| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10323006 | Expert Systems with Applications | 2011 | 8 Pages |
Abstract
⺠In this study we show heart rate variability which can be used as a passive means to quantify drowsiness. Frequency domain components of HRV is used for early detection of fatigue. ⺠We also designed a neural network based artificial intelligent algorithm which detects whether the given HRV signal is in alert of fatigue state. ⺠The frequency domain components of HRV were also used to distinguish between parasympathetic (HF) and sympathetic (LF) activities using LF/HF ratio. Statistical analysis was also performed to identify the difference between LF/HF ratio during alert and fatigue states.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
M. Patel, S.K.L. Lal, D. Kavanagh, P. Rossiter,