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Syracuse Student Mindlabs Overview

an overview of the mindlabs
by

Frank Biocca

on 16 November 2015

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Transcript of Syracuse Student Mindlabs Overview

Research Approach
M.I.N.D. Labs
Network

University of Arizona
Michigan State University
Temple University
Syracuse
University
University of Porto
Technical University of Eindhoven
Technical University of Valencia
Sungkyunkwan University
University of
Cologne
Moscow University
Helsinki School of Economics
M.I.N.D. Labs
Michigan State University
Syracuse
University
Sungkyunkwan (Samsung) University
M.I.N.D. Lab Partners
M.I.N.D. Lab Facilities
Augmented Reality
3D Immersive Projection Display
Projective Multitouch System
3D Design Toolsets
Simdialog
Psychological Measurements
EEG Brain Real Time System
Automatic Facial Emotion Reading
Eye Movement
Behavioral Measurements
EMG, ECG, EMG
M.I.N.D. Labs
Network
University of Arizona
Michigan State University
Temple University
Syracuse
University
University of Porto
Technical University of Eindhoven
Technical University of Valencia
Sungkyunkwan University
University of
Cologne
Moscow University
Helsinki School of Economics
syracuse university
Michigan State University
Sungkyunkwan University
Frank Biocca
Sung Yeun"Su" Kim
Gyoung Kim
Sungkyunkwan University
Michigan State University
corey bohil
Charles Owen
Steve Chung
Seoul, Korea
Hyoungtaek Lim
Hwayeon Kong
Sanghun
M.I.N.D. Labs
RESEARCH APPROACH
Thank you!
Research Facilities @ Newhouse
M.I.N.D. Lab
RESEARCH APPROACH
A MIND TOUR
Dr. Frank Biocca
Newhouse Chaired Professor
World Class University Professor
Recent projects
New Media Research Environment
Research & Teaching in the M.I.N.D. Lab
3D game
effects
Social
Media
Augmented reality
Research on Media At
Different Phases of Diffusion
ACADEMIC CAREERS
INDUSTRY CAREERS
Microsoft
Hewlett-Packard
AT&T
CBS
Daimler-Chrysler
Accenture
General Motors
Siemens
US Government
Others…
Stanford
Harvard
CalTech
Univ. of Southern California
Vancouver Film School
Vanderbilt
Univ. of Michigan
Univ. of Texas
Others…
Students @ M.I.N.D. Lab
Research Approach
Diffuse Theory
Diffuse Technology (Social Intervention or policy)
Tech-Eval Experiments
Iterative Design
Theories of Cognition
Research Approach
Cognitive Artifact
Silicon Valley
At a place near you
Newhouse Chair

Research Approach
Iterative Design
Theories of Communication & Cognition
Research Approach
Cognitive Artifact (medium, interface, app, exp)
Iterative Design / Production
Theories of Cognition, Communication, Interaction
Research Approach
Team Interdisciplinary Research
New Media Research
Communication
Dr. Biocca
Michigan State
Dr. Burgoon
University of Arizona
Dr. Saari
Helsinki Institute of Technology
Dr. Lombard
Temple University
Dr. David
Ohio State
Computer Science
Dr. Owen
Michigan State
Dr. Stockman
Michigan State
Dr. Gouveia
Fernando Pessoa
Cognitive Science
Dr. Bohil
Michigan State
Dr. Bente
University of Cologne
Dr. IJsselsteijn
Eindhoven Technical University
Dr. Voiskinsky
Moscow University
United States
Univ. North Carolina
U.Cal. Berkeley
Stanford (visiting researcher)
Michigan State University
University of Wisconsin Madison
M.I.N.D. Partners & Labs
Augmenting communication in virtual environments.
Overview
Some background
Montreal – my fave
Silicon Valley
Introducing portable-mobile computing
Some background
Recent Projects
Special Lecture about Convergence Research : the Lessons of M.I.N.D. Lab
Teleportal System
Measure and display
social context of mobile
human interaction
PASION Project
Hands Free Zoom
Potential Threat
(Left at -125 deg)
Potential Threat
(Right, +70 deg)
Forward View
360SA View
Tele-Collaboration Table (Social media)
Group project (Korea, Spain, US)

3D Interactive Gaming for Health Communication

360o Awareness System (DARPA $million)
1. MIND & Media
Research on New Media Design and Effects
Experimental Project based
Professionals
Lab Staff
Student teams
Classes
Hands Free Zoom
Potential Threat
(Left at -125 deg)
Potential Threat
(Right, +70 deg)
Forward View
360SA View
Topizen
(News Social Media Interface)

Tele-Collaboration Table (Social media)
Group project (Korea, Spain, US)

3D Interactive Gaming for Health Communication
Human-computer interaction
Interdisciplinary Seminar
Newhouse
Computer Science
Information Studies
Project based
Professionals
Lab Staff
Student teams
Human Computer Interaction
Sampling of Some Recent/Ongoing Efforts
On average, across all subjects, we can predict between:

High trust (HL) and ‘not sure trust’ (LL) with 70% accuracy
High distrust (LH) and ‘not sure trust’ (LL) with 71% accuracy
High trust (HL) and high distrust (LH) with 60% accuracy

High distrust (LH) and control with 74% accuracy
High trust (HL) and control with 61% accuracy
‘not sure trust’ (LL) and control with 64% accuracy

**Interestingly, some subjects would have a high accuracy in one
comparison and a very low accuracy for another pairing. Need for
active learning in algorithms!
Initial fNIRS Classifier Results
Great news as Cz and Fz don’t take up much ‘real estate’!
Machine Learning Results
Overview of Brain and M.I.N.D. Lab Research
High Trust
High Distrust
‘Not Sure’ Trust
Ebay Seller Profile: Trustworthiness Prediction Experiment (n = 15)
Understanding Situational Awareness in the Brain
For each 1 second window, we concatenated the Cz and Fz data together for input into a machine learning classifier.

We implemented a Naïve Bayes Classifier in Matlab
EEG Machine Learning Classifier
Higher cognitive load to deal with the ‘not sure’ (LL) profile
‘Not sure’ activation (LL) > high trust (HL)
‘Not sure ‘activation (LL) > high distrust (LH)
Statistical Differences in Brain Activation Across Subjects
Human Identification with
Non-invasive Brain Measurement
Violation of Expectations on the Web
Fear
Benchmark (High) Trust
Fear
Frustration
Browsing the Web Experiment (n = 11)
Measuring and Predicting Frustration during HCI
(Related to ‘stereotyping’)
Do we see an error potential when:

Links or buttons don’t work?
Unexpected animation comes on the screen?
Selecting an icon has an unexpected effect?
Anything else occurs that we didn’t expect?
The Error Potential
Measuring and Predicting ‘Violations in Expectations’ During HCI Experiment (n = 9)
The activation in these regions is in line with the
neuroscience literature on
Stress, fear, frustration, cognitive load, etc…
Activation in Frontopolar region, DLPFC, orbitofrontal,
and Broca’s area
Activation in Frontopolar region and DLPFC
Fear
Frustration
fNIRS Results
Where We’re Headed From Here….
time stamped
data is sent to a
machine learning classifier
Classifier
user works with
IT system while
wearing sensor(s)
Verbal working memory
High
Low
Visual Search
High
Low
Response Inhibition
High
Low
Cognitive Benchmark Tasks
User Interface Tasks
Predicting Different Types of Workload of Different User Interface Designs
Video Gaming and
Adaptive Interfaces
Educational Applications
Military Applications
Usability Testing and Focus Groups
Adaptive Interfaces for Disabled
Many Applications…
AFOSR DURIP Funded
Suite of Non-Invasive Sensors
usability
software
Electroencephalograph
eyetracking
galvanic skin
response
functional near-infrared
spectroscopy
Embodied Interaction

Campus touring
Overseas
Helsinki School of Economics
Technical University of Einhoven
Sungkyunkwan University
UNUSED
Konkuk University
Work in the MIND Lab
World Class University Professor,
Sungkyunkwan (Samsung) University
Returned:
Virtual Reality, NASA
Full transcript