sensory array having N rows. That is, the scanning of the rows in pairs means that one less measurement is made per column, which decreases the time to scan the capacitive sensor array. For example, where a capacitive sensor array has 10 rows and 10 columns, 9 differential measurements for each of the 10 columns will be made. This results in a total of 90 (e.g., 9 differential measurements×10 columns) differential measurements being made. It is appreciated that a measurement for each row and column intersection would result in 100 measurements (e.g., 10 rows×10 columns). More generally, a capacitive sensor array with N row and M columns will have N−1 measurements per column and N−1×M measurements in total in accordance with embodiments of the present invention.


Microprocessor 122 further analyzes the data from the capacitive sensor array. Based on the differential current measurements and corresponding differential capacitance values, microprocessor 122 can determine the centroid of an object relative to the capacitive sensor array. In one embodiment, microprocessor 122 integrates the differential capacitive values going down each column to create a curve of the total capacitance at each row and column intersection (e.g., See FIG. 4). The integration may be then used for position determination. The curve may be further adjusted by adding the absolute value of the lowest negative number to each capacitance value thereby shifting the curve up to assist in locating a centroid. In another embodiment, microprocessor 122 may execute a method of searching the differential values for locations where the differential values change from positive to negative (e.g., cross zero).



FIG. 2 shows block diagram of an exemplary capacitive sensor array, in accordance with another embodiment of the present invention. Capacitive sensor array 275 includes rows R0-RN and columns C0-CN. Multiplexers 104, 106, 130, and 132 may be used to select respective pairs of rows and columns as microprocessor 122 scans each pair of rows and the corresponding column intersection.


As described herein, scanning of capacitive sensor array 275 may be based on differential measurements of adjacent pairs. For example, column C0282 may be selected and differential measurements may be made with row R0280 and row R1278, then row R1278 and row R2284, then row R2284 and row R3286, all the way up to row R(N−1) 288 and row RN 290. As discussed herein, the role of the columns and rows can be reversed in accordance with embodiments of the present invention.


As described herein, scanning of capacitive sensor array 275 may also be based on differential measurements of distant pairs (e.g., separated by at least one other row). For example, column C0282 may be selected and differential measurements may be made with row R0280 and row R1278, then row R0280 and row R2284, then row R0280 and row R3286, all the way up to row R0280 and row RN 290.



FIG. 3 shows block diagram of an exemplary implementation of a system for determining position information, in accordance with an embodiment of the present invention. System 300 includes clock1370, clock2372, voltage rail 334 (e.g., Vcc), row multiplexers 304 and 330, column multiplexers 306 and 332, row capacitors 308 and 328, column capacitors 310 and 326, measurement capacitors 312 and 324, switches 340-350, amplifiers 310 and 356, resistor 354, capacitor 352, reference voltage (Vref) 358, and analog to digital converter (ADC) 360. Circuit 300 measures the differential current based on the difference in capacitance of measurement capacitors 312 and 324. Arrows 374 reflect an exemplary current flow.


System 300 operates in a substantially similar manner to system 100. Switches 342, 344, and 350 are coupled to clock1370. Switches 340, 346, and 348 are coupled to clock2372. It is appreciated that clock1370 and clock2372 may be inverses of each other. Row multiplexers 330 and 304 and column multiplexers 306 and 332 may be controlled by a microprocessor (e.g., microprocessor 122).


Amplifier 310 in combination with switches 348 and 350 acts a current sampler (e.g., current sampler 116) to sample differential current from measurement capacitors 312 and 324. The differential current measurement signal then passes to capacitor 352, resistor 354, and amplifier 358. Amplifier 358 has reference voltage (Vref) 358 as an input. The combination of capacitor 352, resistor 354, and amplifier 358 acts to convert the current to a voltage for input to ADC 360. ADC 360 may then convert the voltage to a digital signal for input to a microprocessor (e.g., microprocessor 122).



FIG. 4 shows exemplary graphs of capacitance measurements, in accordance with an embodiment of the present invention. Each graph includes a vertical axis corresponding to the capacitance and horizontal axis corresponding to position (p) (e.g., row). Curve 414 corresponds to the measured differential capacitance for each position (e.g., row). A touch position is detected at position 416 where curve 414 crosses the axis. Line 412 represents exemplary integrated capacitance values measured over a plurality of row and column intersections (e.g., for a give column). Line 412 may be expressed by the equation:







f


(
p
)


=


















i



p








Where








i



p






is the differential capacitance measured at each row and column intersection for the given column and reported to the processor. The function ƒ(p) is the summation of each








i



p






which results in the capacitance values as depicted by line 412. The function ƒ(p) may correspond to the capacitance values for a single column. The summation or integration may be performed by a processor (e.g., processor 122). Further, the processor detects a touch position by analyzing the curve of the function ƒ(p).


Regions 402 and 410 corresponds to areas where the differential capacitive measurements have minimal to zero difference and may correspond to row and column intersections where an object (e.g., finger) is not present.


Region 406 corresponds to an area where the capacitance on each measurement capacitor (e.g., measurement capacitors 112 and 124) is substantially similar where there is no object nearby and thus the differential capacitance is minimal or zero. Region 406 may correspond to the centroid where an object is present over or on top of a capacitive sensor array (e.g., capacitive sensor array 275). Region 404 corresponds to locations where the differential capacitance is increasing (e.g., the row and column intersections on the edge of an object).


Region 408 corresponds to locations where the differential capacitance is decreasing (e.g., the row and column intersections on the edge of an object). It is appreciated that the increasing or decreasing nature of the differential capacitive values may be based on the selection of current flow (e.g., as depicted in FIG. 3).



FIG. 5 shows an exemplary system for determining position information, in accordance with an embodiment of the present invention. System 500 includes sensor array controller 502, data processing module 508, data storage 510, sensor array 512, and communications bus 514. The blocks of system 500 may be carried out or performed by system for determining position information (e.g., system 100 or 300). Capacitive sensor array 512 is operable to be controlled by the sensor array controller for detecting the presence of an object proximate to the sensor array.


Sensor array controller 502 selects each of a plurality of rows and each of a plurality of columns for measuring a differential capacitance. Sensor array controller 502 includes row selector 504 and column selector 506. Sensor array controller 502 may use the column selector 506 to select each column of capacitive sensor array and use row selector 504 to select pairs of row for measuring differential capacitances. It is appreciated that embodiments of the present invention may also select a row and pairs of columns.


As described herein, the differential capacitance may be measured by a pair of adjacent rows or a pair of distant rows (e.g., rows separated by at least one other row). For example, differential capacitances may be measured for row 0 and row 1, row 1 and row 2, and so on in adjacent pairs until row N−1 and row N for a capacitive sensor array having N rows. As another example, differential capacitances may be measured for row 0 and row 1, row 0 and row 2, and so on with row 0 being paired with successive rows until row 0 is paired with row N for a capacitive sensory array having N rows. As described herein, the measuring of differential capacitances for pairs of rows allows sensor array controller to make N−1 measurements per column for a capacitive sensor array having N rows.


Further, as described herein, the differential measurements performed by embodiments resulting the capacitance measurements being substantially immune to common mode variations in the capacitive sensor array. The differential measurements facilitate increased resolution as the range of measurement can be calibrated accordingly to the capacitance change instead of the absolute capacitance value.


Data storage module 510 stores a plurality of differential capacitive measurements. As described herein, a plurality of differential capacitive measurements may be made for each pair of rows in a capacitive sensor array.


Data processing module 508 processes a plurality of differential capacitive measurements to determine the position of an object proximate to a capacitive sensor array. As described herein, data processing module 508 may be operable to compute capacitance values for each row and column intersection of the capacitive sensor array based on the differential capacitance measurements.


EXAMPLE OPERATIONS

With reference to FIG. 6, exemplary flowchart 600 illustrates example blocks used by various embodiments of the present invention. Although specific blocks are disclosed in flowchart 600, such blocks are examples. That is, embodiments are well suited to performing various other blocks or variations of the blocks recited in flowchart 600. It is appreciated that the blocks in flowchart 600 may be performed in an order different than presented, and that not all of the blocks in flowchart 600 may be performed. Flowchart 600 includes processes that, in various embodiments, are carried out by a processor under the control of computer-readable and computer-executable instructions. Embodiments of the present invention may thus be stored as computer readable media or computer-executable instructions including, but not limited to, a firmware update, software update package, or hardware (e.g., ROM).


In particular, FIG. 6 shows a flowchart of an exemplary process for determining position information, in accordance with an embodiment of the present invention. Blocks of flow chart 600 may be carried out by modules of system (e.g., system 500) for determining position information.


At block 602, a column of a capacitive sensor array is selected. At block 604, a first row of the capacitive sensor array is selected. At block 606, a second row of the capacitive sensor array is selected. The first row and the second row intersect with the selected column of the capacitive sensor array. In one embodiment, the first row and the second row are adjacent. In another embodiment, the first and second row may be distant from one another (e.g., separated by at least one other row).


At block 608, a differential capacitance between the first row and the second row is measured. As described herein, the differential capacitance is independent of variations in the capacitive sensor array. Further, the differential capacitance facilitates increased resolution as the measurements are zero centered. The measuring of the differential capacitances facilitates quicker scans because the differential measurements are performed N−1 times per column for a capacitive sensor array comprising N rows.


At block 610, a check is performed to determine if the differential measurements have been performed for all rows. If there are rows remaining in a column to be measured block 604 is performed. If there are no more rows remaining, block 612 may be performed.


At block 612, a check is performed to determine if the differential measurements have been performed for all columns. If there are columns remaining to be measured block 602 is performed. If there are no more columns remaining to be measured, block 614 may be performed.


At block 614, the differential capacitance is utilized in determining a location of an object proximate to the capacitive sensor array. As described herein, the differential capacitances are operable to be used to compute capacitance values for each row and column intersection of the capacitive sensor array (e.g., FIG. 4).


Thus, embodiments of the present invention facilitate more accurate capacitance measurements which are immune to capacitive sensor variations (e.g., temperature changes, dielectric property changes, etc.). Embodiments of the present invention further provide increased resolution and zero centered measurements thereby making current compensation circuitry unnecessary for tuning the dynamic range of the measurements. The measuring of differential capacitances by embodiments of the present invention allows for faster scanning of a capacitive sensor array by performing one less measurement per column.


Embodiments of the present invention are thus described. While the present disclosure has been described in particular embodiments, it should be appreciated that the present disclosure should not be construed as limited by such embodiments, but rather construed according to the below claims.

Claims
  • 1. A method for determining position information, the method comprising: selecting a column of a capacitive sensor array;selecting a first row of said capacitive sensor array;selecting a second row of said capacitive sensor array, wherein said first row and said second row intersect with said column of said capacitive sensor array;measuring a differential current between: a current associated with a capacitor of said first row and said column, andanother current associated with another capacitor of said second row and said column;measuring a differential capacitance between said first row and said second row, based on the measured differential current, the measuring of the differential capacitance including: converting the measured differential current to a voltage; andgenerating a digital value based on the voltage, the digital value representing the measured differential capacitance; anddetermining a location of an object proximate to said capacitive sensor array, based on the measured differential capacitance.
  • 2. The method of claim 1, wherein said first row and said second row are adjacent.
  • 3. The method of claim 1, wherein said first row is separated from said second row by at least one other row.
  • 4. The method of claim 1, wherein the determining of the location of the object, based on the measured differential capacitance includes detecting a presence of the object proximate to said capacitive sensor array, based on the measured differential capacitance.
  • 5. The method of claim 1, further comprising: measuring a plurality of differential capacitances over a plurality of rows of said column;integrating said plurality of capacitances to obtain integrated capacitance values; andusing said integrated capacitance values to determine said location.
  • 6. The method of claim 1, wherein said differential capacitance excludes a contribution from uniform variations in said capacitive sensor array.
  • 7. The method of claim 1, wherein said measuring of the differential current is performed by a differential current measurement circuit.
  • 8. The method of claim 1, wherein said capacitive sensor array comprises N rows and said measuring of said differential capacitance is performed N−1 times per column.
  • 9. An apparatus to determine location of an object proximate to a capacitive sensor array, the apparatus comprising: means for selecting a column of a capacitive sensor array;means for selecting a first row of the capacitive sensor array;means for selecting a second row of the capacitive sensor array, wherein the first row and the second row intersect with the column of the capacitive sensor array;means for measuring a differential current between: a current associated with a capacitor of the first row and the column, andanother current associated with another capacitor of the second row and the column;means for measuring a differential capacitance between the first row and the second row, based on the measured differential current, wherein the means for measuring of the differential capacitance is configured to convert the measured differential current to a voltage and generate a digital value based on the voltage, the digital value representing the measured differential capacitance; andmeans for determining a location of an object proximate to the capacitive sensor array, based on the measured differential capacitance.
  • 10. The apparatus of claim 9, wherein the first row and the second row are adjacent.
  • 11. The apparatus of claim 9, wherein the first row is separated from the second row by at least one other row.
  • 12. The apparatus of claim 9, wherein the means for determining the location of the object, based on the measured differential capacitance is configured to detect a presence of the object proximate to the capacitive sensor array, based on the measured differential capacitance.
  • 13. The apparatus of claim 9, wherein the means for measuring the differential capacitance is configured to measure a plurality of differential capacitances over a plurality of rows of the column, and the means for determining the location of the object is configured to integrate the plurality of capacitances to obtain integrated capacitance values, and use the integrated capacitance values to determine the location.
  • 14. The apparatus of claim 9, wherein the differential capacitance excludes a contribution from uniform variations in the capacitive sensor array.
  • 15. The apparatus of claim 9, wherein the means for measuring the differential current includes a differential current measurement circuit.
  • 16. The apparatus of claim 9, wherein the capacitive sensor array comprises N rows and the means for measuring the differential capacitance performs N−1 differential capacitance measurements per column.
US Referenced Citations (505)
Number Name Date Kind
3660801 Paulfus May 1972 A
3921167 Fox Nov 1975 A
3979745 Bishop Sep 1976 A
4039940 Butler et al. Aug 1977 A
4090092 Serrano May 1978 A
4103252 Bobick Jul 1978 A
4113378 Wirtz Sep 1978 A
4145748 Eichelberger et al. Mar 1979 A
4193063 Hitt et al. Mar 1980 A
4238711 Wallot Dec 1980 A
4264903 Bigelow Apr 1981 A
4266144 Bristol May 1981 A
4283713 Philipp Aug 1981 A
4292604 Embree et al. Sep 1981 A
4293734 Pepper, Jr. Oct 1981 A
4305135 Dahl et al. Dec 1981 A
4438404 Philipp Mar 1984 A
4475151 Philipp Oct 1984 A
4497575 Philipp Feb 1985 A
4558274 Carusillo Dec 1985 A
4586260 Baxter et al. May 1986 A
4614937 Poujois Sep 1986 A
4728932 Atherton Mar 1988 A
4736097 Philipp Apr 1988 A
4736191 Matzke et al. Apr 1988 A
4742331 Barrow et al. May 1988 A
4772983 Kerber et al. Sep 1988 A
4773024 Faggin et al. Sep 1988 A
4802103 Faggin et al. Jan 1989 A
4825147 Cook et al. Apr 1989 A
4831325 Watson, Jr. May 1989 A
4876534 Mead et al. Oct 1989 A
4878013 Andermo Oct 1989 A
4879461 Philipp Nov 1989 A
4879505 Barrow et al. Nov 1989 A
4879508 Andermo Nov 1989 A
4920399 Hall Apr 1990 A
4935702 Mead et al. Jun 1990 A
4940980 Tice Jul 1990 A
4953928 Anderson et al. Sep 1990 A
4962342 Mead et al. Oct 1990 A
4977480 Nishihara Dec 1990 A
5008497 Asher Apr 1991 A
5049758 Mead et al. Sep 1991 A
5055827 Philipp Oct 1991 A
5059920 Anderson et al. Oct 1991 A
5068622 Mead et al. Nov 1991 A
5073759 Mead et al. Dec 1991 A
5083044 Mead et al. Jan 1992 A
5095284 Mead Mar 1992 A
5097305 Mead et al. Mar 1992 A
5107149 Platt et al. Apr 1992 A
5109261 Mead et al. Apr 1992 A
5119038 Anderson et al. Jun 1992 A
5120996 Mead et al. Jun 1992 A
5122800 Philipp Jun 1992 A
5126685 Platt et al. Jun 1992 A
5146106 Anderson et al. Sep 1992 A
5160899 Anderson et al. Nov 1992 A
5165054 Platt et al. Nov 1992 A
5166562 Allen et al. Nov 1992 A
5204549 Platt et al. Apr 1993 A
5214388 Vranish et al. May 1993 A
5237879 Speeter Aug 1993 A
5243554 Allen et al. Sep 1993 A
5248873 Allen et al. Sep 1993 A
5260592 Mead et al. Nov 1993 A
5270963 Allen et al. Dec 1993 A
5276407 Mead et al. Jan 1994 A
5281862 Ma Jan 1994 A
5289023 Mead Feb 1994 A
5294889 Heep et al. Mar 1994 A
5303329 Mead et al. Apr 1994 A
5305017 Gerpheide Apr 1994 A
5323158 Ferguson, Jr. Jun 1994 A
5324958 Mead et al. Jun 1994 A
5331215 Allen et al. Jul 1994 A
5336936 Allen et al. Aug 1994 A
5339213 O'Callaghan Aug 1994 A
5349303 Gerpheide Sep 1994 A
5373245 Vranish et al. Dec 1994 A
5374787 Miller et al. Dec 1994 A
5381515 Platt et al. Jan 1995 A
5384467 Plimon et al. Jan 1995 A
5386219 Greanias et al. Jan 1995 A
5408194 Steinbach et al. Apr 1995 A
5412387 Vincelette et al. May 1995 A
5424756 Ho et al. Jun 1995 A
5461321 Sanders et al. Oct 1995 A
5479103 Kernahan et al. Dec 1995 A
5488204 Mead et al. Jan 1996 A
5495077 Miller et al. Feb 1996 A
5518078 Tsujioka et al. May 1996 A
5525980 Jahier et al. Jun 1996 A
5541580 Gerston et al. Jul 1996 A
5541878 Lemoncheck et al. Jul 1996 A
5543588 Bisset et al. Aug 1996 A
5543590 Gillespie et al. Aug 1996 A
5543591 Gillespie et al. Aug 1996 A
5555907 Philipp Sep 1996 A
5565658 Gerpheide et al. Oct 1996 A
5566702 Philipp Oct 1996 A
5572205 Caldwell et al. Nov 1996 A
5589856 Stein et al. Dec 1996 A
5629891 Lemoncheck et al. May 1997 A
5648642 Miller et al. Jul 1997 A
5650597 Redmayne Jul 1997 A
5670915 Cooper et al. Sep 1997 A
5672959 Der Sep 1997 A
5680070 Anderson et al. Oct 1997 A
5682032 Philipp Oct 1997 A
5684487 Timko Nov 1997 A
5694063 Burlison et al. Dec 1997 A
5730165 Philipp Mar 1998 A
5748185 Stephan et al. May 1998 A
5757368 Gerpheide et al. May 1998 A
5760852 Wu et al. Jun 1998 A
5763909 Mead et al. Jun 1998 A
5763924 Lum et al. Jun 1998 A
5767457 Gerpheide et al. Jun 1998 A
5796183 Hourmand Aug 1998 A
5801340 Peter Sep 1998 A
5812698 Platt et al. Sep 1998 A
5841078 Miller et al. Nov 1998 A
5844256 Higashino Dec 1998 A
5844265 Mead et al. Dec 1998 A
5854625 Frisch et al. Dec 1998 A
5861583 Schediwy et al. Jan 1999 A
5861875 Gerpheide Jan 1999 A
5864242 Allen et al. Jan 1999 A
5864392 Winklhofer et al. Jan 1999 A
5880411 Gillespie et al. Mar 1999 A
5889236 Gillespie et al. Mar 1999 A
5905489 Takahama et al. May 1999 A
5914465 Allen et al. Jun 1999 A
5914708 Lagrange et al. Jun 1999 A
5920309 Bisset et al. Jul 1999 A
5920310 Faggin et al. Jul 1999 A
5926566 Wang et al. Jul 1999 A
5942733 Allen et al. Aug 1999 A
5943052 Allen et al. Aug 1999 A
5969513 Clark Oct 1999 A
6023422 Allen et al. Feb 2000 A
6028271 Gillespie et al. Feb 2000 A
6028959 Wang et al. Feb 2000 A
6037929 Ogura et al. Mar 2000 A
6037930 Wolfe et al. Mar 2000 A
6060957 Kodrnja et al. May 2000 A
6067019 Scott May 2000 A
6097432 Mead et al. Aug 2000 A
6145850 Rehm Nov 2000 A
6148104 Wang et al. Nov 2000 A
6184871 Teres et al. Feb 2001 B1
6185450 Seguine et al. Feb 2001 B1
6188228 Philipp Feb 2001 B1
6188391 Seely et al. Feb 2001 B1
6191723 Lewis Feb 2001 B1
6222528 Gerpheide et al. Apr 2001 B1
6239389 Allen et al. May 2001 B1
6249447 Boylan et al. Jun 2001 B1
6262717 Donohue et al. Jul 2001 B1
6271719 Sevastopoulos Aug 2001 B1
6271720 Sevastopoulos Aug 2001 B1
6271835 Hoeksma Aug 2001 B1
6278283 Tsugai Aug 2001 B1
6280391 Olson et al. Aug 2001 B1
6288707 Philipp Sep 2001 B1
6295052 Kato et al. Sep 2001 B1
6304014 England et al. Oct 2001 B1
6320184 Winklhofer et al. Nov 2001 B1
6323846 Westerman et al. Nov 2001 B1
6326859 Goldman et al. Dec 2001 B1
6342817 Crofts et al. Jan 2002 B1
6344773 Sevastopoulos et al. Feb 2002 B1
6353200 Schwankhart Mar 2002 B1
6366099 Reddi Apr 2002 B1
6377009 Philipp Apr 2002 B1
6377129 Rhee et al. Apr 2002 B1
6380929 Platt Apr 2002 B1
6380931 Gillespie et al. Apr 2002 B1
6400217 Bhandari Jun 2002 B1
6414671 Gillespie et al. Jul 2002 B1
6424338 Anderson Jul 2002 B1
6430305 Decker Aug 2002 B1
6441073 Tanaka et al. Aug 2002 B1
6441682 Vinn et al. Aug 2002 B1
6445257 Cox et al. Sep 2002 B1
6448911 Somayajula Sep 2002 B1
6452514 Philipp Sep 2002 B1
6457355 Philipp Oct 2002 B1
6459321 Belch Oct 2002 B1
6466036 Philipp Oct 2002 B1
6473069 Gerpheide Oct 2002 B1
6476798 Bertram et al. Nov 2002 B1
6489899 Ely et al. Dec 2002 B1
6490203 Tang Dec 2002 B1
6498720 Glad Dec 2002 B2
6499359 Washeleski et al. Dec 2002 B1
6522083 Roach Feb 2003 B1
6522128 Ely et al. Feb 2003 B1
6522187 Sousa Feb 2003 B1
6523416 Takagi et al. Feb 2003 B2
6529015 Nonoyama et al. Mar 2003 B2
6534970 Ely et al. Mar 2003 B1
6535200 Philipp Mar 2003 B2
6570557 Westerman et al. May 2003 B1
6574095 Suzuki Jun 2003 B2
6577140 Wenman Jun 2003 B1
6583632 Von Basse et al. Jun 2003 B2
6587093 Shaw et al. Jul 2003 B1
6597347 Yasutake Jul 2003 B1
6610936 Gillespie et al. Aug 2003 B2
6614313 Crofts et al. Sep 2003 B2
6624640 Lund et al. Sep 2003 B2
6639586 Gerpheide Oct 2003 B2
6642857 Schediwy et al. Nov 2003 B1
6649924 Philipp et al. Nov 2003 B1
6667740 Ely et al. Dec 2003 B2
6673308 Hino et al. Jan 2004 B2
6677758 Maki et al. Jan 2004 B2
6677932 Westerman Jan 2004 B1
6680731 Gerpheide et al. Jan 2004 B2
6683462 Shimizu Jan 2004 B2
6690066 Lin et al. Feb 2004 B1
6704005 Kato et al. Mar 2004 B2
6705511 Dames et al. Mar 2004 B1
6714817 Daynes et al. Mar 2004 B2
6720777 Wang Apr 2004 B2
6730863 Gerpheide et al. May 2004 B1
6731121 Hsu et al. May 2004 B1
6744258 Ishio et al. Jun 2004 B2
6750852 Gillespie et al. Jun 2004 B2
6768420 McCarthy et al. Jul 2004 B2
6774644 Eberlein Aug 2004 B2
6781577 Shigetaka Aug 2004 B2
6788221 Ely et al. Sep 2004 B1
6788521 Nishi Sep 2004 B2
6798218 Kasperkovitz Sep 2004 B2
6806693 Bron Oct 2004 B1
6809275 Cheng et al. Oct 2004 B1
6810442 Lin et al. Oct 2004 B1
6825673 Yamaoka Nov 2004 B1
6825890 Matsufusa Nov 2004 B2
6829727 Pawloski Dec 2004 B1
6838887 Denen et al. Jan 2005 B2
6856433 Hatano et al. Feb 2005 B2
6859159 Michalski Feb 2005 B2
6861961 Sandbach et al. Mar 2005 B2
6873203 Latham et al. Mar 2005 B1
6879215 Roach Apr 2005 B1
6882338 Flowers Apr 2005 B2
6888536 Westerman et al. May 2005 B2
6888538 Ely et al. May 2005 B2
6891531 Lin May 2005 B2
6893724 Lin et al. May 2005 B2
6897673 Savage et al. May 2005 B2
6903402 Miyazawa Jun 2005 B2
6904570 Foote et al. Jun 2005 B2
6914547 Swaroop et al. Jul 2005 B1
6933873 Horsley et al. Aug 2005 B1
6940291 Ozick Sep 2005 B1
6946853 Gifford et al. Sep 2005 B2
6949811 Miyazawa Sep 2005 B2
6949937 Knoedgen Sep 2005 B2
6958594 Redl et al. Oct 2005 B2
6969978 Dening Nov 2005 B2
6970120 Bjornsen Nov 2005 B1
6970126 O'Dowd et al. Nov 2005 B1
6975123 Malang et al. Dec 2005 B1
6993607 Philipp Jan 2006 B2
6999009 Monney Feb 2006 B2
7002557 Iizuka et al. Feb 2006 B2
7006078 Kim Feb 2006 B2
7006938 Laraia et al. Feb 2006 B2
7030782 Ely et al. Apr 2006 B2
7030860 Hsu et al. Apr 2006 B1
7031886 Hargreaves Apr 2006 B1
7032051 Reay et al. Apr 2006 B2
7046230 Zadesky et al. May 2006 B2
7068039 Parker Jun 2006 B2
7075316 Umeda et al. Jul 2006 B2
7075864 Kakitsuka et al. Jul 2006 B2
7078916 Denison Jul 2006 B2
7098675 Inaba et al. Aug 2006 B2
7109978 Gillespie et al. Sep 2006 B2
7119550 Kitano et al. Oct 2006 B2
7129714 Baxter Oct 2006 B2
7129935 Mackey Oct 2006 B2
7133140 Lukacs et al. Nov 2006 B2
7133793 Ely et al. Nov 2006 B2
7136051 Hein et al. Nov 2006 B2
7141968 Hibbs et al. Nov 2006 B2
7141987 Hibbs et al. Nov 2006 B2
7148704 Philipp Dec 2006 B2
7151276 Gerlach et al. Dec 2006 B2
7151528 Taylor et al. Dec 2006 B2
7158056 Wright et al. Jan 2007 B2
7158125 Sinclair et al. Jan 2007 B2
7202655 Itoh Apr 2007 B2
7202857 Hinckley et al. Apr 2007 B2
7205777 Schulz et al. Apr 2007 B2
7212189 Shaw et al May 2007 B2
7224591 Kaishita et al. May 2007 B2
7225090 Coley May 2007 B2
7233508 Itoh Jun 2007 B2
7235983 O'Dowd et al. Jun 2007 B2
7245131 Kurachi et al. Jul 2007 B2
7253643 Seguine Aug 2007 B1
7254775 Geaghan et al. Aug 2007 B2
7256588 Howard et al. Aug 2007 B2
7262609 Reynolds Aug 2007 B2
7271608 Vermeire et al. Sep 2007 B1
7288946 Hargreaves et al. Oct 2007 B2
7288977 Stanley Oct 2007 B2
7298124 Kan et al. Nov 2007 B2
7301350 Hargreaves et al. Nov 2007 B2
7307485 Snyder et al. Dec 2007 B1
7312616 Snyder Dec 2007 B2
7323879 Kuo et al. Jan 2008 B2
7323886 Lee Jan 2008 B2
7333090 Tanaka et al. Feb 2008 B2
7339580 Westerman et al. Mar 2008 B2
7359816 Kumar et al. Apr 2008 B2
7375535 Kutz et al. May 2008 B1
7381031 Kawaguchi et al. Jun 2008 B2
7392431 Swoboda Jun 2008 B2
7417411 Hoffman et al. Aug 2008 B2
7417441 Reynolds Aug 2008 B2
7423437 Hargreaves et al. Sep 2008 B2
7439962 Reynolds et al. Oct 2008 B2
7449895 Ely et al. Nov 2008 B2
7450113 Gillespie et al. Nov 2008 B2
7451050 Hargreaves Nov 2008 B2
7453270 Hargreaves et al. Nov 2008 B2
7453279 Corbin, Jr. et al. Nov 2008 B2
7466307 Trent, Jr. et al. Dec 2008 B2
7479788 Bolender et al. Jan 2009 B2
7495659 Marriott et al. Feb 2009 B2
7499040 Zadesky et al. Mar 2009 B2
7504833 Seguine Mar 2009 B1
7515140 Philipp Apr 2009 B2
7521941 Ely et al. Apr 2009 B2
RE40867 Binstead Aug 2009 E
7598822 Rajagopal et al. Oct 2009 B2
7663607 Hotelling et al. Feb 2010 B2
7667468 Anderson Feb 2010 B1
7683641 Hargreaves et al. Mar 2010 B2
7804307 Bokma et al. Sep 2010 B1
7812829 Gillespie et al. Oct 2010 B2
7821274 Philipp Oct 2010 B2
7911456 Gillespie et al. Mar 2011 B2
7932897 Elias et al. Apr 2011 B2
8040142 Bokma et al. Oct 2011 B1
8040321 Peng et al. Oct 2011 B2
8054299 Krah Nov 2011 B2
8068097 Guanghai Nov 2011 B2
8072429 Grivna Dec 2011 B2
8082566 Stallings Dec 2011 B2
8089288 Maharita Jan 2012 B1
8089289 Kremin et al. Jan 2012 B1
8093914 Maharyta Jan 2012 B2
8094128 Vu et al. Jan 2012 B2
8169238 Maharyta et al. May 2012 B1
20010012667 Ma et al. Aug 2001 A1
20020000978 Gerpheide Jan 2002 A1
20020063688 Shaw et al. May 2002 A1
20020067348 Masters et al. Jun 2002 A1
20020109035 Denen et al. Aug 2002 A1
20020136372 Bozorgui-Nesbat Sep 2002 A1
20020140440 Haase Oct 2002 A1
20020191029 Gillespie et al. Dec 2002 A1
20030014239 Ichbiah et al. Jan 2003 A1
20030025679 Taylor et al. Feb 2003 A1
20030062889 Ely et al. Apr 2003 A1
20030063073 Geaghan et al. Apr 2003 A1
20030063428 Nishi Apr 2003 A1
20030076306 Zadesky et al. Apr 2003 A1
20030080755 Kobayashi May 2003 A1
20030091220 Sato et al. May 2003 A1
20030098858 Perski et al. May 2003 A1
20030156098 Shaw et al. Aug 2003 A1
20030160808 Foote et al. Aug 2003 A1
20030178675 Nishizaka et al. Sep 2003 A1
20030183864 Miyazawa Oct 2003 A1
20030183884 Miyazawa Oct 2003 A1
20030184315 Eberlein Oct 2003 A1
20030189419 Maki et al. Oct 2003 A1
20030230438 Keefer et al. Dec 2003 A1
20030232507 Chen Dec 2003 A1
20040041798 Kim Mar 2004 A1
20040068409 Tanaka et al. Apr 2004 A1
20040082198 Nakamura et al. Apr 2004 A1
20040169594 Ely et al. Sep 2004 A1
20040178989 Shahoian et al. Sep 2004 A1
20040178997 Gillespie et al. Sep 2004 A1
20040183560 Savage et al. Sep 2004 A1
20040217945 Miyamoto et al. Nov 2004 A1
20040239616 Collins Dec 2004 A1
20040239650 Mackey Dec 2004 A1
20040252109 Trent et al. Dec 2004 A1
20040263864 Lukacs et al. Dec 2004 A1
20050021269 Ely et al. Jan 2005 A1
20050024341 Gillespie et al. Feb 2005 A1
20050031175 Hara et al. Feb 2005 A1
20050062732 Sinclair et al. Mar 2005 A1
20050073302 Hibbs et al. Apr 2005 A1
20050073322 Hibbs et al. Apr 2005 A1
20050083110 Latham, II et al. Apr 2005 A1
20050099188 Baxter May 2005 A1
20050159126 Wang Jul 2005 A1
20050169768 Kawaguchi et al. Aug 2005 A1
20050179668 Edwards Aug 2005 A1
20050270273 Marten Dec 2005 A1
20050275382 Stessman et al. Dec 2005 A1
20050280639 Taylor et al. Dec 2005 A1
20050283330 Laraia et al. Dec 2005 A1
20060022660 Itoh Feb 2006 A1
20060026535 Hotelling et al. Feb 2006 A1
20060032680 Elias et al. Feb 2006 A1
20060033508 Lee Feb 2006 A1
20060033724 Chaudhri et al. Feb 2006 A1
20060038793 Philipp Feb 2006 A1
20060049834 Umeda Mar 2006 A1
20060053387 Ording Mar 2006 A1
20060066582 Lyon et al. Mar 2006 A1
20060066585 Lin Mar 2006 A1
20060097991 Hotelling et al. May 2006 A1
20060097992 Gitzinger et al. May 2006 A1
20060108349 Finley et al. May 2006 A1
20060113974 Kan et al. Jun 2006 A1
20060114247 Brown Jun 2006 A1
20060139469 Yokota et al. Jun 2006 A1
20060152739 Silvestre Jul 2006 A1
20060164142 Stanley Jul 2006 A1
20060172767 Cathey et al. Aug 2006 A1
20060176718 Itoh Aug 2006 A1
20060187214 Gillespie et al. Aug 2006 A1
20060193156 Kaishita et al. Aug 2006 A1
20060197750 Kerr et al. Sep 2006 A1
20060197752 Hurst et al. Sep 2006 A1
20060221061 Fry Oct 2006 A1
20060227117 Proctor Oct 2006 A1
20060232559 Chien et al. Oct 2006 A1
20060258390 Cui et al. Nov 2006 A1
20060262101 Layton et al. Nov 2006 A1
20060267953 Peterson et al. Nov 2006 A1
20060273804 Delorme et al. Dec 2006 A1
20060290678 Lii Dec 2006 A1
20070046299 Hargreaves et al. Mar 2007 A1
20070069274 Elsass et al. Mar 2007 A1
20070074913 Geaghan et al. Apr 2007 A1
20070076897 Philipp Apr 2007 A1
20070100566 Coley May 2007 A1
20070132737 Mulligan et al. Jun 2007 A1
20070152983 Mckillop et al. Jul 2007 A1
20070164756 Lee Jul 2007 A1
20070173220 Kim et al. Jul 2007 A1
20070176609 Ely et al. Aug 2007 A1
20070176903 Dahlin et al. Aug 2007 A1
20070229469 Seguine Oct 2007 A1
20070236478 Geaghan et al. Oct 2007 A1
20070257894 Philipp Nov 2007 A1
20070263191 Shibazaki Nov 2007 A1
20070268243 Choo et al. Nov 2007 A1
20070268265 Xiaoping Nov 2007 A1
20070268273 Westerman et al. Nov 2007 A1
20070268274 Westerman et al. Nov 2007 A1
20070268275 Westerman et al. Nov 2007 A1
20070273659 Xiaoping et al. Nov 2007 A1
20070291013 Won Dec 2007 A1
20070296709 Guanghai Dec 2007 A1
20080007529 Paun et al. Jan 2008 A1
20080007534 Peng et al. Jan 2008 A1
20080024455 Lee et al. Jan 2008 A1
20080036473 Jansson Feb 2008 A1
20080041639 Westerman et al. Feb 2008 A1
20080041640 Gillespie et al. Feb 2008 A1
20080042986 Westerman et al. Feb 2008 A1
20080042987 Westerman et al. Feb 2008 A1
20080042988 Westerman et al. Feb 2008 A1
20080042989 Westerman et al. Feb 2008 A1
20080042994 Gillespie et al. Feb 2008 A1
20080047764 Lee Feb 2008 A1
20080048997 Gillespie et al. Feb 2008 A1
20080062139 Hotelling et al. Mar 2008 A1
20080062140 Hotelling et al. Mar 2008 A1
20080068100 Goodnow et al. Mar 2008 A1
20080088595 Liu et al. Apr 2008 A1
20080111714 Kremin May 2008 A1
20080116904 Reynolds et al. May 2008 A1
20080128182 Westerman et al. Jun 2008 A1
20080150906 Grivna Jun 2008 A1
20080158178 Hotelling et al. Jul 2008 A1
20080162997 Vu et al. Jul 2008 A1
20080165134 Krah Jul 2008 A1
20080179112 Qin et al. Jul 2008 A1
20080196945 Konstas Aug 2008 A1
20080266263 Motaparti et al. Oct 2008 A1
20080278178 Philipp Nov 2008 A1
20090002206 Kremin Jan 2009 A1
20090096758 Hotelling et al. Apr 2009 A1
20090153152 Maharyta et al. Jun 2009 A1
20090322351 Mcleod Dec 2009 A1
20120043140 Peterson et al. Feb 2012 A1
20120043973 Kremin Feb 2012 A1
Foreign Referenced Citations (7)
Number Date Country
0574213 Dec 1993 EP
05000604 Feb 2005 GB
412528 Jan 1992 JP
5283519 Oct 1993 JP
6104334 Apr 1994 JP
6163528 Jun 1994 JP
0002188 Jan 2000 WO