July 8, 2016

CLTC BioSENSE Grantees Publish Papers on Therapy Robots and “Passthoughts”

CLTC Research, News
Professor John Chuang
Professor John Chuang

Researchers working with BioSENSE—a CLTC-sponsored research group focused on “socio-physiological computing”—have published papers on diverse topics in recent weeks.

Addressing the emerging question of how data-collecting, in-home robots could affect humans’ privacy, Elaine Sedenberg, John Chuang, and Deirdre Mulligan published “Designing Commercial Therapeutic Robots for Privacy Preserving Systems and Ethical Research Practices within the Home,”  in the International Journal of Social Robotics. In the paper, the researchers present “new privacy paradigms and apply the Fair Information Practices (FIPs) to investigate concerns unique to the placement of therapeutic robots in private home contexts.”

The BioSense team has also published two papers in conjunction with conferences of the Institute of Electrical and Electronics Engineers (IEEE). The paper “Classifying Mental Gestures with In-Ear EEG,” by Nick Merrill, Max Curran, Jong-ka Yang, and John Chuang, investigates how electroencephalogram (EEG) signals collected from the ear could be used for “gestural” control of a brain-computer interface (BCI). “Our results indicate that in-ear BCI applications using mental gestures may be feasible,” they write. “While in-ear EEG offers potential advantages to usability over scalp-based EEG, longer-term, in vivo studies will be necessary to fully realize these benefits.”

A related paper, “Passthoughts Authentication with Low Cost EarEEG,” by Max Curran, Jong-ka Yang, Nick Merrill, and John Chuang, set to be published for IEEE’s upcoming Engineering in Medicine and Biology Society conference, hints at how brain signals could serve the function of passwords in the future. “We conclude that earEEG shows potential as a uniquely convenient authentication method as it is integrable into devices like earbud headphones already commonly worn in the ear, and the mental gestures generating the signal are invisible to would-be eavesdroppers.”

Stay tuned to the CLTC website for updates on this and other research from our grantees.

Image Credit: Robot, Math TheRivo via Freeimages.com