J
Jennifer Healey
Researcher at Adobe Systems
Publications - 128
Citations - 8542
Jennifer Healey is an academic researcher from Adobe Systems. The author has contributed to research in topics: Wearable computer & Affective computing. The author has an hindex of 32, co-authored 125 publications receiving 7819 citations. Previous affiliations of Jennifer Healey include Hewlett-Packard & Harvard University.
Papers
More filters
Journal ArticleDOI
Toward machine emotional intelligence: analysis of affective physiological state
TL;DR: It is found that the technique of seeding a Fisher Projection with the results of sequential floating forward search improves the performance of the Fisher Projections and provides the highest recognition rates reported to date for classification of affect from physiology: 81 percent recognition accuracy on eight classes of emotion, including neutral.
Journal ArticleDOI
Detecting stress during real-world driving tasks using physiological sensors
TL;DR: The results show that for most drivers studied, skin conductivity and heart rate metrics are most closely correlated with driver stress level, indicating that physiological signals can provide a metric of driver stress in future cars capable of physiological monitoring.
Journal ArticleDOI
Augmented reality through wearable computing
Thad Starner,Steve Mann,Bradley J. Rhodes,Jeffrey Steven Levine,Jennifer Healey,Dana Kirsch,Rosalind W. Picard,Alex Pentland +7 more
TL;DR: A text-based augmented reality, the Remembrance Agent, is presented to illustrate this approach, and a long-term goal of this project is to model the user's actions, anticipate his or her needs, and perform a seamless interaction between the virtual and physical environments.
Proceedings ArticleDOI
A long-term evaluation of sensing modalities for activity recognition
TL;DR: A number of issues important for designing activity detection systems that may not have been as evident in prior work when data was collected under more controlled conditions are characterized.
Patent
Methods and systems for authoring of mixed-initiative multi-modal interactions and related browsing mechanisms
TL;DR: In this paper, a conversational browsing architecture is provided for use with authoring techniques and information browsing mechanisms associated therewith, which employ programming in association with mixed-initiative multi-modal interactions and natural language understanding for use in dialog systems.