The Undergraduate Research Symposium, or the "Meeting of the Minds," (MoM) is a university-wide celebration of undergraduate research. More than 700 Carnegie Mellon University students, including several from the Human-Computer Interaction Institute, presented their research on Wednesday, May 8, in the Cohon University Center.
Conducting research is a valuable experience for CMU undergraduates and advisors alike.
Jason Wu, first year human-computer interaction Ph.D. student, received a 2019 Graduate Research Fellowship from the National Science Foundation.
We've become accustomed to our smartwatches and smartphones sensing what our bodies are doing, be it walking, driving or sleeping. But what about our hands? It turns out that smartwatches, with a few tweaks, can detect a surprising number of things your hands are doing.
The research paper “Sensing Posture-Aware Pen+Touch Interaction on Tablets” received an Honorable Mention award at CHI 2019.
Lead author Yang Zhang, fourth year HCI Ph.D. student, led the research project while interning at Microsoft Research in Redmond, Washington, last summer.
What is this idea of posture-aware tablet interaction, as mentioned in the paper title, and why is it novel?
Smart devices can seem dumb if they don’t understand where they are or what people around them are doing. Carnegie Mellon University researchers say this environmental awareness can be enhanced by complementary methods for analyzing sound and vibrations.
Smart Walls React to Human Touch, Sense Activity in Room
Walls are what they are — big, dull dividers. With a few applications of conductive paint and some electronics, however, walls can become smart infrastructure that sense human touch, and detect things like gestures and when appliances are used.
Researchers at Carnegie Mellon University and Disney Research found that they could transform dumb walls into smart walls at relatively low cost — about $20 per square meter —using simple tools and techniques, such as a paint roller.
Our research in sensors and machine learning techniques seeks to improve HCI experience by developing objective and near real-time methods for recognizing end-users’ behavioral patterns and in-situ contexts. For this, we utilize a range of sensor devices (e.g., eye trackers, ECG-enabled armband, GSR fingertip sensors, wireless EEG headset and HR monitor) to identify patterns in perceptual and cognitive activities between individuals at different levels of task-complexity.
Pediluma is a shoe accessory designed to encourage opportunistic physical activity. It features a light that brightens the more the wearer walks and slowly dims when the wearer remains stationary. This interaction was purposely simple so as to remain lightweight, both visually and cognitively. Even simple, personal pedometers have been shown to promote walking. Pediluma takes this a step further, attempting to engage people around the wearer to elicit social effects.
