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Obesity sensing and monitoring
Obesity sensing and monitoring
[Food intake behavior monitoring]
Recently many products or services are being introduced to monitor calories through analyzing user's food intake behavior. However, it provided low usability that users should write dietary information manually and some cannot be used in a normal daily life. In this work, we proposed automatic food intake detection method based on accelerometer and gyroscope sensors of smart watches. This system detected wrist motion of eating activity and recognized food intake time, count, term in real time.
Related papers
J. Cho and A.Choi, "Asian-style Food Intake Pattern Estimation Based on Convolutional Neural Network," ICCE 2018, Jan 12-14, 2018.
Blood pressure estimation
Blood pressure estimation
In this project, we are collaborating with HS Lab, department of biomedical engineering at Chonnam National University. We are developing blood pressure estimation method based on deep learning technology.
Affective interaction with VR/AR characters
Affective interaction with VR/AR characters
How does the facial expression of virtual character affect to the users? We monitored users' physiological feedback specially related to emotion and observed users' decision making patterns. Finally we found that emotion expressions in agents affect people emotionally or strategically.
Related papers
A. Choi, C. de Melo, P. Khooshabeh, W. Woo, J. Gratch (2015), "Physiological evidence for a dual process model of the social effects of emotion in computers", International Journal of Human-Computer Studies, 74, 41-53, 2015.
A. Choi, C. Demelo, W. Woo, and J. Gratch (2012), “Affective engagement to emotional facial expressions of embodied social agents in a decision-making game”, Computer Animation and Virtual Worlds, Volume 23, Issue 3-4, pages 331–342, 2012.
Research Grants
Research Grants
AI-based mental status analyses based on physiological signals for self-mental health monitoring, funded by National Research Foundation of Korea (NRF), Jun, 2019 - May, 2022. (50M KRW/year)
Development of mobile health Monitoring system by deep learning-based big data analysis of biometric Signals measured by nanomaterial-based wearable multifunctional sensors, funded by Gachon Univ., May 2019 ~ May, 2020. (10M KRW/year)
Development of the cuffless blood pressure measurement technology for continuous blood pressure monitoring, funded by Bio and Medical Technology Development Program of the NRF funded by the Korean government, MSIP, Nov., 2016～ July, 2021.
Autonomic eating habit monitoring and calorie intake estimation technology, funded by National Research Foundation of Korea (NRF), Nov., 2016 ~ Oct., 2019. (50M KRW/year)
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