TapAssist: Improving Touchscreen Tablet Usability for User with Motor Skill Impairments

Advisor: Mike Y. Chen

Video | GitHub | Slide (Chinese)

Abstract: People with motor impairments such as cerebral palsy have difficulties interacting with touchscreens devices. We evaluated the ability of individuals with motor skill impairments performing touchscreen gestures and proposed an alternative solution to improving the usability. In this work, we analyzed their behavior of individuals performing touch screen tapping gesture. We proposed an adaptive gesture recognizer (AGR) which can tailor individual’s motor capabilities and improved the tapping recognition rate without interfering other gestures such as swipe and press. A within-subjects study with sixteen individuals with Cerebral Palsy is conducted.

Our results showed that the error rate of tapping with AGR is significantly decreased from 80% to 30% compared to no assistance.

My contribution:

  • Identified and characterized motor skill impairments of Cerebral Palsy patients in using touchscreen tablet.

  • Conducted ideation sessions with graduate students to brainstorm for solving tapping problem.

  • Analyzed input data with MATLAB and OpenGL for better understanding of individual’s motor capabilities. The dots are the starting points and end points of each "tap gesture". The dotted line indicates the target point for the user, and the solid line depicts the user's movement while performing the "tap gesture" for tapping the target.

Normal User Cerebral Palsy patients

Overlying the patient's attempts for tapping 18 targets.

Overlying the patient's starting point for tapping 18 targets

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