Evaluating the Effects of Interface Disruption Using fNIR Spectroscopy
Abstract
The primary accomplishment that we achieved during this three year effort was the creation and implementation of a novel usability experiment protocol and a set of machine learning methods that enable us to predict, on the fly, the user state of a given individual. Before we began this research, the majority of brain research, and all fNIRS research could not PREDICT user states. Previous research in non-invasive brain measurement could only predict that two (or more) user states differed from one another. We have had great success publishing our work in part because it offers a large leap forward in the state-of-the-art of non-invasive brain measurement in HCI. We used our techniques to test disruptions that were developed from the DnD project, and we reported on these findings throughout the effort. Building on the techniques and findings from our first 2 1/2 years of research, we spent the second half of our final year of funding pursing the measurement of trust and suspicion while users work with computers. We teamed up with a strong group of experts in the trust domain, including interested parties from AFRL at Wright Patterson Air Force Base, where we have visited several times to share, and build on, our research.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 28, 2011
- Accession Number
- ADA563699
Entities
People
- Leanne M. Hirshfield
- Robert J. Jacob
Organizations
- Tufts University