Dr. Yamagami presented her work on “Optimizing human-machine interfaces for health and accessibility” at the IEEE-BSN Conference in Chicago. Mikayla Deehring was also present at the conference. Great job!
Our lab’s work on inclusive EMG gesture recognition for individuals with motor disabilities was features on the Meta Quest Blog. The work was funded by a Meta gift in 2022 (Framework for Diverse EMG Gesture Recognition) which was renewed in 2023 for an extension project (Closing the Loop on Personalized EMG Gesture Recognition).
Graduate student Mikayla Deehring gave a poster presentation on “Predicting Adherence to At-Home Rehabilitation Using Biosignals”. Great job Mikayla!
“Personalized upper-body gestures
that enable input from various body parts, according to the abilities
of each user, could be useful for ensuring that gesture systems are
accessible. However, we do not know what types of gestures
(or gesture sets) people with upper-body motor impairments would
want to use, or whether wearable sensors can diferentiate between
an individual’s chosen gestures.”
Dr. Yamagami presented her postdoctoral work, “How do people with limited movement personalize upper-body gestures? Considerations for the design of personalized and accessible gesture interfaces” at ASSETS 2023 [ DOI ] (the 25th International ACM SIGACCESS Conference on Computers and Accessibility) in New York City.
Goal: To understand what types of gestures people with upper-body motor impairments would want to use, or whether wearable sensors can differentiate between an individual’s chosen gestures.
Method: We characterize the personalized gesture sets designed by 25 participants with upper-body motor impairments and develop design recommendations for upper-body personalized gesture interfaces.
Result:
We found that the personalized gesture sets that participants designed were highly ability-specifc. Even within a specifc type
of disability, there were signifcant diferences in what muscles participants used to perform upper-body gestures, with some predominantly using shoulder and upper-arm muscles, and others solely using their finger muscles.
Implications: Personalized upper-body gesture interfaces that take advantage of each person’s abilities are critical for enabling accessible upper-body gestures for people with
upper-body motor impairments
She also presented her TACCESS (ACM Transactions on Accessible Computing Journal) 2022 and 2023 papers, titled:
Kai was selected to join the Bioelectronics NSF Research Traineeship program, which focuses on training PhD students to collaborate across different disciplines. Kai will be collaborating with other students to design new brain/body-machine interfaces to augment human capabilities for people with and without disabilities.
Lauren was selected for the Dean’s Prize bonus award from Rice ECE and GPS. This award will help Lauren transition to her graduate studies and support her research on developing data-driven models to improve health and accessibility. She will be starting as a PhD student at Rice University in Fall 2023. Congratulations Lauren!
We are excited to continue developing personalized human-machine interfaces that adapt to the abilities of individual users and support their health and accessibility goals.