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CESG Seminar: “Knowledge-driven representations of physiological signals: Developing measurable indices of non-observable behavior”

October 27 @ 4:10 pm - 5:10 pm

| Free

Dr. Theodora Chaspari, Assistant Professor, Computer Science & Engineering, Texas A & M University

Abstract: 

Recent converging advances in sensing and computing, including wearable technologies, allow the unobtrusive long-term tracking of individuals yielding rich multimodal signal measurements from real-life. In this thesis, we will present the development of data-scientific and context-rich bio-behavioral approaches for analyzing, quantifying, and interpreting these bio-behavioral signals. We propose a novel knowledge-driven signal representation framework able to efficiently handle the large volume of acquired data and the noisy signal measurements. Our approach involves the use of sparse approximation techniques and the design of signal-specific dictionaries learned through Bayesian methods, outperforming previously proposed models in terms of signal reconstruction and information retrieval criteria. We further focus on translating the derived signal representations into novel intuitive quantitative measures analyzed with probabilistic and statistical models in relation to external factors of observable behavior. This work has found applications in Autism intervention for detecting beneficial regulation mechanisms during child-therapist interactions, as well as in the family studies domain for identifying instances of emotional escalation and interpersonal conflict. These are discussed in relation to designing human-assistive personalized bio-feedback systems able to promote healthy routines, increase emotional wellness and awareness, and empower clinical assessment and intervention.

Biography:

Dr. Theodora Chaspari is an Assistant Professor at the Computer Science & Engineering Department in Texas A&M University. She has received her diploma (2010) in Electrical and Computer Engineering from the National Technical University of Athens, Greece and a Master of Science (2012) and Ph.D. (2017) in Electrical Engineering from the University of Southern California. Between 2010 and 2017, she had been working as a Research Assistant at the Signal Analysis and Interpretation Laboratory at USC. She has also been a Lab Associate Intern at Disney Research (summer 2015). Dr Chaspari’s research interests lie in the areas of biomedical signal processing, human-computer interaction, behavioral signal processing, data science, and machine learning. She is a recipient of the USC Annenberg Graduate Fellowship, USC Women in Science and Engineering Merit Fellowship, and the IEEE Signal Processing Society Travel Grant.

Details

Date:
October 27, 2017
Time:
4:10 pm - 5:10 pm
Cost:
Free

Venue

WEB, Room 236-C
Wisenbaker Engineering Building
Website:
http://ecencesg.wpengine.com