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. 2019 Aug 13;42(12):zsz180. doi: 10.1093/sleep/zsz180

Table 3.

Sleep/wake differentiation performance by k-nearest neighbors across different feature inputs in the Apple Watch (PPG, MEMS) dataset

Accuracy Wake correct (specificity) Sleep correct (sensitivity) κ AUC
Motion 0.789 0.672 0.8 0.255 0.803
0.866 0.483 0.9 0.3
0.887 0.405 0.93 0.307
0.9 0.345 0.95 0.307
HR 0.768 0.406 0.8 0.117 0.682
0.845 0.237 0.9 0.117
0.868 0.172 0.93 0.103
0.882 0.12 0.95 0.082
Motion, HR 0.79 0.678 0.8 0.255 0.81
0.867 0.496 0.9 0.308
0.889 0.431 0.93 0.327
0.903 0.38 0.95 0.338
Motion, HR, and Clock Proxy 0.8 0.797 0.8 0.309 0.868
0.877 0.627 0.9 0.391
0.897 0.535 0.93 0.404
0.909 0.458 0.95 0.402

Fraction of wake correct, fraction of sleep correct, κ, and AUC for sleep-wake predictions of k-nearest neighbor classifier with use of motion, HR, clock proxy, or combination of features. HR, heart rate.

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