Emotions and Activity Recognition System Using Wearable Device Sensors

Abstract

Nowadays machines have become extremely smart, there are a lot of existing services that seemed to be unexpectable and futuristic decades or even a few years ago. However, artificial intelligence is still far from human intelligence, machines do not have feelings, consciousness, and intuition. How can we help machines to learn about human feelings and understand their needs better? People take their devices wherever they go, what can devices tell us about their owners? Personal preferences and needs are dependent on emotional and situational contexts. Therefore, emotional and activity aware gadgets would be more intuitive and provide more appropriate information to users. Contemporary wearable devices involve wide-ranging sensors. In this paper, I am going to present emotion and activity recognition approaches. The experimental recognition system elaborated during this research, enriched with sensor data collection and machine learning algorithms. It is targeted to guess how users are doing and what they are feeling. Such recognition systems can find applications in different areas such as music recommendations, personal safety or healthcare domains.