User-Centered and Analytic-Based Approaches to Generate Usable Gestures for Individuals With Quadriplegia

Area of Science:

• Human-Computer Interaction
• Rehabilitation Engineering
• Assistive Technology

Background:

• Standard hand gesture interfaces pose challenges for individuals with upper limb motor impairments, such as those with spinal cord injury (SCI).
• Existing gesture recognition systems often lack adaptability for users with specific motor deficits.
• Developing inclusive interfaces is crucial for enhancing digital accessibility.

Purpose of the Study:

• To adapt existing hand gesture-based interfaces for users with upper limb motor impairments, particularly those with quadriplegia due to cervical SCI.
• To develop and validate methodologies for creating more accessible gesture recognition systems.
• To improve the usability of human-computer interaction for individuals with motor disabilities.

Main Methods:

• Developed two complementary approaches: a user-centered and an analytic method.
• Projected existing gestural patterns to match those typical of users with cervical SCI.
• Validated the methodology through user-based experimental paradigms, collecting both subjective and quantitative data.

Main Results:

• Subjects with upper extremity motor impairments showed a significant preference for the alternative constrained gestures.
• The proposed approach resulted in a significantly lower Borg scale rating, indicating reduced perceived exertion.
• The methodology demonstrated feasibility in creating more usable gesture interfaces for SCI users.

Conclusions:

• The developed methodology effectively adapts hand gesture interfaces for users with motor impairments, including SCI.
• Alternative constrained gestures generated by the proposed approach enhance usability and user preference.
• This work contributes to the field of assistive technology by providing a framework for inclusive interface design.