Bust a Move: IC Ph.D. Student Caitlyn Seim Tests Passive Haptic Learning for Dance at Get a Move On Hackathon

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Earlier this month, School of Interactive Computing Ph.D. student Caitlyn Seim participated in the College of Computing’s Get a Move On hackathon, which focused on music, dance, fitness, gaming, and sports.

As a graduate researcher who has studied wearable computing devices that provide haptic, or tactile, stimulation in Professor Thad Starner’s lab, she took the opportunity to apply what she knew to the lower body. Most of what she and Starner have worked on in the past was focused on upper-body learning – teaching piano, Braille, making you faster at typing – but in this case, she wanted to focus on dance.

“While brainstorming for the hackathon, I reached out to Carnegie Hall tap dancer Christopher Erk,” she said. “He was immediately interested and provided us with three elementary tap routines that we could integrate into the wearable.”

Using a technique called passive haptic learning, individuals can learn new skills through tactile cues provided by a wearable device such as a watch or glove. While continuing normal daily tasks, the instructional stimuli repeat in the background and help them learn. In the past, Starner’s lab has been able to produce results in skills like piano playing or learning Morse code.

Seim’s thought leading up to the hackathon was that she could have similar success in affecting muscle memory for dance.

“Every song is a new pattern of key presses,” said Seim, referring to the computerized haptic gloves that helped teach the finger patterns of different piano songs. “Likewise, every dance is a new pattern of steps. This is what inspired me to prototype a wearable to teach dance steps.”

Over the course of two days at the hackathon, Seim worked with David Purcell, a student in Georgia Tech’s online master of science in computer science (OMSCS) program, to create the prototype. It comes in the form of haptic socks, which are cordless, and is synchronized and programmed to teach a routine sent by Erk using tactile taps from embedded motors.

Results thus far are limited to the pilot program tested by Seim and another student. But, Seim said, the paradigm is exactly like the hands. Seim’s team finished in the top five overall and second place in hardware at the hackathon.

Seim is looking at potential dance-related collaborations to continue the project. Interested students should contact Seim via email.


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    David Mitchell
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