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Think touch screens are cool? What about touchskins?
Skinscreens?
Microsoft Introducesinput technology- ”Skinput”.
CONTENTS
Introduction
What is skinput
How it works
Principle of skinput
Advantages
Disadvantages
Application
Conclusion
IntroductionSkinput is named because it uses the human skin.
Skinput, is a sensor system.
Developed by chris harrison(Mellon university),Microsoft research
Reduce gizmo accessories and multiple gadgets.
What is skinput Giving input through skin
It listen to vibrations in our body
Skinput uses a series of sensors to track where a user taps on his arm.
Provide an always available mobile input system
Turns The body into a touch-screen interface.
The arm is an instrument
How it works
It needs bluetooth connection
A microchip-sized pico projector
An acoustic detector to detect sound vibrations
Working• STEP 1 :• When User tap on skin(Hand),the Bio-Acoustics &
Sensors study the sound waves.
• Variations in bone density,size and mass and the soft tissue and joints create Acoustically different locations
• When a finger taps the skin ,several distinct forms of acoustic energy are produced
• Londitudinal wave• Transverse wave
Transverse waves
When you tap your skin with your finger you generate transverse waves
Tapping on soft regions of the arm create higher amplitude transverse wave than tapping on boney areas
Longitudinal waves
Cause internal skeletal structure to vibrate
These waves travel through the soft tissues of the arm
Joints play an important role in making tapped locations acoustically distinct.
This makes joints behave as acoustic filters.
Bio-Acoustics:sensing• Signal is sensed and worked
upon
• This is done by wearing sensor armband
• The two sensor packages shown
• Each contain five, specially weighted, cantilevered
• piezo films, responsive to a particular frequency range.
Armband Prototype
• Two arrays of five sensing elements incorporated into an armband
• Two sensor packages focus on the arm of input
• One package was located near the Radius other near the Ulna
• Signals transmitted though denser bones
Step 2:
• Bio-Acoustics & Sensors are Connected to the mobile Bluetooth.
Step 3:a system use a tiny projector to display a screen onto your forearm or hand
Then the menu displayed by the Pico-Projecter on user’s hand
• projector display image on arm finger tap on arm
vibrations produced and passed
through bones onto skin
electronic signals produced then detected by detector in
armband in the form of music etc
Processing
Ten channels of acoustic data generated by threefinger taps on the forearm, followed by three taps on the wrist.
The exponential average of the channels is shown in red. Segmented
input windows are highlighted in green
ExperimentParticipants:To evaluate the performance of our system, 13 participants (7 people) were recruited .
These participants represented a diverse cross-section of potential ages and body types.
Ages ranged from 20 to 56 (mean 38.3), and computed body mass indexes (BMIs) ranged from 20.5 (normal) to 31.9 (obese).
Experimental Conditions:Three input groupings from the multitude of possible location combinations to test were selected
These groupings, illustrated in Figure ,are of particular interest with respect to interface design, and at the same time, push the limits of our sensing capability.
From these three groupings, five different experimental conditions are derived ,which are described as:
Fingers (Five Locations)
One set of gestures we tested had participants tapping on the tips of each of their five fingers.
Provide clear, discrete interaction points, which are even already well-named (e.g., ring finger).
In addition to five finger tips, there are 14 knuckles (five major, nine minor), which, takentogether, could offer 19 readily identifiable input locations on the fingers alone.
The fingers are linearly ordered, which is potentially useful for interfacesacoustic information must cross as many as five (finger and wrist) joints to reach the forearm
We decided to place the sensor arrays on the forearm, just below the elbow.
Whole arm (five locations)
We selected these locations for two important reasons.
First, they are distinct and named parts of the body (e.g., “wrist”).
We used these locations in three different conditions.
One condition placed the sensor above the elbow, while another placed it below.participants repeated the lower placement condition in an eyes-free context:
participants were told to close their eyes and face forward, both for training and testing.
Forearm (10 locations)
This experimental conditionused 10 locations on just the forearm
To maximize the surface area for input, we placed the sensor above the elbow
Rather than naming the input locations, we employed small, colored stickers to mark input targets.
we believe the forearm is ideal for projected interface elements; the stickers served as low-tech placeholders for projected buttons.
BMI Effects
• Susceptible to variations in body composition
• Prevalence of fatty tissues and the density/mass of bones
• Accuracy was significantly lower for participants with BMIs above the 50th percentile
Accuracy
To maximise the surface area for input,we placed the sensor above the elbow,leaving the entire forearm free
This increases input consistency
Accuracy does drop when 10 or more locations are used
The sensor can spot many different locations on the arm
This experiment explored the accuracy of our system.
Each participant trained and tested the system while walking and jogging on a treadmill.
Three input locations were used to evaluate accuracy the rate of false positives and true positives was captured.
In both walking trials, the system never produced a falsepositiveinput.
In the jogging trials, the system had four false-positiveinput events (two per participant) over 6 min of continuousjogging.
Accuracy, however, decreased to 83.3% and 60.0% for the male and female participants, respectively.
Walking and jogging
Single-Handed Gestures
• It is a bimanual gestures• First had participants
tap their index,middle, ring and pinky fingers against their thumb ten times each
• Independent experiment that combined taps and flicks
Surface and Object Recognition
• Ability to identify the Operating System
• participants to tap their index finger against 1) a finger on their other hand 2) a paper pad 80 pages thick
3) an LCD screen.
Design and Setup
• Participant performing tasks having five conditions in randomized order
• One sensor package rested on the biceps• Right-handed participants had the armband
placed on the left arm• Tightness of the armband was adjusted to be
firm
PROCEDURE
• Experimenter walked through the input locations to be tested
• Participants practiced the motions for one minute with each gesture
• To convey the appropriate tap force• To train the system, participants were
instructed to tap each location ten times
Higher accuracies can be achieved by collapsing the ten input locations into groups.A-E and G were created using a design-
centric strategy. F was created following analysis of per-location accuracy data
RESULT
• Classification accuracies for the test phases in the five different conditions
• Rates were high, with an average accuracy across conditions of 87.6%
• The correlation between classification accuracy and factors such as BMI, age, and sex
Future Skinput
Research is going on to-
Make armband smaller
Incorporate more devices
Extend accuracy level
ADVANTAGES
No need to interact with the gadget directly.
Don’t have to worry about keypad.
Skinput could also be used without a visual interface
People with larger fingers get trouble in navigating tiny buttons and keyboards on mobile phones. With Skinput that problem disappears.
Disadvantages
Individuals with visible disabilities cannot use this product.
The arm band is currently bulky.
the visibility of the projection of the buttons on the skin can be reduced if the user has a tattoo located on their arm
If the user has more than a 30% Body Mass Index Skinput is reduced to 80% accuracy
The easy accessibility will cause people to be more socially distracted
Applications
• The Skinput system could display an image of a digital keyboard on a person's forearm.
• Using Skinput, someone could send text messages by tapping his or her arm in certain places
• while Walking and jogging, we can listen to music.
Conclusion
This system performs very well even if the body is in motion
in the future your hand could be your iPhone and your handset could be watch-sized on your wrist.