Real-time detection of workload changes using heart rate variability

被引:76
作者
Hoover, Adam [1 ]
Singh, Anirud [1 ]
Fishel-Brown, Stephanie [2 ]
Muth, Eric [2 ]
机构
[1] Clemson Univ, Dept Elect & Comp Engn, Clemson, SC 29634 USA
[2] Clemson Univ, Dept Psychol, Clemson, SC 29634 USA
关键词
ECG; Change point detection; Heart rate variability; Workload; State change; CUSUM; RESPIRATORY SINUS ARRHYTHMIA; CHANGE-POINT DETECTION; ADAPTIVE AUTOMATION; PERFORMANCE; INDEX; COMPONENTS; AROUSAL; PILOTS; TONE;
D O I
10.1016/j.bspc.2011.07.004
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
This work presents a novel approach to detecting real-time changes in workload using heart rate variability (HRV). We propose that for a given workload state, the values of HRV vary in a sub-range of a Gaussian distribution. We describe methods to monitor a HRV signal in real-time for change points based upon sub-Gaussian fitting. We tested our method on subjects sitting at a computer performing a low workload surveillance task and a high workload video game task. The proposed algorithm showed superior performance compared to the classic CUSUM method for detecting task changes. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:333 / 341
页数:9
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