TOUCH SENSING ARCHITECTURE

• US 20080042986A1
• Filed: 07/30/2007
• Published: 02/21/2008
• Est. Priority Date: 01/26/1998
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: Westerman, Wayne, Elias, John
• Granted Patent: US 8,629,840 B2
• Time in Patent Office: Days
• US Class Current: 345/173
• CPC Class Codes: G06F 18/24137 Distances to cluster centroïds
• CPC Class Codes: G06F 2203/04101 2.5D-digitiser, i.e. digitiser detecting the X/Y position of the input means, finger or stylus, also when it does not touch, but is proximate to the digitiser's interaction surface and also measures the distance of the input means within a short range in the Z direction, possibly with a separate measurement setup
• CPC Class Codes: G06F 2203/04104 Multi-touch detection in digitiser, i.e. details about the simultaneous detection of a plurality of touching locations, e.g. multiple fingers or pen and finger
• CPC Class Codes: G06F 2203/04106 Multi-sensing digitiser, i.e. digitiser using at least two different sensing technologies simultaneously or alternatively, e.g. for detecting pen and finger, for saving power or for improving position detection
• CPC Class Codes: G06F 2203/04808 Several contacts: gestures triggering a specific function, e.g. scrolling, zooming, right-click, when the user establishes several contacts with the surface simultaneously; e.g. using several fingers or a combination of fingers and pen
• CPC Class Codes: G06F 3/0235 using chord techniques G06F3/0234 takes precedence
• CPC Class Codes: G06F 3/041 Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means
• CPC Class Codes: G06F 3/0412 Digitisers structurally integrated in a display
• CPC Class Codes: G06F 3/04166 Details of scanning methods, e.g. sampling time, grouping of sub areas or time sharing with display driving Synchronisation with the driving of the display or the backlighting unit to avoid interferences generated internally G06F3/04184
• CPC Class Codes: G06F 3/04186 Touch location disambiguation
• CPC Class Codes: G06F 3/0446 using a grid-like structure of electrodes in at least two directions, e.g. using row and column electrodes
• CPC Class Codes: G06F 3/0447 Position sensing using the local deformation of sensor cells
• CPC Class Codes: G06F 3/04815 Interaction with a metaphor-based environment or interaction object displayed as three-dimensional, e.g. changing the user viewpoint with respect to the environment or object
• CPC Class Codes: G06F 3/04845 for image manipulation, e.g. dragging, rotation, expansion or change of colour
• CPC Class Codes: G06F 3/0485 Scrolling or panning
• CPC Class Codes: G06F 3/0488 using a touch-screen or digitiser, e.g. input of commands through traced gestures
• CPC Class Codes: G06F 3/04883 for inputting data by handwriting, e.g. gesture or text
• CPC Class Codes: G06F 3/04886 by partitioning the display area of the touch-screen or the surface of the digitising tablet into independently controllable areas, e.g. virtual keyboards or menus
• CPC Class Codes: G06V 30/19173 Classification techniques
• CPC Class Codes: G06V 30/1983 Syntactic or structural pattern recognition, e.g. symbolic string recognition
• CPC Class Codes: G06V 40/107 : Static hand or arm
• CPC Class Codes: H03K 17/9622 : using a plurality of detectors, e.g. keyboard
• CPC Class Codes: H03K 2217/960725 : Charge-transfer

Abstract

Apparatus and methods are disclosed for simultaneously tracking multiple finger and palm contacts as hands approach, touch, and slide across a proximity-sensing, multi-touch surface. Identification and classification of intuitive hand configurations and motions enables unprecedented integration of typing, resting, pointing, scrolling, 3D manipulation, and handwriting into a versatile, ergonomic computer input device.

Claims

1. An apparatus comprising the elements of:

a. a surface comprising a plurality of proximity sensors;

b. segmentation circuitry for evaluating indications of said proximity sensors and for segmenting said indications into a plurality of groups, each of said groups representing a part of a hand;

c. identification circuitry for associating each of a plurality of said groups with a specific part of a hand;

d. tracking circuitry for determining, relative to said surface, a path of each hand part over elapsed time.

2. The apparatus of claim 1 wherein said segmentation circuitry comprises hardware and software.

3. The apparatus of claim 1 wherein said indication of said proximity sensors are one or more image pixels.

4. The apparatus of claim 1 wherein said indications of said proximity sensors comprise a part of a proximity image.

5. The apparatus of claim 4 wherein said part of a proximity image is a whole proximity image.

6. The apparatus of claim 1 wherein one of said groups represents a part of a hand that is a finger and another of said groups represents a part of a hand that is a palm.

7. The apparatus of claim 1 where identification circuitry comprises hardware and software.

8. The apparatus of claim 1 wherein tracking circuitry comprises hardware and software.

9. The apparatus of claim 1 further comprising a pen grip detector for evaluating representations of said groups to determine if said surface is proximate to a hand in the position of gripping a pen.

10. The apparatus of claim 9 wherein said representations of said groups are said specific parts of a hand.

11. The apparatus of claim 9 where said pen grip detector is further for generating signals associated with the perceived movement of said hand in the position of gripping a pen.

12. An apparatus comprising the elements of:

e. a surface comprising a plurality of sensors, each sensor adapted to sense proximity of an object;

f. a segmentation unit for evaluating indications of said sensors and for segmenting said indications into a plurality of groups, each of said groups representing a part of a hand;

g. an identification unit for associating each of a plurality of said groups with a specific part of a hand;

h. a tracking unit for determining, relative to said surface, a path of each hand part over elapsed time.

13. The apparatus of claim 12 wherein said segmentation unit comprises either hardware or software or both hardware and software.

14. The apparatus of claim 12 wherein said segmentation unit comprises software and a processor.

15. The apparatus of claim 12 wherein said indication of said sensors are one or more image pixels.

16. The apparatus of claim 12 wherein said indications of said sensors comprise a part of a proximity image.

17. The apparatus of claim 16 wherein said part of a proximity image is a whole proximity image.

18. The apparatus of claim 12 wherein one of said groups represents a part of a hand that is a finger and another of said groups represents a part of a hand that is a palm.

19. The apparatus of claim 12 where said identification unit comprises hardware or software or a combination of hardware and software.

20. The apparatus of claim 12 wherein said identification unit comprises software and a processor.

21. The apparatus of claim 12 wherein said tracking unit comprises hardware and software.

22. The apparatus of claim 12 wherein said tracking unit comprises software and a processor.

23. The apparatus of claim 12 further comprising a pen grip detector for evaluating representations of said groups to determine if said surface is proximate to a hand in the position of gripping a pen.

24. The apparatus of claim 23 wherein said representations of said groups are said specific parts of a hand.

25. The apparatus of claim 23 where said pen grip detector is further for generating signals associated with the perceived movement of said hand in the position of gripping a pen.

26. A method comprising the steps of:

i. providing a plurality of sensors, each sensor adapted to sense proximity of an object;

j. receiving indications from said sensors and segmenting said indications into a plurality of groups, each of said groups representing a part of a hand;

k. associating each said groups with a specific part of a hand;

l. calculating, relative to said sensors, a path of each hand part over elapsed time.

27. The method of claim 26 wherein said indication of said sensors are one or more image pixels.

28. The method of claim 26 wherein said indications of said sensors comprise a part of a proximity image.

29. The method of claim 28 wherein said part of a proximity image is a whole proximity image.

30. The method of claim 26 wherein one of said groups represents a part of a hand that is a finger and another of said groups represents a part of a hand that is a palm.

31. The method claim 26 further comprising the step of evaluating representations of said groups to determine if said sensors are proximate to a hand in the position of gripping a pen.

32. The method of claim 31 wherein said representations of said groups are said specific parts of a hand.

33. The method of claim 31 further comprising the step of generating signals associated with the perceived movement of said hand in the position of gripping a pen.