An online heart rate variability analysis using Fourier and Wavelet Transforms with fuzzy logic successfully inferred human mental stress to enable affect-sensitive human-robot cooperation.
Robots are expected to be pervasive in the society in a not too distant future where they will work extensively as assistants of humans in various activities. With this in view, a novel affect-sensitive architecture for human-robot cooperation is presented in this paper where the robot is expected to recognize human psychological states. As a demonstration, an online heart rate variability analysis to infer the mental stress of a human engaged in a task is presented. This technique involves real-time heart rate monitoring, signal processing using both Fourier Transforrn and Wavelet Transform, and inferring the stress condition based on the level of activation of the sympathetic and parasympathetic nervous systems using fuzzy logic. Results from human subject trials are presented to validate the presented methodology. This stress detection technique is expected to be useful in the future human-robot cooperation activities, where the robot will recognize human stress and respond appropriately.
Rani et al. (Fri,) conducted a other in Mental stress. Online heart rate variability analysis using Fourier/Wavelet Transform and fuzzy logic was evaluated on Stress detection validation. An online heart rate variability analysis using Fourier and Wavelet Transforms with fuzzy logic successfully inferred human mental stress to enable affect-sensitive human-robot cooperation.