# US 2014/0198040 A1 · Apparatus, system and method for self-calibration of indirect pointing devices > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2014/0198040 A1 - Document ID: US20140198040A1 - Status: Published application - Kind: A1 - Application number: 13/743,106 - Filed: 2013-01-16 - Published: 2014-07-17 - Earliest claimed: 2013-01-16 - Assignees: Lenovo (Singapore) Pte. Ltd. - Applicants: Lenovo (Singapore) Pte, Ltd. - Inventors: John Weldon Nicholson; Kenneth Scott Seethaler - Web page: https://patentgrep.com/patent/US20140198040A1 ## CPC - G06F 3/0416: {Control or interface arrangements specially adapted for digitisers} - G06F 3/038: Control and interface arrangements therefor, e.g. drivers or device-embedded control circuitry - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract An apparatus, system, and method are disclosed for pointing device calibration. An observation module may track physical movement sensed by an indirect pointing device and record actual cursor behavior corresponding to the physical movement. An analysis module may compare the actual cursor behavior to reference cursor behavior to detect a deviation. A calibration module may adjust one or more settings of the pointing device in a manner calculated to reduce the deviation. ## Claims ### Claim 1 An apparatus comprising: an observation module that tracks physical movement sensed by an indirect pointing device and records actual cursor behavior corresponding to the physical movement; an analysis module that compares the actual cursor behavior to reference cursor behavior to detect a deviation; and a calibration module that adjusts one or more settings of the pointing device in a manner calculated to reduce the deviation wherein the observation module, the analysis module, and the calibration module comprise one or more of logic hardware and executable code, the executable code stored on one or more memory devices. ### Claim 2 (depends on 1) The apparatus of claim 1, wherein the calibration module comprises an expert system that improves the manner of reducing the deviation through machine learning. ### Claim 3 (depends on 1) The apparatus of claim 1, wherein the physical movement comprises one or more of pointing, navigating, scrolling, manipulating, writing, drawing, and painting. ### Claim 4 (depends on 1) The apparatus of claim 1, wherein the deviation comprises one or more of overshoot, undershoot, slowness, lurching, and repetition. ### Claim 5 (depends on 2) The apparatus of claim 2, wherein the settings comprise one or more of sensitivity, ballistics, and momentum. ### Claim 6 A system comprising: an indirect pointing device; a computer having a cursor that is controlled at least in part by the indirect pointing device; an observation module that tracks physical movement sensed by an indirect pointing device and records actual cursor behavior corresponding to the physical movement; an analysis module that compares the actual cursor behavior to reference cursor behavior to detect a deviation; and a calibration module that adjusts one or more settings of the pointing device in a manner calculated to reduce the deviation. ### Claim 7 (depends on 6) The system of claim 6, further comprising a support module that maintains one or more models of reference cursor behavior including at least a default model. ### Claim 8 (depends on 6) The system of claim 6, further comprising a second indirect pointing device, wherein the calibration module adjusts one or more second settings of the second pointing device in a manner calculated to reduce the deviation. ### Claim 9 (depends on 6) The system of claim 6, wherein the system is multi-user, calibrating the indirect pointing device independently for each user. ### Claim 10 (depends on 6) The system of claim 6, wherein the indirect pointing device is selected from the set consisting of a mouse, a touchpad, a trackpoint, a joystick, a pedal, a wand, a remote, a touchscreen, and a gesture camera. ### Claim 11 A computer program product comprising a computer readable storage medium storing a computer readable program code executed to perform operations for self-calibration, the operations of the computer program product comprising: tracking physical movement sensed by an indirect pointing device; recording actual cursor behavior corresponding to the physical movement; comparing the actual cursor behavior to reference cursor behavior to detect a deviation; and adjusting one or more settings of the pointing device in a manner calculated to reduce the deviation. ### Claim 12 (depends on 11) The computer program product of claim 11, further comprising the operation of improving the manner of reducing the deviation through machine learning. ### Claim 13 A method comprising: tracking physical movement sensed by an indirect pointing device; recording actual cursor behavior corresponding to the physical movement; comparing the actual cursor behavior to reference cursor behavior to detect a deviation; and adjusting one or more settings of the pointing device in a manner calculated to reduce the deviation. ### Claim 14 (depends on 13) The method of claim 13, further comprising improving the manner of reducing the deviation through machine learning. ### Claim 15 (depends on 13) The method of claim 13, further comprising providing a training mode in which a user demonstrates the reference cursor behavior. ### Claim 16 (depends on 13) The method of claim 13, further comprising providing a user interface that enables a user to explicitly define the reference cursor behavior. ### Claim 17 (depends on 13) The method of claim 13, further comprising providing a user interface that enables a user to explicitly control the step of adjusting. ### Claim 18 (depends on 13) The method of claim 13, further comprising filtering out cursor behavior related to extraneous physical movement. ### Claim 19 (depends on 18) The method of claim 18, wherein filtering comprises statistically combining historical cursor behavior. ### Claim 20 (depends on 18) The method of claim 18, wherein filtering comprises ignoring aimless cursor behavior.