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Human ComputerInteractionusingHandGesture SilasWanandHung T. Nguyen,SeniorMember,
IEEE Abstract—Handgesture isaverynatural formof humanexpensive andingeneral donot
promote free movementof interactionandcanbe usedeffectivelyinhuman computerinteraction
(HCI).Thisprojectinvolvesthe designandimplementationof aHCI usinga small hand-wornwireless
module witha3-axisaccelerometerasthe motionsensor.The small stand-alone unitcontainsan
accelerometerandawirelessZigbee transceiverwithmicrocontroller.Tominimize intrusivenessto
the user,the module isdesignedtobe small (3cmby4 cm).A time-delayneural networkalgorithmis
developedtoanalyze the time seriesdatafromthe 3-axisaccelerometer.Powerconsumptionis
reducedbythe noncontinuoustransmissionof dataand the use of low-powercomponents,efficient
algorithmandsleepmode betweensamplingforthe wirelessmodule.A home control interface is
designedsothatthe usercan control home appliancesbymoving throughmenus.The results
demonstrate the feasibilityof controllinghome appliancesusinghandgesturesandwouldpresent
an opportunityfora sectionof the agingpopulationanddisabledpeople toleadamore
independentlife.I.INTRODUCTION HISpaper describesthe designandimplementationof an
accelerator-basedhandgestureclassificationsystemwhichcanbe usedforhumancomputer
interaction(HCI) applications.A home control interface isdesignedsothatthe user can control
home appliancesbymovingthroughmenus.Thisapplicationistargetedtowardsthe agedand
disabledpeople whohave problemsusingremote control.The mainapproachesforanalyzingand
classifyinghandgesturesforHCIinclude glove-basedtechniquesandvisionbasedtechniques. The
glove-basedtechniquesuse sensorstomeasure the positionsof the fingersandthe positionof the
handin real-time [1-4].The NintendoPowerGlove,launchedin1989, wasthe firstperipheral that
createdhumanhand gesturesonthe televisionorcomputerscreen.Itusesbendsensorstodetect
movementof fingersaswell asmagnetic/inertiatrackingdevicestotrackthe pitch,yaw,roll and
accelerationof the whole glove.The CyberGlove IIfromImmersionisamore sophisticatedsystem
whichhas multiplesensorssuchasbendsensors,abductionsensorsandpalm-arcsensorsandcan
be usedto obtainaccurate three-dimensional representationsof the hand.Recently,itwasusedto
describe ambiguoussetsof phrasesconsistingof three tofive handgestures[1].However,gloves
tendto be This workwassupportedinpart by AustralianResearchCouncilunderDiscoveryGrant
DP0666942. H. T. NguyeniswithFacultyof Engineering,Universityof Technology,Sydney,
Broadway,NSW2007, Australia(phone:+612-9514-2451; fax:+61 2 9514 2868; e-mail:
Hung.Nguyen@uts.edu.au).S.WaniswithFacultyof Engineering,Universityof TechnologySydney,
Broadway,NSW2007, Australia(e-mail:silas.wan@student.uts.edu.au).the hand.The vision-based
techniquescanbe either3Dor 2D approaches.As3D handmodelsare quite complex,the
classificationof gesturesfrom3Dmodelsiscomputationallyintensivemakingreal-time
implementationdifficult.Onthe otherhand,the 2D approach isrestrictedtothe lesscomplex
problemof classifyingwell-definedstaticgestures[5-8].Recentexistingsystemsusinginertial
devicesincludethe NintendoWii.Itusesthe ADXL330accelerometerfromAnalogDevices.The
nunchukusesthe LIS3L02AL accelerometerfromSTMicroelectronics.The Wii remote isawireless
device thatcommunicateswiththe NintendoWii viaBluetooth.Toobtainabsolutepositionfor
games,an infraredsensorisused(Wii InfraredSensorBar).Infraredsensors,unlike accelerometers,
provide goodlowfrequencyinformationbutnothighfrequencyinformation.Thusthe twosensors
can be fusedusingoptimal filteringtoobtainaccurate positionandmovementinformation.Inthis
paper,we describe the developmentof bothhardware andsoftware fora wirelesshandgesture
recognition system.SectionIIprovidesanoverview of the handgesture recognitionmodule design
and the relevantsoftware forthe system.SectionIIIpresentsthe developmentandresultsof an
embeddedneuralnetworkimplementation.SectionIV providesaconclusion forthisstudy.II.
METHODS A.WirelessHandGesture Module The SensorNode BlockasshowninFig.1 isthe heart of
thisproject.Itconsistsof a JennicJN5139 wirelesstransceivermodule,anAnalogDevicesADXL330
accelerometer,alithiumpolymerbatteryandacharger system.The JennicJN5139 Zigbee Module is
a surface

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  • 1. Human ComputerInteractionusingHandGesture SilasWanandHung T. Nguyen,SeniorMember, IEEE Abstract—Handgesture isaverynatural formof humanexpensive andingeneral donot promote free movementof interactionandcanbe usedeffectivelyinhuman computerinteraction (HCI).Thisprojectinvolvesthe designandimplementationof aHCI usinga small hand-wornwireless module witha3-axisaccelerometerasthe motionsensor.The small stand-alone unitcontainsan accelerometerandawirelessZigbee transceiverwithmicrocontroller.Tominimize intrusivenessto the user,the module isdesignedtobe small (3cmby4 cm).A time-delayneural networkalgorithmis developedtoanalyze the time seriesdatafromthe 3-axisaccelerometer.Powerconsumptionis reducedbythe noncontinuoustransmissionof dataand the use of low-powercomponents,efficient algorithmandsleepmode betweensamplingforthe wirelessmodule.A home control interface is designedsothatthe usercan control home appliancesbymoving throughmenus.The results demonstrate the feasibilityof controllinghome appliancesusinghandgesturesandwouldpresent an opportunityfora sectionof the agingpopulationanddisabledpeople toleadamore independentlife.I.INTRODUCTION HISpaper describesthe designandimplementationof an accelerator-basedhandgestureclassificationsystemwhichcanbe usedforhumancomputer interaction(HCI) applications.A home control interface isdesignedsothatthe user can control home appliancesbymovingthroughmenus.Thisapplicationistargetedtowardsthe agedand disabledpeople whohave problemsusingremote control.The mainapproachesforanalyzingand classifyinghandgesturesforHCIinclude glove-basedtechniquesandvisionbasedtechniques. The glove-basedtechniquesuse sensorstomeasure the positionsof the fingersandthe positionof the handin real-time [1-4].The NintendoPowerGlove,launchedin1989, wasthe firstperipheral that createdhumanhand gesturesonthe televisionorcomputerscreen.Itusesbendsensorstodetect movementof fingersaswell asmagnetic/inertiatrackingdevicestotrackthe pitch,yaw,roll and accelerationof the whole glove.The CyberGlove IIfromImmersionisamore sophisticatedsystem whichhas multiplesensorssuchasbendsensors,abductionsensorsandpalm-arcsensorsandcan be usedto obtainaccurate three-dimensional representationsof the hand.Recently,itwasusedto describe ambiguoussetsof phrasesconsistingof three tofive handgestures[1].However,gloves tendto be This workwassupportedinpart by AustralianResearchCouncilunderDiscoveryGrant DP0666942. H. T. NguyeniswithFacultyof Engineering,Universityof Technology,Sydney, Broadway,NSW2007, Australia(phone:+612-9514-2451; fax:+61 2 9514 2868; e-mail: Hung.Nguyen@uts.edu.au).S.WaniswithFacultyof Engineering,Universityof TechnologySydney, Broadway,NSW2007, Australia(e-mail:silas.wan@student.uts.edu.au).the hand.The vision-based techniquescanbe either3Dor 2D approaches.As3D handmodelsare quite complex,the classificationof gesturesfrom3Dmodelsiscomputationallyintensivemakingreal-time implementationdifficult.Onthe otherhand,the 2D approach isrestrictedtothe lesscomplex problemof classifyingwell-definedstaticgestures[5-8].Recentexistingsystemsusinginertial devicesincludethe NintendoWii.Itusesthe ADXL330accelerometerfromAnalogDevices.The nunchukusesthe LIS3L02AL accelerometerfromSTMicroelectronics.The Wii remote isawireless device thatcommunicateswiththe NintendoWii viaBluetooth.Toobtainabsolutepositionfor games,an infraredsensorisused(Wii InfraredSensorBar).Infraredsensors,unlike accelerometers, provide goodlowfrequencyinformationbutnothighfrequencyinformation.Thusthe twosensors can be fusedusingoptimal filteringtoobtainaccurate positionandmovementinformation.Inthis paper,we describe the developmentof bothhardware andsoftware fora wirelesshandgesture recognition system.SectionIIprovidesanoverview of the handgesture recognitionmodule design and the relevantsoftware forthe system.SectionIIIpresentsthe developmentandresultsof an embeddedneuralnetworkimplementation.SectionIV providesaconclusion forthisstudy.II. METHODS A.WirelessHandGesture Module The SensorNode BlockasshowninFig.1 isthe heart of thisproject.Itconsistsof a JennicJN5139 wirelesstransceivermodule,anAnalogDevicesADXL330