Abstract
In recent days, many wearable biological data measuring devices have been developed. Despite many advantages, these devices have a few shortcomings such as tissue allergies, motion artifact, and signal noise problem. User identification for the remote monitoring center is another issue. Most of these problems are caused by the sensor contact measurement method. Due to these problems, many studies have been conducted to find ways that simplify the measurement process and cause less discomfort to the users. Many existing studies measured heart rate and respiratory rate by extracting photo plethysmography (PPG) signals from the user’s face with cameras and proper lighting. In this study, the face recognition experiment, we conducted face recognition in various situations. The recognition rate of this system exhibited 96.0% accuracy when trying to recognize the front, and exhibited 86.0% accuracy from the sides of the face. The average heart rate estimation accuracy was 99.1%, compared to the gold standard method.
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Acknowledgement
This work is supported by the Foundation Assist Project of Future Advanced User Convenience Service” through the Ministry of Trade, Industry and Energy (MOTIE) (R0004840, 2020) and Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A1B04031182).
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Kim, Ci., Lee, Jh. (2021). A Development of Enhanced Contactless Bio Signal Estimation Algorithm and System for COVID19 Prevention. In: Singh, M., Kang, DK., Lee, JH., Tiwary, U.S., Singh, D., Chung, WY. (eds) Intelligent Human Computer Interaction. IHCI 2020. Lecture Notes in Computer Science(), vol 12615. Springer, Cham. https://doi.org/10.1007/978-3-030-68449-5_16
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DOI: https://doi.org/10.1007/978-3-030-68449-5_16
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