Clustering Stress Reactivity based on Heart Rate Variability During Acute Mental Stress Task

Stress reactivity refers to an individual's ability to cope with job stress, influenced by her/ his subjective emotional and physiological reactions in various stressful situations. Despite extensive research on the association of heart rate variability (HRV) and productivity indicators, very few studies have utilized HRV change to group individual stress reactivity. This paper aims at identifying subjects based on their cardiovascular stress reactivity, indicated by HRV parameters, on an acute mental stress task. We performed a k-means clustering analysis using the Nbclust package in R environment to classify 162 healthy subjects according to their heart rate and HRV indexes reactivity between baseline and mental stress tasks into k = 2 and
$k$
=3 number of clusters. We found that k = 3 could differentiate subjects with similar patterns into two groups but with different magnitudes of reactivity (high and low) and one group for those who experienced the opposite pattern. Our study offers the potential use of such a classification in the implementation of workplace health promotion programs and to assign the right jobs or tasks to employees.