Estimating changes in a cognitive performance using heart rate variability

This paper presents a low-invasive framework for estimating changes in a cognitive performance using heart rate variability (HRV). Although HRV is a common physiological indicator of autonomous nerve activity or central nervous fatigue, there are individual differences in the relationship between HRV and such internal state. The new framework enables an estimation model to be determined using the HRV characteristics of individuals performing tasks through cognitive efforts. They also enable users working in a chair to have their changes in the cognitive performance estimated without interrupting their work or having to use a lot of devices as most previous methods require. Experimental results show the framework can estimate mental fatigue; defined based on cognitive performance, using HRV as the same level as the previous work did using higher-invasive method(using multi-channel electroencephalogram (EEG) sensor or multiple vital sensors). It can also estimate changes in a cognitive performance for most of subjects, and one of our proposed method in the framework realizes more effective and useful estimation than the others. It therefore has the potential to help managerial personnel in making performance change reports for their workers, suggesting reasons for changes in the performance, and urging them to change their working styles using HRV.