Accession Number:

ADA582457

Title:

Sensei: A Multi-Modal Framework for Assessing Stress Resiliency

Descriptive Note:

Rept. for 1-28 Feb 2013

Corporate Author:

SRI INTERNATIONAL ARLINGTON VA

Personal Author(s):

• Divakaran, Ajay
• Lubin, Jeffrey
• Ferraro, Joe

Report Date:

2013-02-01

Pagination or Media Count:

5.0

Abstract:

Progress during this reporting period was in two primary areas. First, we completed all necessary modifications to our laboratory environment to allow accurate, automatic data collection in Experiment 2. This included 1 Enabling full time stamping of all data streams IR and visible video sensors, plus physiological signals from the Equivital belt. 2 Developing automatic, trial synced audio recording. 3 Better illumination to allow pupillometry from the high resolution video camera. 4 Time-stamping of subject responses to the peripheral detection task. 5 Python-based automatic startstop of all data streams. 6 Automatic generation and population of directories for each data stream for each subject. In addition to these lab accomplishments, we also fine-tuned the timing of the StroopPDT presentations to achieve maximal engagement and hence maximal stress response as the trials come more and more quickly towards the end of the session. In data analysis, we perfected a technique, described briefly in the last report, for accurately tracking facial feature points in the IR video stream. As shown in Figure 1, this tracking works quite well, even over large facial rotations.

Descriptors:

• *RESILIENCE
• *STRESSES
• AUTOMATIC
• DATA PROCESSING
• ILLUMINATION
• REAL TIME

Subject Categories:

• Mechanics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE