Optimization of heartbeat detection in fiber-optic unobtrusive measurements by using maximum a posteriori probability estimation.

Abstract

This paper deals with an optimized heartbeat detection multimethod by using maximum a posteriori probability (MAP). The approach was derived for unobtrusive fiber-optic measurements of cardiac activity. Multiple independent detection methods were selected and characterized by their delays and variability referring to cardiac electrical excitation (R waves). Validation of the approach was performed in two experiments involving 24 participants: 10 interferometric signals were recorded at rest, 14 with variable heart rate after physical exercise. The proposed MAP heartbeat detection was assessed by a cross validation in 250 iterations. Obtained results show the overall efficiency, which was estimated by a product of the sensitivity, precision, and variability of heartbeat detections, yields 97.04 ± 3.36% for the experiment with physical exercise and 97.07 ± 4.49% at rest. The method's accuracy guarantees that the heartbeat detections differ for 22 ± 5 ms and 22 ± 3 ms from the ECG reference in the two types of experiments, respectively.