This document summarizes a student project on applying bio-acoustic sensor technology to Skinput. Skinput uses skin as an input device by detecting sound vibrations from finger taps. The students designed an armband with an acoustic detector, pico-projector, and Bluetooth. They tested finger tap detection accuracy in different configurations, finding 5-finger input on the forearm achieved the highest accuracy. The document discusses applications for calling, texting and education, and outlines advantages like portability and reduced social distraction, while also noting current disadvantages like cost and bulkiness. It proposes future directions like smaller form factors and incorporating the technology into more devices.

1. APPLICATION OF BIO-ACOUSTIC
SENSOR ON SKINPUT TECHNOLOGY
APPLIED ELECTRONICS & INSTRUMENTATION ENGINEERING
Under Supervision of Prof.
Hiranmoy Mandal
Presented By-
SNIGDHA BASAK
(Roll No.:16905516013)
&
SNEHA BASU
(Roll No.:16905516014)

2. INTRODUCTION:
Skinput is a technology that uses the skin as
input device.
It was developed by Chris Harrison, D. Tan &
D. Morris at Microsoft Research(2010).
Using it to simply tap our skin, we can make
phone calls, send text as well as listing music by
tapping our arm.
There’s no need to interact with the gadgets
directly.

3.  Physical interface needed for Touch screen,
but for Skinput no physical interface required.
 Touch screen leads to low battery life,
whereas Skinput doesn’t affect this.
 Touch screen is layered on top of electronic
visual display, whereas Skinput uses human
body as input device.

4.  An Acoustic Detector to detect sound vibrations &
ultra low frequencies, built into arm-band.
 A microchip-sized Pico-projector to display menu.
 A Bluetooth Connection to connect Bio-Acoustic
sensing element with mobile.

6.  Longitudinal Wave Propagation:
o Finger impacts creates this wave causing
vibration in internal skeletal structure.
o Moves into & out of bone through soft
tissues.
 Transverse Wave Propagation:
o Finger impacts creates this wave as
ripples.
o Moves directly along arm surface.

7. Five Finger Input:
oOn tips of each of five fingers
oArmband is in approx. 7cm above
Whole Arm Five Finger Input:
oOn the forearm and hand : arm, wrist,
palm, thumb & middle finger
oArmband is above elbow or below it approx
3cm aside from elbow
Fore-arm Ten Finger Input:
oIn overhead of elbow
oArmband is in approx. 7cm above joint part

8.  Five Finger Input:
o Avg. 87.7%
 Whole Arm Five Finger Input:
o Arm-band below elbow 95.5%
o Arm-band above elbow 88.3%
 Fore-arm Ten Finger Input:
o Avg. 81.5%
 BMI Effect:
o Increasing BMI accuracy decreases
 Walking & Jogging:
o While walking avg. 100% & jogging avg. 83.3%

9. Make phone calls, text messages
Used in education system(calculator) Used by paralyzed people
Play games just moving hands

10. ADVANTAGES
 Easy to access when your phone is not available
 Larger buttons reduce the risk of pressing the wrong buttons
 Body is portable and always available
 allows users to interact more personally with their device
DISADVANTAGES
 The arm band is currently bulky
 As it’s a new technology the cost is high for normal people
 The easy accessibility will cause people to be more socially
distracted
 Degradation of accuracy due to longer time or other causes

11.  The shape could be made much more simpler like in Wrist
watch sized or going to Ring Shape
 Incorporate with more devices like use as keyboard of PC
 Video projectors will be made using this technology
 Google will very soon going to release this technology in the
form of wearable password ring
 Making banking system & ATM transactions’ more secure by
using NYMI(a tiny device with Skinput technology)

12.  The research is still going on- to make
armband smaller, extend accuracy level,
incorporate more devices, etc.
 This system performs well even if your
body is in motion.
 Being very interesting technology, it’s fate
depends on how Microsoft is going to
make their decision.

13. I. https://www.ijser.org/researchpaper/BIO-
ACOUSTIC-SENSING-OF-SKINPUT-
TECHNOLOGY.pdf
II. https://www.slideshare.net/VarshaRajput3/sk
input-37646995?from_m_app=android
III. https://en.wikipedia.org/wiki/Skinput

14. Snigdha Basak(Roll No.:13)
&
Sneha Basu(Roll No.:14)
Department of AEIE