# Drowsiness Transitions Detection Using a Wearable Device
## 4 Results
### MSPC-PCA Analysis
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Domain** & **Metrics** & **Description** \\ \hline \multirow{8}{*}{Time} & mean\_nni & Mean of the R–R intervals. \\  & median\_nni & Median of the R–R intervals. \\  & range\_nni & Difference between the maximum and the minimum of the R–R intervals. \\  & sdnn & Standard Deviation of the R–R intervals. \\  & sdsd & Standard deviation of differences between adjacent R–R intervals. \\  & rmssd & Square root of the mean of the sum of the squares of differences between adjacent R–R intervals. \\  & & Intervals’ number differences of successive R–R intervals greater than 50 ms. \\  & pnni\_50 & Derived Proportion by dividing mni\_50 by the R–R intervals’ total number. \\  & nni\_20 & Intervals’ number differences of successive R–R intervals greater than 20 ms. \\  & pnni\_20 & Derived Proportion by dividing mni\_20 by the R–R intervals’ total number. \\  & cvsd & rmssd divided mean\_nni. \\  & cvnni & sdnn divided by mean\_nni. \\  & mean\_hr & Heart rate mean. \\  & min\_hr & Heart rate minimum. \\  & max\_hr & Heart rate maximum. \\  & std\_hr & Standard deviation of the heart rate. \\ \hline \multirow{8}{*}{Frequency} & power\_vlf & Variance in HRV in the very low frequency. \\  & power\_lf & Variance in HRV in the low frequency \\  & power\_hf & Variance in HRV in the high frequency \\  & total\_power & Total power density spectral. \\  & f\_hf\_ratio & f/hf ratio. \\ \hline \multirow{4}{*}{Non-Linear} & csi & Cardiac Sympathetic Index. \\  & cvi & Cardiac Vagal Index. \\ \cline{1-1}  & modified\_csi & Modified csi. \\ \cline{1-1}  & sampen & Sample entropy. \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Heart Rate Variability Time Domain Metrics. second line, the drowsiness levels from Wierwille and Ellsworth's drowsiness scale [16] are plotted over the simulation time. Figure 5: Participant 15 MSPC-PCA Analysis for the Heart Rate Variability. Figure 6: Participant 15 MSPC-PCA Analysis for the Accelerometer information. Figure 7: MSPC-PCA Methodology and Drowsiness Classification. (**a**) participant 15. (**b**) participant 21. It is noticeable that participant 21 has more transitions and reached higher levels of drowsiness than participant 15. Consequently, it also has more out-of-control points using the heart rate variability since, in the drowsiness periods, the value 1 was reached more often, which would be expected. In terms of the accelerometer, the first point, in both cases, is out of control, and it represents the first two minutes using the wearable device. During that time, the participants are adjusting the positioning of the device. It is also visualized that, for participant 15, there is one out-of-control point in common using the heart rate variability and accelerometer. Since this point happened before the recording of the participant's face, it is not possible to check if there is a transition change and greater movement of the participant's arm. This happened with other participants and the drowsiness transition is not affected by noise due to large movements. Another aspect to take into account is that, for participant 15, any out-of-control point does not represent a drowsiness transition, considering the present drowsiness classification. This is contrary to participant 21 in which some transitions are, actually, being detected. For a better understanding of what is happening, what conclusions can be drawn, and what improvements can be implemented, it is necessary to evaluate the number of drowsiness levels transitions, the number of out-of-control points reached using the heart rate variability and accelerometer, and the number of out-of-control points in common (see Figure 8). Globally, considering all the information from all the participants, there are 2 to 18 drowsiness transitions, where 7, 8, and 10 are the most common. However, there are 2 to 12 and 0 to 7 out-of-control points, using the multivariate statistical process control for the heart rate variability and accelerometer, respectively.