Table 14.
Typical HRV measures after applying cubic spline interpolation and the proposed algorithms for various gap sizes, compared to the HRV measures in the original signal for Participant 1 (PhysioNet database).
| Signal | Method | RMSSD | SDNN | SDSD | Total Power |
LF | HF | SD1 | SD2 | Mean Error |
|---|---|---|---|---|---|---|---|---|---|---|
| Original | 32.18 | 57.26 | 32.22 | 2296.47 | 1295.86 | 403.44 | 22.78 | 77.71 | ||
| Gap w = 3 | Cubic spline | 32.13 | 57.16 | 32.16 | 2285.85 | 1292.51 | 400.33 | 22.74 | 77.58 | 0.3% |
| Algorithm 2 | 32.04 | 56.81 | 32.07 | 2244.04 | 1276.18 | 386.67 | 22.68 | 77.08 | 1.4% | |
| (StDev.) | (0.04) | (0.04) | (0.04) | (5.45) | (2.93) | (1.58) | (0.03) | (0.07) | ||
| Gap w = 5 | Cubic spline | 31.58 | 56.31 | 31.61 | 2206.60 | 1266.42 | 372.33 | 22.35 | 76.43 | 2.9% |
| Algorithm 2 | 32.46 | 56.96 | 32.49 | 2253.18 | 1276.37 | 390.11 | 22.98 | 77.21 | 1.3% | |
| (StDev.) | (0.17) | (0.17) | (0.17) | (11.04) | (4.62) | (1.92) | (0.12) | (0.21) | ||
| Gap w = 7 | Cubic spline | 31.46 | 56.23 | 31.49 | 2210.85 | 1270.94 | 368.61 | 22.27 | 76.36 | 3.1% |
| Algorithm 2 | 33.15 | 57.28 | 33.18 | 2286.60 | 1299.44 | 400.71 | 23.46 | 77.54 | 1.3% | |
| (StDev.) | (0.49) | (0.33) | (0.49) | (11.51) | (10.68) | (9.53) | (0.35) | (0.42) |