McDuff Daniel, Gontarek Sarah, Picard Rosalind
Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:2957-60. doi: 10.1109/EMBC.2014.6944243.
Remote detection of cognitive load has many powerful applications, such as measuring stress in the workplace. Cognitive tasks have an impact on breathing and heart rate variability (HRV). We show that changes in physiological parameters during cognitive stress can be captured remotely (at a distance of 3m) using a digital camera. A study (n=10) was conducted with participants at rest and under cognitive stress. A novel five band digital camera was used to capture videos of the face of the participant. Significantly higher normalized low frequency HRV components and breathing rates were measured in the stress condition when compared to the rest condition. Heart rates were not significantly different between the two conditions. We built a person-independent classifier to predict cognitive stress based on the remotely detected physiological parameters (heart rate, breathing rate and heart rate variability). The accuracy of the model was 85% (35% greater than chance).
认知负荷的远程检测有许多强大的应用，比如测量工作场所的压力。认知任务会对呼吸和心率变异性（HRV）产生影响。我们表明，在认知压力期间生理参数的变化可以使用数码相机进行远程（3米距离）捕捉。对10名参与者进行了一项研究，让他们处于休息状态和认知压力状态。使用一台新型五波段数码相机拍摄参与者面部的视频。与休息状态相比，在压力状态下测量到的归一化低频HRV分量和呼吸频率显著更高。两种状态下的心率没有显著差异。我们构建了一个独立于个体的分类器，基于远程检测到的生理参数（心率、呼吸频率和心率变异性）来预测认知压力。该模型的准确率为85%（比随机概率高35%）。
