VibPress is a technique that uses a mobile device's accelerometer to estimate pressure input without additional hardware. It activates the vibration motor and measures the displacement absorbed using the accelerometer. A pilot study found users could reliably produce minimum and maximum pressure levels. A follow up study tested input performance at different pressure levels, finding selection times averaged 1-4 seconds with error rates up to 33% for higher pressure levels. Overall, VibPress allows pressure input estimation using only existing mobile sensors.

1. VibPress
Estimating Pressure Input Using Vibration Absorption on Mobile Devices
Presenter: S.J. Hwang Ph.D. Candidate | 6th Semester

2. BACKGROUND
VibPress

3. BACKGROUND
Human interacts with environmental objects by grasping, holding, twisting, pressing with pressure.

4. BACKGROUND
However, current touch screen
does not support pressure-sensitive input.

5. BACKGROUND
1.It can free the user from spatial restrictions and repetitive movement (Miyaki, & Rekimoto, 2009).
2.It is suitable for one-handed interaction, adds a degree of freedom to touch locations (Boring et al., 2012).
3.Pressure input allows relatively stable and accurate interactions when user is in mobile context (Wilson et al., 2011).
4.It can be used to alleviate occlusion problems and provide ways for rich contextual selections (Ramos et al., 2004).
Advantages of pressure input for mobile device

6. PREVIOUS WORK
VibPress

7. PREVIOUS WORK
Hardware augmentation approach
Pressure estimation in software
Pressure input techniques for mobile devices

8. PREVIOUS WORK
GraspZoom
(Miyaki et al., 2009)
Pressure-based Text Entry
(Brewster et al., 2009)
Squeezing the Sandwich
(Essl, 2009)
Pressure-based Menu Selection (Wilson et al., 2010)
ForceGestures (Heo et al., 2011)
Indirect Shear Force
(Heo et al, 2013)
Multi-digit Pressure Input (Wilson et al., 2012)
ForceDrag (Heo et al., 2012)
Hardware Augmentation Approach

9. PREVIOUS WORK
Hardware Augmentation Approach to Enable Pressure Interaction

10. PREVIOUS WORK
Hardware Augmentation Approach
Specialize Hardware offers reliable and fast input pressure readings.
However,
- It is still not widely supported in current mobile devices.
- It represents additional costs (production cost for vendors and maintenance costs for users).

11. c
t
a
PREVIOUS WORK
Software Approach to Enable Pressure Interaction
A tangible controller (Kato et al., 2009)
Vision-based Force Sensor (Sato et al., 2012)
The Fat Thumb
(Boring et al., 2012)
Muscle Tremors (Strachan et al., 2004)
Use the Force or something
(Essl et al., 2010)
ForceTap
(Heo et al., 2011)
Expressive typing
(Iwasaki et al., 2009)
camera
touchscreen
accelerometer
c
t
a

12. Technique (Author)
Sensor Repurposed
P levels
Modality emulated (type)
Property Used
A/P
A tangible controller (Kato et al., 2009)
Camera
(cont)
Pressure (S)
Marker position and size
P
Vision-based Force Sensor (Sato et al., 2012)
Camera
(cont)
Pressure (S)
Marker position and size
P
Muscle Tremors (Strachan et al., 2004)
accelerometer
2
Pressure (S)
Vibration
P
Expressive typing
(Iwasaki et al., 2009)
Accelerometer
Keyboard
2
Pressure (E)
physical movement
P
ForceTap
(Heo et al., 2011)
Accelerometer
Touchscreen
2
Pressure (E)
physical movement
P
Use the Force or something
(Essl et al., 2010)
Accelerometer
N/A
Pressure (E)
physical movement
P
The Fat Thumb
(Boring et al., 2012)
Touchscreen
2
Pressure (E)
Contact size
P
A, Active; P, Passive; P/A, Passive/Active; S, Streaming based; E, Event-based; R, Recognition-based;
PREVIOUS WORK
Software Approach to Enable Pressure Interaction

13. PREVIOUS WORK
Software Approach to Enable Pressure Interaction
-They do not continuously measure pressure. (e.g., ForceTap, MicPen, and Expressive typing)
-The interaction area is limited by hardware settings. (e.g., PseudoButton)
-An additional calibration process is needed. (e.g, The Fat Thumb, and Muscle tremor)
These approaches successfully estimated the input pressure using only inertial sensors on mobile devices. However,

14. OUR METHOD
VibPress

15. OUR METHOD
Vibration Absorption As Proxy For Pressure Input
Amount of pressure on a mobile device can be approximated by using an accelerometer to measure the spatial displacement generated when the internal vibration motor vibrations.

16. OUR METHOD
Implementation
-Implemented on the Samsung Galaxy S3, running Android OS 4.0.4.
-Activated internal linear vibration motor with a continuous pulse at maximum amplitude (setting on OS).
-Sampled the data from the internal three-axis accelerometer at 100Hz.
-Passed through a low-pass filter to reduce sampling noise and Euclidean distance between last reading and its predecessor is computed.
-Finally, we used the sum of these values to reach a good estimation of the amount of pressure exerted on the device.

17. OUR METHOD
VibPress
10-2012-0110731, Method and apparatus for sending touch strength on user terminal and method, Korea Patent, Pended (2012.10.05)
10-2012-0066225, Apparatus and method for touch Sensing, Korea Patent, Pended (2012.06.19)
Finally, we built software that reliably and quickly estimate the input pressure by measuring the spatial displacement absorbed. And we filed some patents based on the technique.

18. PREVIOUS WORK
GripSense (Goel et al., Oct, 2012)
Muscle tremor (Gyroscope) + + Finger size (Touchscreen) Machine learning algorithm
Damping effect (Gyroscope)

19. PREVIOUS WORK
Main differences from the previous work
GripSense (Goel et al., 2012)
Technique
P levels
Sensor Used
Estimation
Method
A/P
Postures
Explored
GripSense
(Goel et al., 2012)
<= 3
Gyroscope
Touchscreen
Machine-learning
Active
Pressure
VibPress
(Hwang et al., 2013)
<= 6
Accelerometer
Real-time readings
Active
Pressure
Squeeze
Our approach is fast and lightweight, supporting two types of gestures.

20. EVALUATION
VibPress

21. EVALUATION
Pilot study The goal of the pilot study was to establish the average minimum and maximum pressure that user could exert on the mobile device in order to derive an appropriate estimation of the maximum number of distinguishable pressure levels. Usability study The goal of the usability study was to test the input performance (time, errors, and cognitive load) for different pressure levels and hand gripping gestures derived from the pilot.

22. Pilot Test
-4 participants (2 women) aged between 26 and 33 (average 29.5 , SD 3.1)
-Asked to sequentially apply maximum and minimum pressure with their dominant hands using two postures (touch and grip).
-For touch gesture, participants asked to press the center of the screen with their thumbs.
-For the grip gesture, participants asked to hold the device with the dominant hand and activated the vibration motor by clicking a button with the other hand.
-Every press event took 1.5 seconds and repeated ten times.
-We discarded the first 500ms to allow for pressure stabilization.
Touch
Grip

23. Pilot Test : Result
Ranges of average minimum and maximum pressure according to hand-gripping type.

24. Usability Test
The graphical interface used for testing pressure input with 2 levels (L2), 4 levels (L4) and 6 levels (L6).
Continuous visual feedback + Dwell

25. Usability Test
-12 volunteers (6 women) with ages between 24 and 33 (average 27.5, SD 2.5).
-Participants were asked to familiarize themselves with the device for a maximum of five minutes.
-We asked users to perform 36 successful targeting trials (the first 12 discarded as practice) for each pressure level (L2, L4, L6) with two hand gestures (press and squeeze).
-NATA TLX questionnaire for each pressure level.
-Every target level was evenly represented and balanced, collecting data for a total of 288 trials per hand gesture type.
-We recorded measures of performance (e.g., the selection time of successful trials, number of wrong selections, and the variations of the pressure within the targets).
-The experiment took approximately one hour.

26. Usability Test : Result
Metrics for selection times and error rate (low is better).
(F(2,11)=126.6, p<0.01)
*
*
(F(1,11)=6.3, p<0.05)
Overall error rates for levels L2, L4, and L6 are, respectively, 0.3%, 7.6% and 12.5% for the press gesture, and 0.7%, 11.5%, and 33% for the squeeze posture.
(F(2,11)=25.1, p<0.01)
*
*
(F(1,11)=5.1, p<0.05)

27. Usability Test : Result
Users’ cognitive workload with a TLX.
The error rate is also reflected in the results from the TLX (cognitive load is directly proportional to the number of pressure levels).
(F(2,11)=84.5, p<0.01)
*

28. Usability Test : Result
% of error distribution among the selection levels for L6 (low is better).
The distribution of errors was uneven and most errors happened in the central targets (especially in the box5) rather than at the extremes.
Box 6
Box 1
268 (MAX PRESSURE)
0 (MIN PRESSURE)
coarse
smooth

29. Usability Test : Result
-Most participants expressed that VibPress is enjoyment and quick adoption.
-However, some reported that “continuous vibrations are somehow disturbing.”
-Overall, participants agreed that for L2 and L4, the performance and the usability level were satisfactory
-Despite the accuracy level, users preferred the squeeze gesture to the press one, as they felt it took less physical effort.
Interview

30. Usability Test : Result
VibPress shows …
-Selection times similar to those obtained with specialized hardware (Cechanowicz et al., 2007; Ramos et al., 2004).
-But faster (Goel et al., 2012).
-With fewer errors than software pressure techniques (Goel et al., 2012; Heo et al., 2011; Hwang et al., 2012).
When comparing these results with those from previous work for analogous dwell-based targeting tasks,

31. VIDEO
VibPress

33. CONCLUSION
VibPress

34. LIMITATION
Compatibility across devices (different motors or device cases propagate vibrations differently).
Battery consumption due to the continuous activation of the vibration motor. (However, these issues could be alleviated by using frequent but short vibration patterns at lower intensities).

35. CONCLUSION
-We showed evidence that, with continuous visual feedback, users can reliably and quickly input with accuracy ranging from 99.7% to 67% and from ~1 to ~4 seconds interaction time, depending on the different pressure levels and hand gripping used.
-We also described how different users favorably judged the usability and potential applications of the system.
-Future work will aim to identify hand postures and specific pressure for selective portions of the screen. Finally, we also plan to measure pressure inputs using tangible objects (e.g., styli, tokens) rather than fingers.

36. END
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