Heart rate variability predicts low cognitive capacity choices

Author(s)

Mario Muramatsu Júnior

• Document type: Master's Dissertation
• Press: São Paulo.
• Institution: Universidade de São Paulo (USP). Instituto de Matemática e Estatística (IME/SBI)
• Defense date: 2024-06-18

Examining board members

André Fujita; Katerina Lukasova; João Paulo Papa

• Advisor: André Fujita

Abstract

Decision-making is a fundamental aspect of everyday life. It takes place in a variety of contexts, from choosing what to eat for breakfast to complex decisions such as career choices or business strategies. In this context, a natural question is: could we predict a persons decision? To help answer this question, we hypothesized that the state of the body is fundamental to some classes of decision-making, for example, fast and intuitive reasoning decisions made by System 1 (Kahneman model). To measure the physiological state of the body, we propose using interoception. It is interesting to note that we can measure interoception through heart rate variability. We designed an experiment in which a person watches a trailer and decides whether or not to watch the movie to test our hypothesis. Using a machine learning model, we demonstrated that predicting a person\'s choice is more effective when heart rate variability is combined with emotional measures, compared to using emotions or movie genre preferences alone, achieving an accuracy rate of 73%. These results show that the physiological state of the body is associated with decision-making, which can be predicted based on these parameters with acceptable accuracy. (AU)

• FAPESP's process: 21/05658-0 - Classification of emotions based on heart rate variability
• Grantee: Mario Muramatsu Junior
• Support Opportunities: Scholarships in Brazil - Master