Evaluation of the SmartCap technology by Monash University
Following is a report based on our initial analysis of data collected for analysis of the SmartCap fatigue monitoring technology.
The primary outcome used for this analysis was four consecutive misses during an Osler task, which is indicative of having brief periods of EEG defined sleep.
Monash University found that the SmartCap fatigue algorithm performed well at identifying when people were severely sleepy in the laboratory setting.
- SmartCap fatigue level 4 provided a high sensitivity of 94.75%, correctly identifying most of the one minute periods when severe sleepiness was present;
- The lowest one-minute average output observed for an impaired (as per the definition for this primary analysis) subject was 3.683 (as determined by SmartCap).
- SmartCap average fatigue level 4 had a good specificity (0.82), hence it had a small to moderate false positive rate (meaning individuals who showed SmartCap fatigue level 4, but were not severely sleepy according to the primary outcome measure on the OSLER test).
Overall, the area under the curve of the ROC curves of 0.90 is consistent with the SmartCap fatigue algorithm being good at determining when severe sleepiness is present.
Click to read more – Monash-Fatigue-Assessment-full-report