Table 1 Classification results.

The algorithm validation study used LOSO-CV and an RF classifier. The clinical study included manually labeled datasets from all 46 nights with the ADAM sensor mounted on the dominant hand of each subject. The algorithm developed in the algorithm validation study was then deployed on the raw data from the clinical study. The overall accuracy in the clinical study was 99.0% with a sensitivity of 84.3% and a specificity of 99.3%. The accuracy of the algorithm validation was lower (89.1%) due to a higher number of confounding activities to train the algorithm (e.g., typing and texting) that are not seen in nocturnal settings.

Algorithm
validation study
(n = 10)
Clinical study
(n = 11)
Sensitivity87.8%84.3%
Specificity88.1%99.3%
Accuracy89.1%99.0%
Precision94.4%82.5%
F1 score89.8%82.9%