1. SKIN PUT:
APPROPRIATING THE BODY AS
AN INPUT SURFACE
P.PRANNOY CHAKRAVARTHI
&
K.B.S.MANIKANTA
BHIMAVARAM INSTITUTE OF ENGINEERING & TECHNOLOGY

2. EVOLUTION OF TOUCHSCREEN
Motion
tracking
is the principle
used in touch-
screen
WHAT’S NEXT?

3. WHAT IT IS?
A novel input technique that allows
the skin to be used as a finger input
surface.
To capture this acoustic information ,
http://walyou.com/touch
they developed a wearable armband that screen-interface-on-your-
is non-invasive and easily removable arm-with-skinput/

4. ENERGY THROUGH ARM
 Transverse Wave Propagation
Longitudinal Wave Propagation

5. A VIDEO ON SKINPUT

6. ARM BAND
 Two arrays of five sensing elements.
 Bone conduction microphones.
 Microphones Placed near:
 Humerus
http://www.robaid.com/gadgets/
 Radius skinput-.htm
 Ulna

7. HOW SKINPUT WORKS
 Data was then sent from the client over a
local socket to our primary application,
written in Java.
 Key function of application are:
Live visualization. http://www.bestnweb.com/sk
Segmentation of data stream. input-touch.html
Classification of Input instances.

8. EXPERIMENT
Participants
 13-> 7 female, 6 male.
 Ages ranged from 20 to 56.
 Body mass indexes (BMIs) ranged
 From 20.5 (normal) to 31.9 (obese).
 Each participant was made to memorize the
locations for a minute .

9. LOCATIONS

10. RESULTS
Five Fingers
 When classification was incorrect, the system
believed the input to be an adjacent finger 60.5%
of the time.
 Ring finger constituted 63.3% percent of the
misclassifications.

11. RESULTS
Whole Arm
 Below elbow placed the sensors
closer to the input targets than
the other conditions.
 The margin of error got double
or tripled when eyes were closed.

12. RESULTS
Fore Arm
 Classification accuracy for the
ten-location forearm condition
stood at 81.5%.

13. BMI EFFECTS
 High BMI is correlated with
decreased accuracies.
 No direct relation with gender of the
participant.

14. ADVANTAGES
UI will appear much larger than on
screen
Can be used without a visual screen
Ideal for anyone with little to or no
eyesight

15. CONCLUSION
Since we cannot simply make buttons and
screens larger it will be an alternative
approach
Skin put's are not available yet, but
could be in the next few years.

16. REFERENCES
1. Ahmad, F., and Musilek, P. A Keystroke and Pointer Control
Input Interface for Wearable Computers. In Proc. IEEE
PERCOM ’06, 2-11.
2. Amento, B., Hill, W., and Terveen, L. The Sound of One
Hand: A Wrist-mounted Bio-acoustic Fingertip Gesture Interface.
In CHI ‘02 Ext. Abstracts, 724-725.
3. Argyros, A.A., and Lourakis, M.I.A. Vision-based Interpretation
of Hand Gestures for Remote Control of a Computer
Mouse . In Proc. ECCV 2006 Workshop on Computer Vision in
HCI, LNCS 3979, 40-51.
4.Images from www.google.com