Effect of Observation Time and Estimation Interval on rPPG-based Blood Pressure Estimation

Key Result

Longer observation times and appropriately spaced estimation intervals reduce mean absolute error and increase correlation in rPPG-based blood pressure estimation.

Key Points

• Blood pressure estimation becomes more precise as observation time increases, and estimation intervals are optimized—leading to reduced absolute errors.
• The average absolute error decreases when observation periods are sufficiently long and estimation intervals are not overly short, enhancing estimation performance.
• Using a dataset constructed at Leipzig University Hospital, rPPG signals are processed to optimize blood pressure estimates while utilizing recurrent neural networks.
• The findings highlight a significant reduction in performance differences between rPPG and contact-based PPG estimation methods through careful design of observation and estimation intervals.