chris harrison developed Skinput technology

1. ____________________________
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Sorav saha - electronicsBy
SKINPUT
TECHNOLOGY

2. MOTIVATION
Electronics gadgets ,especially
Touchscreens are prevalent
They suffer from:
 Limited interaction space
 Less accurate interactions
 Cannot make buttons and screens larger without
losing the primary benefits of small size

3. displayed at was at Microsoft’s
TechFest 2010

4. What is “Skinput”?
 Skinput is technology that appropriates
the human body for acoustic transmission.
 It allows the skin to be used as input
surface, allows to interact with body .
 Was devloped by Chris Harrison(Carnegie
Mello University),Microsoft Research.

5. Mechanical phenomenon :
 As the skin taps on the skin; acoustic
energies are formed.
 Two forms of the waves are formed:
1. Transverse.
2. Longitudinal.

6.  Sensors are activated by the waves
moving underneath it.
 Transverse waves formed moves outward
form the point of contact
 Transverse waves formed at soft part of
the skin is of higher amplitude than the
bony part of skin.

8. Cont…
 Some energy is transmitted inward, toward
the skeleton.
 These are longitudinal waves; excites the
bane.
 This excitation vibrates soft tissues
surrounding the entire length of the bone,
resulting in new longitudinal waves that
propagate outward to the skin.
 The sensor is activated as these waves hits
underneath it.

10. Sensing :
 Instead of a single sensing element
with a flat response curve, an array
of highly tuned vibration sensors are
used.
 Bio –acoustic sensor, its employed
with small, cantilevered piezo films.

11. Cont…….
 Cantilever is adjusted in the resonating
frequency.
 Adjustment done by adding weight.
 Irresponsive to singal parallel on the skin;
reduce the noise due other signal.

12. About the sensor design…
relatively inexpensive.
 Can be manufactured in a very small form
factor, rendering it suitable for inclusion in
future mobile devices.

13. Requirements :
 An acoustic detector to detect
sound vibrations.
 It uses a microchip-sized pico
projector to display menu.
 It needs bluetooth connection.
Bio
Acoustics
Pico
Projector
Bluetooth

14. ARMBAND
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INSIDE VIEW
OUTSIDE VIEW

15. The design :
 The prototype features has two arrays of five
sensing elements, incorporated into an
armband form.
 Each sensor array is sensible to particular set
of frequencies:
1. Upper – low frequencies – fleshier.
2. Lower – high frequencies – denser
bones.

16. The processing :
 Employ a mackie onyx 1200f audio
interface to digitally capture data form the
ten sensors.
 Each channel is sampled at 5.5 khz.
 This is connected to conventional desktop
computer , where a thin client written in
C interfaced with the device using the
ASLO protocol.

17. Key functions :
 This program provides a live visuization of the
data from the ten sensors.
 Its segments inputs from the data stream into
independent instances.
 Classifies these input instances.
 The audio stream is segmented into
individual taps using an absolute
exponential average of all ten channels.

18. Analysis :

19. Experimental conditions :
 Fingers (Five Locations)
 Whole Arm (Five Locations)
 Forearm (Ten Locations)

20. RESULTS
FIVE FINGERS
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Accuracy remained high for five finger condition
averaging 87.7%
When classification was incorrect, the system
believed the input to be an adjacent finger
60.5% of the time.
Ring finger constituted 63.3% of the
misclassifications.

21. WHOLE ARM
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 Below-elbow placement performed the best posting
at 95.5% accuracy.
 Moving the sensor above the elbow reduced
accuracy to 88.3 (7.2% drop).
 The eyes free input condition yielded lower
accuracies than other conditions averaging
85%(10.5% drop)

22. FOREARM
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Classification accuracy for the 10 location forearm
condition stood at 81.5%.
Higher accuracies can be achieved by collapsing the
10 locations into groups.

23. BMI effects:
1. BMI –Body mass index.
2. to assess how these variations affected
our sensing accuracy.
3. the participants with the three highest
BMIs(29.2, 29.6, 31.9) produced the three
lowest average accuracies.

24. Advantages :
 The projected interface can appear much
larger than it ever could on a device’s
screen.
 Arm can be brought closer to face (or vise
versa ) to see the display close up.
 colour contrast can be adjusted by
dimming the light so that a better picture
will be visible if skin and the text are too
similar in color during daylight.

25. conclusion :
 The technology itself is intriguing , and have
more application other than always avaibility.
 Skinput is very intersting technology . But its fate
will ultimately depend on how committed
Microsoft is to making it a commercial reality and
how soon.