Understanding & Modeling Input Devices

1. Understanding & ModelingInput Devices

2. Questions How do common input devices work? How can we think about the larger space of all possible input devices? Can we predict human input performance? What about uncommon input devices (multitouch, tangible interfaces, …)? Will this be on the exam? Yes.

3. Today’s lecture in graphic form

4. I think my keyboard is broken. Whenever I have a few keys pressed down, some keys suddenly don’t work anymore; at other times ‘phantom’ characters appear. What’s going on?

5. Keyboard

9. Microprocessor and Controller

10. Row/Column Scanning http://v.youku.com/v_show/id_XMTI5NjE0OTQ4.html 9 lines and 20 keys

11. Closeup

12. One key down

14. 3 Keys Down

15. Encoding keyboard: Keys conflict http://www.upsdn.net/html/2006-10/760.html • C1-R1-C2-R2 • 3 or 4 keys • Q,W,A,S

16. A Layered Framework From: Hartmann, Follmer, Klemmer: Input Devices are like Onions

17. Mouse Mouse. Engelbart and English ~1964

20. Right button Left button Encoder wheel for scrolling

21. IR emitter IR detector slotted wheel (between emitter & detector)

22. Sensing: Rotary Encoder

23. Sensing: Fwd rotation

24. Sensing: Backwd Rotation

25. Solutions: Use two Out-of-Phase Detectors

26. Sensing: Rotary Encoder

28. Transformation cxt = max(0, min( sw, cxt-1+dx*cd )) cyt = … cxt: cursor x (horizontal) position in screen coordinates at time t dx: mouse x movement delta in mouse coordinates sw: screen width cd: control-display ratio

29. Device Abstraction Click, DoubleClick, MouseUp, MouseDown, MouseMove …

30. What about optical mice? Source: http://spritesmods.com/?art=mouseeye

31. Source: http://spritesmods.com/?art=mouseeye

32. Trackball, Trackpad

33. Trackpoint Indirect, force sensing, velocity control Nonlinear transfer function

34. Joystick

35. A design space of input devices… Card, S. K., Mackinlay, J. D., and Robertson, G. G. 1991. A morphological analysis of the design space of input devices. ACM TOIS 9, 2 (Apr. 1991), 99-122.

38. Which is faster?

39. Which is faster? Engelbart

40. Experiment: Mice are fastest!

41. Exam Question Material! Fitts’s law Source: Landay, James. “Human Abilities”. CS160 UC Berkeley. Time Tpos to move the hand to target (size S) which is distance D away is given by: Tpos = a + b log2 (D/S + 1) Index of Difficulty (ID) Only relative precision matters

43. Tpos = a + b log2 (D/S + 1) Device Characteristics (bandwidth of human muscle group & of device) a: start/stop time (intercept) b: speed (slope)

44. Bandwidth of Human Muscle Groups

45. Why is mouse fastest? Why these results? Time to position mouse proportional to Fitts’s Index of Difficulty ID. [i.e. how well can the muscles direct the input device] Therefore speed limit is in the eye-hand system, not the mouse. Therefore, mouse is a near optimal device.

46. Fitts’s law example • Which will be faster on average? • pie menu (bigger targets & less distance)

47. Fitts’s law in Windows &Mac OS Windows 95: Missed by a pixel Windows XP: Good to the last drop The Apple menu in Mac OS X v10.4 Tiger.

48. In office 2007 Larger, labeled controls can be clicked more quickly Magic Corner: Office Button in the upper-left corner Mini Toolbar: Close to the cursor Source: Jensen Harris, An Office User Interface Blog : Giving You Fitts. Microsoft, 2007.

49. Uncommon Input Devices • Assumptions so far: • Single user, working in front of a desktop PC • Main tasks are typing and pointing • Efficiency rules • What if we change these assumptions? • Design for enjoyment / engagement • Design for multi-user scenarios

50. Position+Orientation: Nitendo Wii