Our team is excited to share with you our journey. The project is a collaboration among five departments.
The Human Bio-Behavioral Signals (HUBBS) lab at the department of Computer Science & Engineering focuses on computational models of human behavior from multimodal signals, including audiovisual and physiological indices. In this project, the HUBBS/CSCE team is working on processing and analyzing physiological signals from performance tasks under different noise conditions. The team is further designing machine learning models to automatically estimate one's stress, mood, perceived workload, and performance from the collected signals.
We focus on smart building and data-driven human-building interaction for examining the effect of built environments to occupants’ environmental comfort and work performance. In this project, the auralization-based acoustic simulation is conducted in a virtual environment, which explores the real-time dynamic interaction between noise and human stress/performance in a virtual scene.
Our conjecture is that reconfiguring the geometrical shapes of the kerf panel will allow adaptive tuning of the room acoustics, which will be explored in this project. In order to fulfill it, our focus is to design intelligent and reconfigurable kerf panels that can vary the acoustics in the room to achieve personalized space. We are specifically studying the modal response of adaptive and compliant kerf structures. After understanding the modal response, we study acoustic wave propagation through these kerf structures using numerical wave based models.
Team A is comprised of the Laboratory in the Department of Computer Science and the Individual and Team Performance and Complex Skill Acquisition Laboratory in the Department of Psychological and Brain Sciences. Currently, they have been utilizing the Individual and Team Performance Lab’s unique human research capabilities and the Lab’s technical study design abilities in the development and implementation of a comprehensive study design and protocol. Currently, the team gathers psychological and physiological data that will be used to create bio-behavioral models of the effects of noise on stress and task performance.