Personal state and emotion monitoring by wearable computing and machine learning

One of the major scientific undertakings over the past few years has been exploring the interaction between humans and machines in mobile environments. Research projects have brought forth various possibilities of interaction between humans and computers. Our daily lives are becoming more and more pervasive: we now have smart devices with high computational power. Until now, there is no smart device which has the capability of determining whether the user's heart beat is normal or not while also taking the emotion states into account. To find out whether the user's heart beat is normal or not; the user's physical activities and emotion states have to be identified. Recognizing human physical activities with a body worn sensor is not a new field in research, a lot of the research has been done in this area. We can identify the user's physical movements using different techniques like body movement suit [12], we do have other research project where researchers identify the users' physical activities using some sensors like [1,2,3,4,5,6]. We can identify the user's emotion states as described in [7,11]. I want to develop a physical activity and emotion state recognition system that should be able to identify the physical activities (Sitting, Standing, Walking, Running, Laying, Climbing stairs, Cycling, Strength training) and the emotion states(Grief, Excited, Tension, Frustration, Stress). 2. PROBLEM STATEMENT