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28 results on '"Afergan, Daniel"'

2. Using fNIRS for Real-Time Cognitive Workload Assessment

Author

Hincks, Samuel W., Afergan, Daniel, Jacob, Robert J. K., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Schmorrow, Dylan D., editor, and Fidopiastis, Cali M., editor

Published
2016
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5. Automated SAF Adaptation Tool (ASAT)

Author

Stripling, Roy, Coyne, Joseph T., Cole, Anna, Afergan, Daniel, Barnes, Raymond L., Rossi, Kelly A., Reeves, Leah M., Schmorrow, Dylan D., Carbonell, Jaime G., editor, Siekmann, J\'org, editor, Schmorrow, Dylan D., editor, and Reeves, Leah M., editor

Published
2007
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7. Automated SAF Adaptation Tool (ASAT)

Author

Stripling, Roy, primary, Coyne, Joseph T., additional, Cole, Anna, additional, Afergan, Daniel, additional, Barnes, Raymond L., additional, Rossi, Kelly A., additional, Reeves, Leah M., additional, and Schmorrow, Dylan D., additional

Published
2007
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9. Rico

Author

Deka, Biplab, primary, Huang, Zifeng, additional, Franzen, Chad, additional, Hibschman, Joshua, additional, Afergan, Daniel, additional, Li, Yang, additional, Nichols, Jeffrey, additional, and Kumar, Ranjitha, additional

Published
2017
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10. BRAAHMS: A Novel Adaptive Musical Interface Based on Users' Cognitive State

Author

Yuksel, Beste Filiz, Afergan, Daniel, Peck, Evan, Griffin, Garth, Harrison, Lane, Chen, Nick, Chang, Remco, and Jacob, Robert

Subjects
InformationSystems_INFORMATIONINTERFACESANDPRESENTATION(e.g.,HCI)
Abstract

We present a novel brain-computer interface (BCI) integrated with a musical instrument that adapts implicitly (with no extra effort from user) to users' changing cognitive state during musical improvisation. Most previous musical BCI systems use either a mapping of brainwaves to create audio signals or use explicit brain signals to control some aspect of the music. Such systems do not take advantage of higher level semantically meaningful brain data which could be used in adaptive systems or without detracting from the attention of the user. We present a new type of real-time BCI that assists users in musical improvisation by adapting to users' measured cognitive workload implicitly. Our system advances the state of the art in this area in three ways: 1) We demonstrate that cognitive workload can be classified in real-time while users play the piano using functional near-infrared spectroscopy. 2) We build a real-time, implicit system using this brain signal that musically adapts to what users are playing. 3) We demonstrate that users prefer this novel musical instrument over other conditions and report that they feel more creative.

Published
2015
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11. DriftBoard

Author

Shibata, Tomoki, primary, Afergan, Daniel, additional, Kong, Danielle, additional, Yuksel, Beste F., additional, MacKenzie, I. Scott, additional, and Jacob, Robert J.K., additional

Published
2016
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13. Learn Piano with BACh

Author

Yuksel, Beste F., primary, Oleson, Kurt B., additional, Harrison, Lane, additional, Peck, Evan M., additional, Afergan, Daniel, additional, Chang, Remco, additional, and Jacob, Robert JK, additional

Published
2016
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18. Brain-based target expansion

Author

Afergan, Daniel, primary, Shibata, Tomoki, additional, Hincks, Samuel W., additional, Peck, Evan M., additional, Yuksel, Beste F., additional, Chang, Remco, additional, and Jacob, Robert J.K., additional

Published
2014
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19. Dynamic difficulty using brain metrics of workload

Author

Afergan, Daniel, primary, Peck, Evan M., additional, Solovey, Erin T., additional, Jenkins, Andrew, additional, Hincks, Samuel W., additional, Brown, Eli T., additional, Chang, Remco, additional, and Jacob, Robert J.K., additional

Published
2014
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23. Company and Below Command and Control Information Exchange Study

Author

NAVAL RESEARCH LAB WASHINGTON DC, Coyne, Joseph T., Stripling, Roy, Pfluger, Kent C., La Budde, Zina, Afergan, Daniel, NAVAL RESEARCH LAB WASHINGTON DC, Coyne, Joseph T., Stripling, Roy, Pfluger, Kent C., La Budde, Zina, and Afergan, Daniel

Abstract

This report presents the results of a recently conducted task analysis on the communications needs for the Marine Corps Distributed Operations (DO) concept of infantry operations and recommendations based on currently available technologies for outfitting future DO small units. The results of this task analysis should be of use not only to DO but also to other rapidly paced collective/team-oriented operations that would benefit from distributed command and control decision structures. The intent of DO is to take advantage of advanced, distributed information technologies and systems in order to enable these teams to function more autonomously than they have in the past. Communication systems typically employed by the Marine Corps infantry do not offer practical support for this mode of operation. A summary of the advantages and disadvantages of the sensory "channels" available for communicating timely information is provided. In addition, a description of the desired traits for an effective communications package suitable for modes of team operation such as DO is offered.

Published
2007

26. Designing Implicit Interfaces for Physiological Computing: Guidelines and Lessons Learned Using fNIRS.

Author

SOLOVEY, ERIN TREACY, AFERGAN, DANIEL, PECK, EVAN M., HINCKS, SAMUEL W., and JACOB, ROBERT J. K.

Subjects
BODY sensor networks, DECISION making, BRAIN-computer interfaces, NEAR infrared reflectance spectroscopy, DATA analysis
Abstract

A growing body of recent work has shown the feasibility of brain and body sensors as input to interactive systems. However, the interaction techniques and design decisions for their effective use are not well defined. We present a conceptual framework for considering implicit input from the brain, along with design principles and patterns we have developed from our work. We also describe a series of controlled, offline studies that lay the foundation for our work with functional near-infrared spectroscopy (fNIRS) neuroimaging, as well as our real-time platform that serves as a testbed for exploring brain-based adaptive interaction techniques. Finally, we present case studies illustrating the principles and patterns for effective use of brain data in human-computer interaction. We focus on signals coming from the brain, but these principles apply broadly to other sensor data and in domains such as aviation, education, medicine, driving, and anything involving multitasking or varying cognitive workload. [ABSTRACT FROM AUTHOR]

Published
2015
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28. Automated SAF Adaptation Tool (ASAT).

Author

Carbonell, Jaime G., Siekmann, Jörg, Stripling, Roy, Coyne, Joseph T., Cole, Anna, Afergan, Daniel, Barnes, Raymond L., Rossi, Kelly A., Reeves, Leah M., and Schmorrow, Dylan D.

Abstract

The purpose of this paper is to describe a new, user-friendly tool that will enable researchers and instructors to setup and run virtual environment scenarios that adapt to the VE user's real-time performance and cognitive status. This tool, the Automated SAF Adaptation Tool (ASAT), will work with existing performance and cognitive state assessment software, and with existing semi-automated forces (SAF) behavior engines. ASAT will collect processed performance and cognitive state data from the assessment software and trigger SAF behavior setting manipulations that were pre-selected by the SAF operator. A key feature of ASAT is the ability to setup and execute these real-time manipulations without the need to alter code in either the assessment software or the SAF engines. [ABSTRACT FROM AUTHOR]

Published
2007
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