Name
Title | ||
|---|---|---|
Cognitive State Estimation for Adaptive Learning Systems using Wearable Physiological Sensors |
Abstract | ||
|---|---|---|
This paper presents a historical overview of intelligent tutoring systems and describes an adaptive instructional architecture based upon current instructional and adaptive design theories. The goal of such an endeavor is to create a training system that can dynamically change training content and presentation based upon an individual's real-time measure of cognitive state changes. An array of physiological sensors is used to estimate the cognitive state of the learner. This estimate then drives the adaptive mitigation strategy, which is used as a feed-back and changes how the learning information is presented. The underlying assumptions are that real-time monitoring of the learners cognitive state and the subsequent adaptation of the system will maintain the learner in an overall state of optimal learning. The main issues concerning this approach are constructing cognitive state estimators from a multimodal array of physiological sensors and assessing initial baseline values, as well as changes in baseline. We discuss these issues in a data processing block wise structure, where the blocks include synchronization of different data streams, feature extraction, and forming a cognitive state metric by classification/clustering of the features. Initial results show our current capabilities of combining several data streams and determining baseline values. Given that this work is in its initial staged the work points to our ongoing research and future directions. |
Year | Venue | Keywords |
|---|---|---|
2008 | BIOSIGNALS 2008: PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ON BIO-INSPIRED SYSTEMS AND SIGNAL PROCESSING, VOL II | intelligent tutoring,psychophysiological metrics,augmented cognition,signal processing,wearable sensors |
Field | DocType | Citations |
Data processing,Data stream mining,Wearable computer,Training system,Computer science,Feature extraction,Artificial intelligence,Cluster analysis,Cognition,Adaptive learning,Machine learning | Conference | 6 |
PageRank | References | Authors |
0.80 | 4 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aniket A. Vartak | 1 | 6 | 1.14 |
| Cali M. Fidopiastis | 2 | 22 | 6.23 |
| Denise M. Nicholson | 3 | 57 | 11.54 |
| Wasfy B. Mikhael | 4 | 76 | 76.27 |
| Dylan Schmorrow | 5 | 181 | 31.31 |