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Elderly Text-Entry Performance on Touchscreens
 

Elderly Text-Entry Performance on Touchscreens

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My presentation at ACM ASSETS 2012.

My presentation at ACM ASSETS 2012.

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    Elderly Text-Entry Performance on Touchscreens Elderly Text-Entry Performance on Touchscreens Presentation Transcript

    • Elderly Text-EntryPerformance onTouchscreensHugo Nicolauhman@vimmi.inesc-id.ptJoaquim Jorge
    • Mobile evolution
    • … led us to touchscreens
    • Direct Manipulation
    • Engaging
    • Adaptable[Findlater et al., 2012]
    • Hard to select targets[Jin et al., 2007]
    • Occurs to everyone[Nicolau, 2012]
    • Elderly
    • Hand tremor[Strickland and Bertoni, 2004]
    • Small targets [Jin et al., 2007]
    • Text-Entry is a challenge
    • Transversal task Communication Document Note editing takingTextInput Managing Web contacts browsing
    • Re-visiting adaptability
    • Provide the knowledge
    • User Study
    • Text-Entry Performance
    • Hand tremor
    • ApparatusTablet:20x10 mmMobile:10x10 mm
    • Participants15 participants (4 males)67 to 89 years oldRight-handedNo severe visual impairmentsNo familiarity with touchdevices
    • Two Phases1st - Familiarization2nd - Evaluation
    • FamiliarizationExplanation and exemplificationCopy tasks30 minute practice session
    • Physiological tremor assessmentAction tremor (task-specific)Archimedes Spiral [Bain et al., 1993]Postural tremorAccelerometer data [Selker et al., 2011]
    • Copy Task1 practice sentences / condition5 test sentences / conditionPortuguese languagerepresentative corpusError correction was notavailable
    • Dependent MeasuresSpeed:Words per minuteAccuracy:Minimum String Distance error rateSubstitution error rateInsertion error rateOmission error rate
    • Results
    • Tremor ProfileTask-specific TremorArchimedes Spiral DrawingsPostural TremorHand Oscillation[Oulasvirta et al., 2011]Peak Magnitude[Salarian et al., 2007][Elble and Koller, 1990]
    • Tremor ProfileTask-specific TremorArchimedes Spiral DrawingsPostural TremorHand Oscillation[Oulasvirta et al., 2011]Peak Magnitude[Salarian et al., 2007][Elble and Koller, 1990]
    • Text-Entry Performance
    • Error RateMinimum String Distance (MSD) Error Rate 26% 17% Mobile Tablet
    • Tablet Compensates ErrorsMinimum String Distance (MSD) Error Rate Statistically Significant [Z=-2.417, p<.05] 26% 17% Mobile Tablet
    • Correlation with Hand OscillationMinimum String Distance (MSD) Error RateHand OscillationNon-dominant handY [Pearson r=.751, n=9, p<.05]Z [Pearson r=.613, n=9, p=.079] 26% 17% Mobile Tablet
    • Types of ErrorsError Rate 6% 8% 13% 4% 4% 9% Mobile Tablet Insertions Substitutions Omissions
    • Omissions
    • Omission were the most commonError Rate 6% 8% 13% 4% 4% 9% Mobile Tablet Insertions Substitutions Omissions
    • Omission were the most commonError Rate No Significant Difference [Z=-.722, p>.4] 6% 8% 13% 4% 4% 9% Mobile Tablet Insertions Substitutions Omissions
    • Blank space was recurrently omittedOmission Error Rate in Mobile condition 28% 23% 16% 15% e i v x m p u zSPACE s w o r k n q y c t d f g h j a b l
    • Forgetfulness and coordination arereal issues#13 Usually forgot to transcribe words atmiddle and end of sentences#8 “where was I?”
    • Unintentional touches
    • Insertions
    • Insertion Error Rate 6% 8% 13% 4% 4% 9% Mobile Tablet Insertions Substitutions Omissions
    • Few Insertions with TabletError Rate Statistically Significant [Z=-2.103, p<.05] 6% 8% 13% 4% 4% 9% Mobile Tablet Insertions Substitutions Omissions
    • Bounces and Accidental TouchesError Rate 1.5% 3.3% 2.2% 1.1% Mobile Tablet Bounces Accidental
    • Few Accidental Touches with TabletError Rate Statistically Significant [Z=-2.292, p<.05] 1.5% 3.3% 2.2% 1.1% Mobile Tablet Bounces Accidental
    • Correlations with Hand TremorError RateDominant Hand OscillationX [Spearman rho=.596, n=14, p<.05] Non-Dominant Hand Oscillation Y [Spearman rho=.762, n=9, p<.05] 1.5% 3.3% 2.2% 1.1% Mobile Tablet Bounces Accidental
    • Deal with Insertion ErrorsRequired: r e c e i t a d o (English: prescribed)Transcribed: rreceiittadoo
    • Substitutions
    • Substitution Error Rate 6% 8% 13% 4% 4% 9% Mobile Tablet Insertions Substitutions Omissions
    • Few Substitutions with TabletError Rate Statistically Significant [Z=-2.731, p<.01] 6% 8% 13% 4% 4% 9% Mobile Tablet Insertions Substitutions Omissions
    • Correlation with task-specific tremor Error Rate[Spearman rho=.624, n=15, p<.05][Spearman rho=.541, n=9, p<.05] [Spearman rho=.539, n=15, p<.05] 6% 8% 13% 4% 4% 9% Mobile Tablet Insertions Substitutions Omissions
    • Substitution PatternsMobile Error Rate
    • Right-Bottom Substitution PatternLift Points – Mobile condition
    • Similar and Symmetrical Substitutionsp -> qi -> j , i -> lParticipant #11: m -> w , n -> uCognitive errors?
    • Most Substitutions are due to Poor AimingError Rate 1.1% 6.7% 0.2% 3.5% Mobile Tablet Slip Poor Aiming
    • Most Substitutions are due to Poor AimingError Rate Statistically Significant Statistically Significant [Z=-2.944, p<.01] [Z=-3.107, p<.01] 1.1% 6.7% 0.2% 3.5% Mobile Tablet Slip Poor Aiming
    • Preferences andComments
    • Participants Preference 2 13 Mobile Tablet
    • Participants Comments“I am always hitting neighboring keys”“The hardest thing is trying not to tremblewhile typing”“The main difficulty for me is in knowingwhere the letters are. I am not used to it(the keyboard)”
    • InclusiveKeyboards
    • Implications
    • ImplicationsShift keyboard layout
    • ImplicationsShift keyboard layoutAvoid errors by understanding typingbehaviors
    • ImplicationsShift keyboard layoutAvoid errors by understanding typingbehaviorsDeal with poor aiming rather than finger slips
    • ImplicationsShift keyboard layoutAvoid errors by understanding typingbehaviorsDeal with poor aiming rather than finger slipsUse language-based correctors
    • ImplicationsShift keyboard layoutAvoid errors by understanding typingbehaviorsDeal with poor aiming rather than finger slipsUse language-based correctorsAllow personalization
    • ImplicationsShift keyboard layoutAvoid errors by understanding typingbehaviorsDeal with poor aiming rather than finger slipsUse language-based correctorsAllow personalizationCompensate hand tremor
    • ConclusionElderly Text-Entry PerformanceEmpirical Body of KnowledgeError PatternsDesign Implications
    • Future WorkAnalyze hand tremor dataDevelop touch modelsCompensate input errors Touch + Intended key Accelerometer data
    • The End.Hugo Nicolauhman@vimmi.inesc-id.pthttp://web.ist.utl.pt/hugo.nicolau/