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Human–robot collaboration has emerged as a prominent research topic in recent years. To enhance collaboration and ensure safety between humans and robots, researchers employ a variety of methods. One such method is physiological computing, which aims to estimate a human’s psycho-physiological state by measuring various physiological signals such as galvanic skin response (GSR), electrocardiograph (ECG), heart rate variability (HRV), and electroencephalogram (EEG). This information is then used to provide feedback to the robot. In this paper, we present the latest state-of-the-art methods in physiological computing for human–robot collaboration. Our goal is to provide a comprehensive guide for new researchers to understand the commonly used physiological signals, data collection methods, and data labeling techniques. Additionally, we have categorized and tabulated relevant research to further aid in understanding this area of study. |
