Table 1.
Use of technology for diagnosis of sleep disorders[23]
|
Type of sensor
|
Number of studies
|
Percentage
|
Sample size
|
AUC1
|
Evidence
|
| Bed/mattress sensors | 11 | 27% | 10-366 | AUC: 0.94-1.00 | Strong |
| Wearables | 10 | 24% | 20-404 | AUC: 0.80-1.00 | Strong |
| Smartphones | 7 | 17% | 15-620 | AUC: 0.61-0.95 | Moderate to strong |
| Nasal airflow sensors | 5 | 12% | 5-288 | AUC: 0.77-0.91 | Moderate to strong |
| Other digital tools (could not be classified) | 8 | 20% | 10-359 | AUC: 0.85-1.00 | Strong |
1
Area under curve measures discrimination power of the predictive classification model. AUC: Area under curve.