Table 2 Performance metrics of meal detection algorithms.
From: Performance of continuous glucose monitoring-based meal detection algorithms in young healthy adults
Algorithm | TP | FP | FN | Sensitivity (%) | FP/day | Δt (min) |
|---|---|---|---|---|---|---|
MDADassau−2of33 | 156 | 43 | 60 | 72.2 [65.7–78.1] | 0.60 [0.43–0.80] | 37.6 [33.7–41.6] |
MDADassau−3of43 | 106 | 9 | 110 | 49.1 [42.2–55.9] | 0.12 [0.06–0.24] | 36.8 [32.9–40.7] |
MDAFaccioli16 | 139 | 100 | 77 | 64.4 [57.6–70.7] | 1.39 [1.13–1.69] | 39.6 [34.5–44.8] |
MDAHarvey15 | 152 | 19 | 64 | 70.4 [63.8–76.4] | 0.26 [0.16–0.41] | 37.3 [34.4–40.2] |
MDAKölle-Ra13 | 167 | 24 | 49 | 77.3 [71.1–82.7] | 0.33 [0.21–0.50] | 41.7 [38.2–45.1] |
MDAKölle-CGM13 | 178 | 28 | 38 | 82.4 [76.7–87.2] | 0.38 [0.26–0.56] | 43.8 [40.4–47.2] |
MDAPopp12 | 179 | 92 | 37 | 82.9 [77.2–87.6] | 1.28 [1.03–1.57] | 60.5 [55.9–65.0] |
MDASamadi18 | 194 | 174 | 22 | 89.8 [85.0–93.5] | 2.42 [2.07–2.80] | 58.5 [53.6–63.5] |
MDATurksoy14 | 166 | 16 | 50 | 76.9 [70.6–82.3] | 0.22 [0.13–0.36] | 40.7 [37.9–43.5] |
