Application of LSTM to Prediction of Biological Information by Thermographic Images

Abstract

In this study, we tried to understand the relationship between the thermographic images and the biological information obtained from various sensors during the exercise, and to predict the biological information from the thermographic image. The exercise adopted in this study is step exercise. Step exercise is an exercise using a stepstool like climbing and descending stairs that is performed in daily life. Specifically , the step exercises with a constant rhythm were performed, and thermographic images and biological information during this exercise were acquired as data set. The relationship between the thermographic image and biometric information was learned by LSTM using the acquired data set. After that, the heart rate, body surface temperature and the core body temperature were predicted using the learned model, and the prediction accuracy was verified.