Can human decisions be predicted through heart rate changes?

Researchers in the area of neuroscience, psychophysiology and communication technology believe that emotion plays an important role in decision making, learning and memory. Recent years, due to the development of instrument and experimental paradigm, emotion and its' influence on decision making has become clear. This paper utilized Iowa Gambling Task (IGT) and Heart Rate Variability (HRV) analysis, found out subjects having different types of decisions related to their heart rate changes right before they made decisions (p <; 0.001). As a pattern classification problem, promising results were obtained in this study using Partial Regularized Least Squares (PRLS) extended feature extraction techniques, showing that human decisions are predictable through their concurrent physiological state.