Context-Based Decision Making Method for Physiological Signal Analysis in a Pervasive Sensing Environment

With the advent of light-weight, high-performance sensing and processing technology, a pervasive physiological sensing device has been actively studied. However, a pervasive sensing device is easily affected by the external factors and environmental changes such as noise, temperature or weather. In addition, it is hard to deal with the internal factors of a user and personal differences based on physiological characteristics while measuring physiological signal with a pervasive sensing device. To address these issues, we propose a context-based decision making method considering pervasive sensing environments in which it concerns users’ age, gender and sensing environments for detecting normal physiological condition of a user. From the research conducted, we found that the context-based physiological signal analysis for multiple users’ regular data showed reliable results and reduced errors.