Table 6.
Performance of Personalized and Generalized Sleep-Wake States Predictors Averaged Separately Across Individuals Within Each Study. In Each Column of Each Study, the Boldface Number(s) Indicate(s) the Highest Value Obtained for the Corresponding Metric
| Study | Classifier | Personalized Approach | Generalized Approach | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| ACC | SN | SP | MCC | AUC | ACC | SN | SP | MCC | AUC | ||
| SR | NB | 0.76 | 0.75 | 0.75 | 0.40 | 0.85 | 0.68 | 0.79 | 0.66 | 0.34 | 0.85 |
| RLR | 0.88 | 0.32 | 0.98 | 0.42 | 0.86 | 0.88 | 0.33 | 0.98 | 0.41 | 0.86 | |
| RF | 0.87 | 0.47 | 0.94 | 0.44 | 0.85 | 0.87 | 0.50 | 0.95 | 0.47 | 0.85 | |
| AB | 0.88 | 0.49 | 0.95 | 0.49 | 0.85 | 0.88 | 0.46 | 0.97 | 0.50 | 0.89 | |
| XGB | 0.84 | 0.43 | 0.94 | 0.42 | 0.88 | 0.89 | 0.48 | 0.97 | 0.51 | 0.89 | |
| TI | NB | 0.80 | 0.67 | 0.80 | 0.38 | 0.84 | 0.75 | 0.74 | 0.75 | 0.39 | 0.83 |
| RLR | 0.86 | 0.23 | 1.00 | 0.35 | 0.85 | 0.85 | 0.20 | 0.99 | 0.27 | 0.84 | |
| RF | 0.89 | 0.52 | 0.95 | 0.49 | 0.84 | 0.87 | 0.40 | 0.96 | 0.41 | 0.83 | |
| AB | 0.90 | 0.48 | 0.98 | 0.53 | 0.86 | 0.87 | 0.37 | 0.98 | 0.45 | 0.87 | |
| XGB | 0.80 | 0.27 | 0.95 | 0.32 | 0.88 | 0.88 | 0.37 | 0.98 | 0.46 | 0.88 | |
| AC | NB | 0.60 | 0.70 | 0.57 | 0.24 | 0.70 | 0.72 | 0.41 | 0.83 | 0.25 | 0.69 |
| RLR | 0.76 | 0.13 | 0.98 | 0.18 | 0.67 | 0.77 | 0.10 | 1.00 | 0.23 | 0.68 | |
| RF | 0.72 | 0.26 | 0.88 | 0.17 | 0.64 | 0.76 | 0.17 | 0.96 | 0.21 | 0.63 | |
| AB | 0.75 | 0.26 | 0.92 | 0.22 | 0.62 | 0.77 | 0.15 | 0.98 | 0.25 | 0.69 | |
| XGB | 0.87 | 0.47 | 0.96 | 0.48 | 0.66 | 0.77 | 0.16 | 0.98 | 0.25 | 0.69 | |
| NW | NB | 0.82 | 0.79 | 0.82 | 0.45 | 0.90 | 0.83 | 0.75 | 0.84 | 0.45 | 0.90 |
| RLR | 0.91 | 0.40 | 0.98 | 0.44 | 0.89 | 0.91 | 0.33 | 0.99 | 0.42 | 0.90 | |
| RF | 0.91 | 0.53 | 0.95 | 0.49 | 0.88 | 0.91 | 0.49 | 0.96 | 0.48 | 0.86 | |
| AB | 0.91 | 0.55 | 0.95 | 0.50 | 0.84 | 0.92 | 0.44 | 0.99 | 0.54 | 0.92 | |
| XGB | 0.91 | 0.55 | 0.96 | 0.52 | 0.91 | 0.92 | 0.45 | 0.99 | 0.54 | 0.92 | |
Notes: © 2018 IEEE. Reprinted, with permission, from Khademi A, El-Manzalawy Y, Buxton OM, Honavar V. Toward personalized sleep-wake prediction from actigraphy. In 2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018 (Vol. 2018-March pp. 414-417). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/BHI.2018.8333456.45
Abbreviations: SR, sleep restriction; TI, tiagabine; AC, acoustics; NW, night working, NB, Naive Bayes; RLR, regularized logistic regression; RF, random forest; AB, adaptive boosting; XGB, extreme gradient boosting; ACC, accuracy; SN, sensitivity; SP, specificity; MCC, Matthews correlation coefficient; AUC, area under curve.