The field of human-robot interaction is moving towards a more holistic approach, considering not only the technical aspects of interaction but also the emotional and social aspects. Researchers are exploring the use of multimodal sensing and machine learning to improve human-robot collaboration, with a focus on safety and trust. The integration of psychophysiological methods, such as measuring brain activity and electrodermal activity, is also being investigated to enhance mutual communication and collaboration between humans and robots. Furthermore, the use of somatic safety, a holistic mind-body approach, is being proposed to learn and enact safety through bodily contact with robots. Notable papers in this area include: The paper on Enhancing Human-Robot Interaction in Healthcare, which explores the use of humanoid robots in health monitoring and caregiving for older adults. The paper on Somatic Safety, which introduces a holistic mind-body approach to safety in human-robot interaction. The paper on Multimodal Sensing and Machine Learning, which compares the performance of CNNs and LSTMs in classifying physiologies for paper vs robot-based instruction.