Name
Title | ||
|---|---|---|
A real-time stress classification system based on arousal analysis of the nervous system by an F-state machine. |
Abstract | ||
|---|---|---|
•A new system able to detect six different stress categories in real‐time.•Detected stress stages two different kinds of activations with three different levels are differentiated from 20 to 35 s.•Data collected from 166 subjects.•The input to algorithm is an easily calculable feature, the slope, extracted from the two noninvasive physiological signals.•The performance of this system has been evaluated by means of the F-measure, achieving an average value of 0.965. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.cmpb.2017.06.010 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
Stress,HRV,GSR,Finite-state machine | End user,Computer science,Artificial intelligence,Computation,Arousal,F1 score,Computer vision,Pattern recognition,Heart rate variability,Wearable computer,Speech recognition,Finite-state machine,Skin conductance | Journal |
Volume | ISSN | Citations |
148 | 0169-2607 | 2 |
PageRank | References | Authors |
0.45 | 10 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| R Martinez | 1 | 2 | 0.45 |
| Eloy Irigoyen | 2 | 38 | 14.23 |
| Andoni Arruti | 3 | 47 | 6.61 |
| J I Martin | 4 | 2 | 0.45 |
| Javier Muguerza | 5 | 338 | 28.61 |