A Heartbeat Interval Error Compensation Method Using Multiple Linear Regression for Photoplethysmography Sensors

This paper presents an error compensation method for heartbeat intervals measured by a photoplethysmography (PPG) sensor. The objective of this work is to improve the accuracy of heart rate variability analysis (HRVA) using PPG, because a peak-to-peak interval (PPI) of the PPG has an error when compared with R to R interval (RRI) of electrocardiograph (ECG). This error is caused by several factors such as blood pressure fluctuation, body motion artifact, and body position. The proposed method predicts RRI using multiple regression analysis with time series of PPIs. The predicted RRI using the proposed method can also reduce the error of frequency characteristics, which are used for HRVA. Evaluation results with three subjects show that the proposed method achieved about 30% mean absolute error (MAE) reduction for predicted RRI and 17% mean absolute percentage error (MAPE) of LF/HF index of HRV analysis.