Machine Learning Enabled Non-contact Sensing Platform for Blood Pressure and Glucose Prediction

• Project/Area Number: 23K11341
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 62020:Web informatics and service informatics-related
• Research Institution: Waseda University
• Principal Investigator: 劉 江 早稲田大学, 理工学術院, 准教授 (50546851)
• Co-Investigator(Kenkyū-buntansha): 中田 孝明 千葉大学, 大学院医学研究院, 教授 (20375794) ; 嶋本 薫 早稲田大学, 理工学術院, 教授 (80235639)
• Project Period (FY): 2023-04-01 – 2026-03-31
• Project Status: Granted (Fiscal Year 2023)
• Budget Amount: ¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000); Fiscal Year 2025: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000); Fiscal Year 2024: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000); Fiscal Year 2023: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
• Keywords: Non-contact Method / Blood Glucose / Blood Pressure / Prediction / Machine Learning

Outline of Research at the Start

The measurement of blood pressure and glucose level is very important for both clinical work-up and home heath monitoring. This research designs and develops contactless blood pressure and glucose measurement devices with AI technology to help people to achieve comfortable healthcare services.