Name
Abstract | ||
|---|---|---|
In this work, we evaluate the potential of using wearable non-contact (infrared) thermal sensors through a user study (N=12) to measure mental workload. Our results indicate the possibility of mental workload estimation through the temperature changes detected using the prototype as participants perform two task variants with increasing difficulty levels. While the sensor accuracy and the design of the prototype can be further improved, the prototype showed the potential of building AR-based systems with cognitive aid technology for ubiquitous task assistance from the changes in mental workload demands. As such, we demonstrate our next steps by integrating our prototype into an existing AR headset (i.e. Microsoft HoloLens).
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3290607.3313010 | CHI Extended Abstracts |
Keywords | Field | DocType |
affective computing, cognitive load, thermal sensor | Headset,Workload,Wearable computer,Computer science,Human–computer interaction,Affective computing,Cognitive load,Cognition,Thermal sensors,Multimedia | Conference |
ISBN | Citations | PageRank |
978-1-4503-5971-9 | 4 | 0.45 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qiushi Zhou | 1 | 13 | 3.23 |
| Joshua Newn | 2 | 67 | 11.06 |
| Namrata Srivastava | 3 | 8 | 1.51 |
| Tilman Dingler | 4 | 281 | 37.00 |
| Jorge Gonçalves | 5 | 162 | 12.48 |
| Eduardo Velloso | 6 | 400 | 32.81 |