Please note! This essay has been submitted by a student.
Nowadays, emotion detection based on the physiological changes of the body is a major concern. Anger is one of the most destructive emotional states and needs continuous monitoring for a healthy lifestyle. In this study, we developed and implemented a wearable anger-monitoring system, which analyses various physiological changes during the state of anger in humans and notifies the monitoring unit using a global system for mobile communication. This is unique as it detects the human mood swing and realizes it on hardware. This can be develop as a low-cost non-invasive wrist band and can be used all-day and anywhere for detecting anger and other physiological parameters. Doctors or guardian can also see the patient’s health status on website remotely. Mainly, Anger monitoring physician who monitor or control the anger of a person use this wearable product and give it to patient. After that he can monitor it remotely. Not only physician but also guardian or friends who registered on website can see the health data of a person if a person accepts a follow request. All data flow in an encrypted form so no intruders can steal or change the data.
For this project I have created a system using IOT devices and sensors on the arduino platform to monitor anger in humans using various parameters. We have used three different parameters namely Temperature, Pulse and motion sensors to determine if a person is angry or not or any other physiological state. Our main objectives for the project is to integrate all the 3 sensors into a single system and with their combined result get the desired data. As it could be a possibility that a person’s pulse rate and the temperature could be high because of exercise hence all 3 parameters should be taken into account to make sure that the person is angry. All data are store in cloud and then use by any user by requesting an http request for analytical purpose.
The paper  “Emotion recognition from physiological signals using wireless sensors for presence technologies” by Andreas Haag, Silke Goronzy, Peter Schaich, Jason William describe a new approach to enhance presence technologies. First, they discuss the strong relationship between cognitive processes and emotions and how human physiology is uniquely affected when experiencing each emotion. Secondly, they introduce our prototype multimodal affective user interface. In the remainder of the paper we describe the emotion elicitation experiment we designed and conducted and the algorithms they implemented to analyse the physiological signals associated with emotions. These algorithms can then be used to recognise the affective states of users from physiological data collected via non-invasive technologies. The affective intelligent user interfaces we plan to create will adapt to user affect dynamically in the current context, thus providing enhanced social presence. In order to make emotion recognition accurate and reliable, our completed system will take as input both physiological components (facial expressions, vocal intonation, skin temperature, galvanic skin response (GSR), and heart rate) and subjective components (written or spoken language) that are associated with emotions experienced by the user.
The paper  “Wearable anger-monitoring system” by Vivekanand Jha∗, Nupur Prakash, Sweta Sagar Nowadays, emotion detection based Anger is one of the most destructive emotional states and needs continuous monitoring for a healthy lifestyle. In this study, we developed and implemented a wearable anger-monitoring system, which analyses various physiological changes during the state of anger in humans and notifies the monitoring unit using a global system for mobile communication. This is unique as it detects the human mood swing and realizes it on hardware. The developed low-cost noninvasive wrist band can be used all-day and anywhere for detecting anger. Biosensors are commonly used in wearable healthmonitoring systems to measure physiological parameters such as pulse rate, respiration rate, skin conductivity, skin temperature, electrocardiogram, and sweat level. The WAMS is designed to measure three parameters: skin temperature, body motion, and heart rate. The collective information of temperature and heart rate is used to detect high pulse rate and anger level of a person.
The paper  “Remarks on Emotion Recognition from Bio-Potential Signals” by Kazuhiko Takahashi Faculty of Engineering, Doshisha University, Kyoto, Japan. proposes an emotion recognition system from multi-modal bio-potential signals. For emotion recognition, support vector machines (SVM) are applied to design the emotion classifier and its characteristics are investigated. Using gathered data under psychological emotion stimulation experiments, the classifier is trained and tested. In experiments of recognizing five emotion: joy, anger, sadness, fear, and relax, recognition rate of 41.7% is achieved. The experimental result shows that using multi-modal bio-potential signals is feasible and that SVM is well suited for emotion recognition tasks.
The paper  “Wrist ambulatory monitoring system and smart glove for real time emotional, sensorial and physiological analysis.” Improvement of the quality and efficiency of the quality of health in medicine, at home and in hospital becomes more and more important Designed to be user-friendly, smart clothes and gloves fit well for such a citizen use and health monitoring. Analysis of the autonomic nervous system using non-invasive sensors provides information for the emotional, sensorial, cognitive and physiological analysis. MARSIAN (modular autonomous recorder system for the measurement of autonomic nervous system) is a wrist ambulatory monitoring and recording system with a smart glove with sensors for the detection of the activity of the autonomic nervous system. It is composed of a ‘smart tee shirt’, a ‘smart glove’, a wrist device and PC which records data. The smart glove is one of the key point of MARSIAN. Complex movements, complex geometry, sensation make smart glove designing a challenge. MARSIAN has a large field of applications and researches (vigilance, behaviour, sensorial analysis, thermal environment for human, cognition science, sport, etc…) in various fields like neurophysiology, affective computing and health monitoring.