Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In this article,  discuss the strong relationship beten affect and cognition and the importance of emotions in Multimodal Human Computer Interaction (HCI) and User-Modeling.  introduce the overall paradigm for our multi-modal system that aims at recognizing its users' emotions and at responding to them accordingly depending upon the current context or application.  then describe the design of the emotion elicitation experiment  conducted by collecting, via arable computers, physiological signals from the autonomic nervous system (galvanic skin response, heart rate, temperature) and mapping them to certain emotions (Sadness, Anger, Fear, Surprise, Frustration, and Amusement).  show the results of three different supervised learning algorithms that categorize these collected signals in terms of emotions, and generalize their learning to recognize emotions from new collections of signals.  finally discuss possible broader impact and possible applications of emotion recognition for multimodal intelligent systems.
['Christine L. Lisetti', 'Fatma Nasoz']
I am writing a research paper on a idea Categorizing Autonomic Nervous System (ANS) Emotional Signals using Bio-Sensors for HRI within the MAUI Paradigm
[{"from": "human", "value": "I am writing a research paper on a idea Categorizing Autonomic Nervous System (ANS) Emotional Signals using Bio-Sensors for HRI within the MAUI Paradigm"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In this article,  discuss the strong relationship beten affect and cognition and the importance of emotions in Multimodal Human Computer Interaction (HCI) and User-Modeling.  introduce the overall paradigm for our multi-modal system that aims at recognizing its users' emotions and at responding to them accordingly depending upon the current context or application.  then describe the design of the emotion elicitation experiment  conducted by collecting, via arable computers, physiological signals from the autonomic nervous system (galvanic skin response, heart rate, temperature) and mapping them to certain emotions (Sadness, Anger, Fear, Surprise, Frustration, and Amusement).  show the results of three different supervised learning algorithms that categorize these collected signals in terms of emotions, and generalize their learning to recognize emotions from new collections of signals.  finally discuss possible broader impact and possible applications of emotion recognition for multimodal intelligent systems."}]