Categorization Framework for Usability Issues of Smartwatches and Pedometers for the Older Adults

In recent years various usability issues related to device characteristics of quantified-self wearables such as smartwatches and pedometers have been identified which appear likely to impact device adoption among the older adults. However, an overall framework has not yet been developed to provide a comprehensive set of usability issues related to smartwatches and pedometers. This study used a two-stage research approach with 33 older participants, applying contextual action theory and usability evaluation methods both to determine perceived usability issues and to formulate a usability categorization framework based on identified issues. Additionally, we prioritized the predominant usability issues of smartwatches and pedometers that warrant immediate attention from technology designers, the research community, and application developers. Results revealed predominant usability issues related to the following device characteristics of smartwatches: user interface (font size, interaction techniques such as notification, button location) and hardware (screen size); and of pedometers: user interface (font size, interaction techniques such as notification, button location, and tap detection) and hardware (screen size).

[1]  Carl Gutwin,et al.  The effects of interaction sequencing on user experience and preference , 2017, Int. J. Hum. Comput. Stud..

[2]  James Irvine,et al.  Privacy Implications of Wearable Health Devices , 2014, SIN.

[3]  S. Weisberg Applied Linear Regression: Weisberg/Applied Linear Regression 3e , 2005 .

[4]  LeeUichin,et al.  Smartwatch Wearing Behavior Analysis , 2017 .

[5]  Wendy A. Rogers,et al.  Activity Monitoring Technologies and Older Adult Users , 2014 .

[6]  Halimah Badioze Zaman,et al.  A wearable device for the elderly: A case study in Malaysia , 2014, Proceedings of the 6th International Conference on Information Technology and Multimedia.

[7]  W. Einhäuser,et al.  Effects of aging on eye movements in the real world , 2015, Front. Hum. Neurosci..

[8]  Qian Han,et al.  Frictio: Passive Kinesthetic Force Feedback for Smart Ring Output , 2017, UIST.

[9]  Vesna Popovic,et al.  Ageing, Technology Anxiety and Intuitive Use of Complex Interfaces , 2013, INTERACT.

[10]  Nagul Cooharojananone,et al.  Study of Sound and Haptic Feedback in Smart Wearable Devices to Improve Driving Performance of Elders , 2015 .

[11]  Fabio Pianesi,et al.  Designing a familiar technology for elderly people , 2008 .

[12]  Brendan O'Flynn,et al.  A Review of Activity Trackers for Senior Citizens: Research Perspectives, Commercial Landscape and the Role of the Insurance Industry , 2017, Sensors.

[13]  Birgit Penzenstadler,et al.  Living with Smartwatches and Pedometers: The Intergenerational Gap in Internal and External Contexts , 2017, GOODTECHS.

[14]  Hang-Bong Kang,et al.  An Analysis of the Effects of Smartphone Push Notifications on Task Performance with regard to Smartphone Overuse Using ERP , 2016, Comput. Intell. Neurosci..

[15]  David Beymer,et al.  An eye tracking study of how font size and type influence online reading , 2008 .

[16]  Cooper S. Levy,et al.  Improved Performance of Zinc Oxide Thin Film Transistor Pressure Sensors and a Demonstration of a Commercial Chip Compatibility with the New Force Sensing Technology , 2018 .

[17]  Uichin Lee,et al.  Smartwatch Wearing Behavior Analysis , 2017, Proc. ACM Interact. Mob. Wearable Ubiquitous Technol..

[18]  Blaine A. Price,et al.  Wearables: has the age of smartwatches finally arrived? , 2015, Commun. ACM.

[19]  Fuchun Sun,et al.  Low-Rank Linear Dynamical Systems for Motor Imagery EEG , 2016, Comput. Intell. Neurosci..

[20]  Spencer W Black Current Practices for Product Usability Testing in Web and Mobile Applications , 2015 .

[21]  Kent Lyons,et al.  Shimmering Smartwatches: Exploring the Smartwatch Design Space , 2015, TEI.

[22]  Mirco Musolesi,et al.  Intelligent Notification Systems: A Survey of the State of the Art and Research Challenges , 2017, ArXiv.

[23]  Jussi P. P. Jokinen Emotional user experience: Traits, events, and states , 2015, Int. J. Hum. Comput. Stud..

[24]  Marti A. Hearst,et al.  The state of the art in automating usability evaluation of user interfaces , 2001, CSUR.

[25]  Hans-Werner Gellersen,et al.  Orbits: Gaze Interaction for Smart Watches using Smooth Pursuit Eye Movements , 2015, UIST.

[26]  Charlie Hargood,et al.  The Effect of Timing and Frequency of Push Notifications on Usage of a Smartphone-Based Stress Management Intervention: An Exploratory Trial , 2017, PloS one.

[27]  N. Charness,et al.  Aging and Information Technology Use , 2009 .

[28]  Richard A. Malinauskas,et al.  Use of the FDA nozzle model to illustrate validation techniques in computational fluid dynamics (CFD) simulations , 2017, PloS one.

[29]  Mustafa Ally,et al.  Application and device characteristics as drivers for smart mobile device adoption and productivity , 2012 .

[30]  Elena Mugellini,et al.  Designing a desirable smart bracelet for older adults , 2013, UbiComp.

[31]  Tone Bratteteig,et al.  Touch-Screens and Elderly users: A Perfect Match? , 2013, ACHI 2013.

[32]  Christopher M. Schlick,et al.  Activity Tracker and Elderly , 2015, 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing.

[33]  Stephen A. Brewster,et al.  Multimodal 'eyes-free' interaction techniques for wearable devices , 2003, CHI '03.

[34]  A M Clayton,et al.  Diary data enhancing rigour: analysis framework and verification tool. , 2000, Journal of advanced nursing.

[35]  Ritch Macefield,et al.  How to specify the participant group size for usability studies: a practitioner's guide , 2009 .

[36]  Andreas Holzinger,et al.  Perceived usefulness among elderly people: Experiences and lessons learned during the evaluation of a wrist device , 2010, 2010 4th International Conference on Pervasive Computing Technologies for Healthcare.

[37]  T. Hassard,et al.  Applied Linear Regression , 2005 .

[38]  William N. Venables,et al.  Modern Applied Statistics with S , 2010 .

[39]  Achim Zeileis,et al.  Diagnostic Checking in Regression Relationships , 2015 .

[40]  Jacob Cohen,et al.  Applied multiple regression/correlation analysis for the behavioral sciences , 1979 .

[41]  David Harris,et al.  Engineering Psychology and Cognitive Ergonomics , 2014, Lecture Notes in Computer Science.

[42]  Goshiro Yamamoto,et al.  User interaction in smart ambient environment targeted for senior citizen , 2010, 2010 3rd International Symposium on Applied Sciences in Biomedical and Communication Technologies (ISABEL 2010).

[43]  Min Jou,et al.  Development of a Sensor Network System for Industrial Technology Education , 2010, WSKS.

[44]  Carolina Fuentes,et al.  Helping Elderly Users Report Pain Levels: A Study of User Experience with Mobile and Wearable Interfaces , 2017, Mob. Inf. Syst..

[45]  Sanford Weisberg,et al.  An R Companion to Applied Regression , 2010 .

[46]  Melanie Swan,et al.  Connected Car: Quantified Self becomes Quantified Car , 2015, J. Sens. Actuator Networks.

[47]  Manfred Tscheligi,et al.  Hands free - care free: elderly people taking advantage of speech-only interaction , 2014, NordiCHI.

[48]  L. Piwek,et al.  The Rise of Consumer Health Wearables: Promises and Barriers , 2016, PLoS medicine.

[49]  Jan Stage,et al.  Instant data analysis: conducting usability evaluations in a day , 2004, NordiCHI '04.

[50]  Ching-Ju Chiu,et al.  Understanding Older Adult's Technology Adoption and Withdrawal for Elderly Care and Education: Mixed Method Analysis from National Survey , 2017, Journal of medical Internet research.

[51]  Pam J. Mayhew,et al.  Task Design: Its Impact on Usability Testing , 2008, 2008 Third International Conference on Internet and Web Applications and Services.

[52]  R. Chester The Psychology of Reading , 1974 .

[53]  W. Revelle psych: Procedures for Personality and Psychological Research , 2017 .

[54]  Brian D. Jones,et al.  Older Adults’ Use of and Attitudes toward Activity Monitoring Technologies , 2013, Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Human Factors and Ergonomics Society. Annual Meeting.

[55]  Keiji Shimada,et al.  The Assessment of Driver's Arousal States from the Classification of Eye-Blink Patterns , 2009, HCI.

[56]  Noritaka Osawa,et al.  Effect of Button Size and Location When Pointing with Index Finger on Smartwatch , 2015, HCI.

[57]  James Tung,et al.  User Acceptance of Wrist-Worn Activity Trackers Among Community-Dwelling Older Adults: Mixed Method Study , 2017, JMIR mHealth and uHealth.

[58]  H Kanis,et al.  Usage centred research for everyday product design. , 1998, Applied ergonomics.