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Differentiation and classification of different materials on a touch-screen using a piezoelectric contact microphone

Björn, Anders LU (2016) EEM820 20161
Department of Biomedical Engineering
Abstract
In this report, a potential improvement of an optical touch screen solution by
means of acoustic sensing is presented. The goal is to utilize the different vibration
patterns that arise when different materials touch the screen to be able to identify
them. This identification of different materials opens up new opportunities to give
input to the touch-device which could potentially replace menu bars or touch-andhold
interaction that exists today. The ability to discriminate between object also
gives the opportunity for different objects to represent different things, such as
colors, tools or unique users. A piezoelectric accelerometer is used to collect the
sound signals, which are then classified using the K-Nearest-Neighbour... (More)
In this report, a potential improvement of an optical touch screen solution by
means of acoustic sensing is presented. The goal is to utilize the different vibration
patterns that arise when different materials touch the screen to be able to identify
them. This identification of different materials opens up new opportunities to give
input to the touch-device which could potentially replace menu bars or touch-andhold
interaction that exists today. The ability to discriminate between object also
gives the opportunity for different objects to represent different things, such as
colors, tools or unique users. A piezoelectric accelerometer is used to collect the
sound signals, which are then classified using the K-Nearest-Neighbour method
to identify which material that touched the screen. The result shows that the
classification for three different objects was done with a 96% correct classification.
If only two different pens are used, the correct classification goes above 99%.
The report further describes some of the key factors that needs to be taken in
account when developing such an acoustic sensing system, such as force, distance
and location of the taps on the screen. Those factors does all seem to alter the
frequency spectrum in some way. (Less)
Popular Abstract (Swedish)
Klassificering av pennor av olika material till touch-skärm

Genom att koppla en kontaktmikrofon till en touchskärm och undersöka de vibrationsmönster som uppstår då olika objekt rör vid skärmen har en dator tränats till att känna igen olika typer av material. Om en filt och en träpenna användes kunde datorn känna skillnad på vilket material som användes i mer än 99,5% av fallen. Resultatet av projektet innebär att det finns möjlighet för pennor gjorda av olika material att nu representera specifika användare, färger eller verktyg i de program som körs på enheter med touchskärm genom att koppla en kontaktmikrofon till skärmen.
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author
Björn, Anders LU
supervisor
organization
course
EEM820 20161
year
type
H2 - Master's Degree (Two Years)
subject
language
English
additional info
2016-15
id
8889313
date added to LUP
2016-09-12 11:41:47
date last changed
2016-09-12 11:53:05
@misc{8889313,
  abstract     = {In this report, a potential improvement of an optical touch screen solution by
means of acoustic sensing is presented. The goal is to utilize the different vibration
patterns that arise when different materials touch the screen to be able to identify
them. This identification of different materials opens up new opportunities to give
input to the touch-device which could potentially replace menu bars or touch-andhold
interaction that exists today. The ability to discriminate between object also
gives the opportunity for different objects to represent different things, such as
colors, tools or unique users. A piezoelectric accelerometer is used to collect the
sound signals, which are then classified using the K-Nearest-Neighbour method
to identify which material that touched the screen. The result shows that the
classification for three different objects was done with a 96% correct classification.
If only two different pens are used, the correct classification goes above 99%.
The report further describes some of the key factors that needs to be taken in
account when developing such an acoustic sensing system, such as force, distance
and location of the taps on the screen. Those factors does all seem to alter the
frequency spectrum in some way.},
  author       = {Björn, Anders},
  language     = {eng},
  note         = {Student Paper},
  title        = {Differentiation and classification of different materials on a touch-screen using a piezoelectric contact microphone},
  year         = {2016},
}