Quantitative measures of autonomic activations during software development

This paper focuses on the analysis of autonomic nervous system responses of programmers during tasks of code comprehension and code writing. The signals analyzed are the heart rate variability and the respiratory signal, acquired using unobtrusive sensors connected to a polygraph. A bivariate time-variant autoregressive model was used to compute frequency domain features and their variations in time. A significant increase in heart rate and respiratory rate and a reduction in the total power of the heart rate variability were identified during code writing compared to other protocol tasks. This research is part of the second study of the BASE (Biofeedback Augmented Software Engineering) project.