Missing RRI Interpolation Algorithm based on Locally Weighted Partial Least Squares for Precise Heart Rate Variability Analysis

Figure 1. An example of an ECG trace with artifacts (colored band). An R wave cannot be detected due to artifacts.

Figure 2. Missing RRI data and its effect on HRV features: (a) RRI, (b) RMSSD, (c) NN50, and (d) HF. The HRV features greatly fluctuate when the R detection error occurs.

Figure 3. Example of missing RRI with α=0.5%: some RRIs were intentionally eliminated randomly.

Figure 4. HRV features extracted from the missing RRI: (a) NN50, (b) RMSSD, (c) HF, and (d) LF/HF. There were large errors in HRV features due to frequent missing RRI

Figure 5. RMSE of RRI interpolated by MEAN, ED, PLS, and LWPLS when α=0.3% (left), 0.5% (center), and 1% (right) when a simulation was repeated 30 times using all of the eighteen pieces of validation data. The proposed LWPLS-RI achieved the best interpolation performance.

Figure 6. RMSE of HRV features derived from RRIs interpolated by MEAN, ED, PLS, and LWPLS when α=0.3%. These eight HRV features were explained in the Appendix A. RMSEs of the four methods were calculated through a simulation repeated 30 times using all of the eighteen pieces. The proposed LWPLS-RI achieved the best HRV analysis performance.

Figure 7. RMSE of HRV features derived from RRIs interpolated by MEAN, ED, PLS, and LWPLS when α=0.5%. These eight HRV features were explained in the Appendix A. RMSEs of the four methods were calculated through a simulation repeated 30 times using all of the eighteen pieces. The proposed LWPLS-RI achieved the best HRV analysis performance.

Figure 8. RMSE of HRV features derived from RRIs interpolated by MEAN, ED, PLS, and LWPLS when α=1.0%. These eight HRV features were explained in the Appendix A. RMSEs of the four methods were calculated through a simulation repeated 30 times using all of the eighteen pieces. The proposed LWPLS-RI achieved the best HRV analysis performance.

Figure 9. RMSE of RRI interpolation in each subject by LWPLS when α=0.5%. Although RMSEs of almost all subjects except Subject 6 were less than twenty, that of Subject 6 was more than forty.