A Mood Prediction System for Preventing Diseases Using Biological Information and Weather Information

Preventive medicine has attracted much attention due to increase of medical expenses in Japan. As a preventive measurement against diseases, this paper presents a system for predicting three types of moods namely, good, normal, and bad using biological and weather information. Specifically, we focus on analyzing factors for the predictions. Evaluation experiments demonstrate that the proposed system predicts the tomorrow's mood with 73% accuracy by learning biological information, weather information, and moods in the past with multiple classifiers. Moreover, we found that body fat, maximal pressure, and amount of insolation are important factors for the prediction. The evaluation experiments indicate that the proposed system is useful for the prevention of bipolar disorder and lifestyle diseases.