New Approach for Sampling Mobile Phone Accelerometer Sensor Data for Daily Mood Assessment
Keywords:
Mobile Phone Sensor, Mood Assessment, Sampling, Clustering, Daily Mood Assessment (DMA)Abstract
With the increasing stress and unhealthy in people’s daily life, mental health problems are becoming a global concern. In particular, mood related mental health problems, such as mood disorders, depressions, and elation, are seriously impacting people’s quality of life. However, due to the complexity and unstableness of personal mood, assessing and analyzing daily mood is both difficult and inconvenient, which is a major challenge in mental health care. In this paper, we propose a novel framework for assessing and analyzing daily mood of persons working in corporate organizations. It uses mobile phone data—particularly mobile phone accelerator sensor data to extract human behavior pattern and assess daily mood. We also present a sampling approach for rapidly and efficiently computing the best sampling rate which minimizes the Sum of Square Error in order to handle the large data.
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