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Analyzing user-generated youtube videos to understand touchscreen use by people with motor impairments

Published: 27 April 2013 Publication History

Abstract

Most work on the usability of touchscreen interaction for people with motor impairments has focused on lab studies with relatively few participants and small cross-sections of the population. To develop a richer characterization of use, we turned to a previously untapped source of data: YouTube videos. We collected and analyzed 187 non-commercial videos uploaded to YouTube that depicted a person with a physical disability interacting with a mainstream mobile touchscreen device. We coded the videos along a range of dimensions to characterize the interaction, the challenges encountered, and the adaptations being adopted in daily use. To complement the video data, we also invited the video uploaders to complete a survey on their ongoing use of touchscreen technology. Our findings show that, while many people with motor impairments find these devices empowering, accessibility issues still exist. In addition to providing implications for more accessible touchscreen design, we reflect on the application of user-generated content to study user interface design.

References

[1]
Abascal, J. & Civit, A. (2009). Mobile communication for people with disabilities and older people: new opportunities for autonomous life. Proc. 6th ERCIM Workshop, 255--268.
[2]
Belatar, M. & Poirier, F. (2008). Text entry for mobile devices and users with severe motor impairments: handiglyph, a primitive shapes based onscreen keyboard. Proc. ASSETS 2008, 209--216.
[3]
Biswas, P. & Langdon, P. (2012). Developing multimodal adaptation algorithm for mobility impaired users by evaluating their hand strength. Int J Hum-Comput Int, 28(9), 576--596.
[4]
Blythe, M. & Cairns, P. (2009). Critical methods and user generated content: the iPhone on YouTube. Proc. CHI 2009, 1467--1476.
[5]
Cunningham, S. J. & Nichols, D. M. (2008). How people find videos. Proc. JCDL 2008, 201--210.
[6]
Duff, S. N., Irwin, C. B., Skye, J. L., Sesto, M. E., Wiegmann, D. A. (2010). The effect of disability and approach on touch screen performance during a number entry task. Proc. HFES Annual Meeting 2010, 566--570.
[7]
Findlater, L., Jansen, A., Shinohara, K., Dixon, M., Kamb, P., Rakita, J., Wobbrock, J. O. (2010). Enhanced area cursors: Reducing fine pointing demands for people with motor impairments. Proc. UIST 2010, 153--162.
[8]
Froehlich, J., Wobbrock, J. O., Kane, S. K. (2007). Barrier pointing: using physical edges to assist target acquisition on mobile device touch screens. Proc. ASSETS 2007, 19--26.
[9]
Gajos, K. Z., Wobbrock, J. O., Weld, D. S. (2008). Improving the performance of motor-impaired users with automatically-generated, ability-based interfaces. Proc. CHI 2008, 1257--1266.
[10]
Guerreiro, T., Nicolau, H., Jorge, J., Gonçalves, D. (2010). Towards accessible touch interfaces. Proc. ASSETS 2010, 19--26.
[11]
Hourcade, J. P., Bederson, B. B., Druin, A., Guimbretiere, F. (2004). Differences in pointing task performance between preschool children and adults using mice. ACM TOCHI, 11(4), 357--386.
[12]
Hourcade, J. P., Perry, K. B. Sharma, A. (2008). PointAssist: helping four year olds point with ease. Proc. IDC 2008, 202--209.
[13]
Hurst, A., Hudson, S. E., Mankoff, J., Trewin, S. (2008). Automatically detecting pointing performance. Proc. IUI 2008, 11--19.
[14]
Hwang, F., Keates, S., Langdon, P., Clarkson, P. J. (2003). Multiple haptic targets for motion-impaired computer users. Proc. CHI 2003, 41--48.
[15]
Hwang, F., Keates, S., Langdon, P., Clarkson, P. J. (2004). Mouse movements of motion-impaired users: A submovement analysis. Proc. ASSETS 2004, 102--109.
[16]
Irwin, C. B. & Sesto, M. E. (2012). Performance and touch characteristics of disabled and non-disabled participants during a reciprocal tapping task using touch screen technology. Applied Ergonomics, 43(6), 1038--1043.
[17]
Jang, S. H. (2011). YouTube as an innovative resource for social science research. Proc. Australian Association for Research in Education Conference 2011, 1--16.
[18]
Kabbash, P. & Buxton, W. (1995). The "Prince" technique: Fitts' law and selection using area cursors. Proc. CHI 1995, 273--279.
[19]
Kane, S. K., Bigham, J. P., Wobbrock, J. O. (2008). Slide rule: Making mobile touch screens accessible to blind people using multi-touch interaction techniques. Proc. ASSETS 2008, 73--80.
[20]
Kane, S. K., Jayant, C., Wobbrock, J. O., Ladner, R. E. (2009). Freedom to roam: a study of mobile device adoption and accessibility for people with visual and motor disabilities. Proc. ASSETS 2009, 115--122.
[21]
Keates, S. & Trewin, S. (2005). Effect of age and Parkinson's disease on cursor positioning using a mouse. Proc. ASSETS 2005, 68--75.
[22]
Keelan, J., Pavri-Garcia, V., Tomlinson, G., Wilson, K. (2007). YouTube as a source of information on immunization: a Content analysis. JAMA-J Am Med Assoc, 298(21), 2482--2484.
[23]
Lange, P. G. (2007). Publicly private and privately public: social networking on YouTube. J Comput-Mediat Comm, 13(1), 361--380.
[24]
Manduchi, R. & Coughlan, J. (2008). Portable and mobile systems in assistive technology. Proc. ICCHP 2008, 1078--1080.
[25]
McGookin, D., Brewster, S., Jiang, WeiWei. (2008). Investigating touchscreen accessibility for people with visual impairments. Proc. NordiCHI 2008, 298--307.
[26]
Paay, J., Kjeldskov, J., Skov, M., O'Hara, K. (2012). Cooking together: a digital ethnography. Extended Abstracts of CHI 2012, 1883--1888.
[27]
Paek, H.-J., Kim, K., Hove, T. (2010). Content analysis of antismoking videos on YouTube: message sensation value, message appeals, and their relationships with viewer responses. Health Education Research, 25(6), 1085--1099.
[28]
Power, M. R. & Power, D. (2004). Everyone here speaks TXT: deaf people using SMS in Australia and the rest of the world. J. Deaf Stud. Deaf Educ., 9(3), 333--343.
[29]
Trewin, S., Keates, S., Moffatt, K. (2006). Developing steady clicks: a method of cursor assistance for people with motor impairments. Proc. ASSETS 2006, 26--33.
[30]
Trewin, S. & Pain, H. (1999). Keyboard and mouse errors due to motor disabilities. IJHCS, 50(2), 109--144.
[31]
Wacharamanotham, C., Hurtmanns, J., Mertens, A., Kronenbuerger, M., Schlick, C., Borchers, J. (2011). Evaluating swabbing: a touchscreen input method for elderly users with tremor. Proc. CHI 2011, 623--626.
[32]
Wobbrock, J. O., Fogarty, J., Liu, S., Kimuro, S., Harada, S. (2009). The angle mouse: target-agnostic dynamic gain adjustment based on angular deviation. Proc. CHI 2009, 1401--1410.
[33]
Wobbrock, J. O., Myers, B. A. and Kembel, J. A. (2003). EdgeWrite: a stylus-based text entry method designed for high accuracy and stability of motion. Proc. UIST 2003, 61--70.
[34]
Worden, A., Walker, N., Bharat, K., Hudson, S. (1997). Making computers easier for older adults to use: area cursors and sticky icons. Proc. CHI 1997, 266--271.

Cited By

View all
  • (2024)Please Understand My Disability: An Analysis of YouTubers' Discourse on Disability ChallengesProceedings of the ACM on Human-Computer Interaction10.1145/36869468:CSCW2(1-25)Online publication date: 8-Nov-2024
  • (2024)Understanding the Interaction between Delivery Robots and Other Road and Sidewalk Users: A Study of User-generated Online VideosACM Transactions on Human-Robot Interaction10.1145/367761513:4(1-32)Online publication date: 23-Oct-2024
  • (2024)Danger, Nuisance, Disregard: Analyzing User-Generated Videos for Augmented Reality Gameplay on Hand-held DevicesProceedings of the ACM on Human-Computer Interaction10.1145/36770638:CHI PLAY(1-33)Online publication date: 15-Oct-2024
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  1. Analyzing user-generated youtube videos to understand touchscreen use by people with motor impairments

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      Ganapathy Mani

      People with disabilities face considerable challenges when using touchscreens. The authors of this paper investigate how well touchscreen devices work out of the box, evaluating the extent to which they affect interaction and how disabled users adapt to improve usability. They assembled a YouTube videos dataset for the investigation and analysis based on a search in two categories: medical conditions (60 keywords, such as brain injury, Parkinson's, and so on) and technology terms (eight keywords, such as touchscreen, tablet, iPad, and so on). For their analysis, they separated the resulting dataset of 187 noncommercial videos into four groups based on video characteristics, device usage in the video, user characteristics, and type of user interaction. The results show that even though these touchscreen devices empower people with physical disabilities in some ways, accessibility challenges are far more significant. This paper sheds light on some of the important characteristics of touchscreen use by motor-impaired users that could have profound effects on future human-computer interaction research. First, the authors categorize interaction styles: 91 percent of the videos show direct interactions using fingers, hands, or feet, while only eight percent show indirect interaction using an intermediary tool such as a mouthstick. The analysis reveals that people with motor impediments are not able to perform certain tasks required for touch-based apps. When they use hands, fists, knuckles, feet, and nose, they generally touch a broad surface area and may hold the touch for a long enough time that the app disregards the action. These findings can indeed become the basis for the development of new adaptation techniques for physically disabled users. Second, the paper presents the characteristics of indirect interaction methods using tools such as headsticks, mouthsticks, styluses, arm and leg slings, and user posture. Although these tools serve as efficient intermediaries for interaction, people with severe physical disabilities still face several challenges in managing them. The survey conducted by the authors among the users who uploaded the study videos shows either extremely positive or extremely negative sentiment toward touchscreens. The positive sentiments are mostly driven by the affordability of touchscreen devices such as the iPad and the ability of some children with speech impediments to communicate using apps. Negative sentiments are driven by the difficulty of accessing and using some devices and apps. The survey also reveals problems with nonscreen hardware parts such as buttons, which are either too hard to push or too sensitive to inadvertent contact. Finally, the authors present an extensive discussion of the improvements needed to adapt touchscreen devices for use by people with minor to severe physical disabilities. Suggestions include developing generic interaction models for the applications and tools targeted at people with various disabilities. The authors also demonstrate the importance and efficiency of the dataset of YouTube videos and uploader surveys. They contend that their approach is effective for the analysis and characterization of human-computer interaction, especially when it comes to touchscreens and the accessibility issues of the physically disabled. The paper is well written, with extensive analysis. The authors have made an important and valuable contribution to the field of human-computer interaction. Online Computing Reviews Service

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      cover image ACM Conferences
      CHI '13: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
      April 2013
      3550 pages
      ISBN:9781450318990
      DOI:10.1145/2470654
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 27 April 2013

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      Author Tags

      1. assistive technology
      2. ipad
      3. iphone
      4. motor impairments
      5. physical disabilities
      6. touchscreen
      7. youtube

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      Cited By

      View all
      • (2024)Please Understand My Disability: An Analysis of YouTubers' Discourse on Disability ChallengesProceedings of the ACM on Human-Computer Interaction10.1145/36869468:CSCW2(1-25)Online publication date: 8-Nov-2024
      • (2024)Understanding the Interaction between Delivery Robots and Other Road and Sidewalk Users: A Study of User-generated Online VideosACM Transactions on Human-Robot Interaction10.1145/367761513:4(1-32)Online publication date: 23-Oct-2024
      • (2024)Danger, Nuisance, Disregard: Analyzing User-Generated Videos for Augmented Reality Gameplay on Hand-held DevicesProceedings of the ACM on Human-Computer Interaction10.1145/36770638:CHI PLAY(1-33)Online publication date: 15-Oct-2024
      • (2024)DREEM: Moving from Empathy to Enculturation in Disability Related Human-Centered DesignProceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility10.1145/3663548.3675642(1-17)Online publication date: 27-Oct-2024
      • (2024)Vision-Based Hand Gesture Customization from a Single DemonstrationProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676378(1-14)Online publication date: 13-Oct-2024
      • (2024)Toward Building Design Empathy for People with Disabilities Using Social Media Data: A New Approach for Novice DesignersProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3660687(3145-3160)Online publication date: 1-Jul-2024
      • (2024)"Voices Help Correlate Signs and Words": Analyzing Deaf and Hard-of-Hearing (DHH) TikTokers’ Content, Practices, and PitfallsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642413(1-18)Online publication date: 11-May-2024
      • (2024)Co-Designing Accessible Computer and Smartphone Input Using Physical ComputingIEEE Pervasive Computing10.1109/MPRV.2024.341889923:3(39-48)Online publication date: 1-Jul-2024
      • (2024)Enhancing Mobile Interaction for Individuals With Tremors via Optical See-Through Augmented RealityIEEE Access10.1109/ACCESS.2024.344988012(123946-123955)Online publication date: 2024
      • (2023)Designing voice interfaces to support mindfulness-based pain managementDIGITAL HEALTH10.1177/205520762312044189Online publication date: 19-Oct-2023
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