Skinput is a technique developed by researchers at Carnegie Mellon University and Microsoft that uses the human body as a touch interface. It involves wearing sensor armbands that can detect finger taps on the skin through bio-acoustics, translating the taps into device inputs. This allows users to control audio players, phones, games, and other devices by simply tapping on their arm. The armbands pick up longitudinal and transverse waves generated by taps and can accurately classify input locations and gestures with high accuracy rates. Potential applications include controlling mobile devices, gaming, browsing, and audio playback through taps on the skin.

1. SKINPUT
Appropriating the Body as an Input
surface
PRESENTED BY:
M.DHANASRI
SSIT

2. Overview: what is Skinput
• Skinput is a collaboration between Chris Harrison of Carnegie
Mellon University and Dan Morris at Microsoft’s research lab in
Redmond in Washington.
• Due to the advantages of Touch Screen Gadgets , they have
become very popular .
• Skinput is also an Touch Screen one which was using body as
an interface

3. Touch-Screen

4. Skinput

5. What Skinput does
 Skinput allows users to simply tap their skin in order to
control audio devices, play games, making of calls, and
navigate different types of browsing systems hierarchically.
 It applies on the skin on the series of sensors , where they
can be activated on the arm at different places.
 Each part of the body can be created by the different types
of variations on the depending on the bones, muscles and
tendons.

6. Skinput works by:
Bio-Acoustics
Bluetooth
Pico-Projector

7. Pico-Projector:
 A very Small Projector basically used in Gadgets.
Ex: Spice Popcorn(mobile cum Projector)

8. Bio-Acoustics:
 When finger taps on he skin , it leads to formation of two
different types of waves called as
Longitudinal waves
Transverse waves
 These waves makes to activate whole concept of Skinput.

9. Bio-Acoustics Works:
Transverse wave Propagation Longitudinal Wave Propagation

10. Bio-Acoustics Sensing:
These signals can be sensed and worked upon by wearing Wave
Sensor Arm Bands.

11. Arm Band:
 The decision to have the two sensor
packages was focused by our
motivation on the arm.
 We employ a Mackie Onyx 1200F
audio interface to digitally capture
data from the ten sensors.
 Each channel was sampled at
5.5kHz a sampling rate.

12. Processing model:
 This program performed three key
functions.
 First, it provided a live visualization of
the data from our ten sensors
 Second, it segmented inputs from the
data stream into independent
instances(taps) .
 Third, it classified these input
instances.

13. Experimental Conditions:
• For the Experiment, we
selected three input groupings
from the multitude of possible
location combinations to test.
• We believe that these
groupings, are of particular
interest with respect to
interface design, and at the
same time, push the limits of
our sensing capability.

14. Supplemental Experiments:
 Walking and Jogging
 Single-Handed Gestures
 Surface and Object Recognition
 Identification of Finger Tap Type
 Segmenting Finger Input

15. Accuracy:
Accuracy of the three whole-arm-centric
conditions.
Accuracy was significantly lower for
participants with BMIs above the 50th percentile

16. Applications:
• Mobiles.
• Gaming applications.
• Audio players.
• Browsers.

17. Conclusion:
Skinput is an appropriating the human body as an input surface which
was a novel, wearable bio-acoustic sensing array that we built into an
armband in order to detect and localize finger taps on the forearm and
hand , it even performs well when the body is in motion also

18. THANK YOU