Table and Figure Caption
List
Table 1. Demographic Characteristics of Participants in the
Combined Dataset (Controlled-Setting and Real-world), Controlled-Setting
Position Dataset, and Real-world Dataset
Table 2. Total Number of Annotations Containing Each Class in
the Real-world Dataset, Controlled-Setting Dataset, and Combined
(Controlled-Setting and Real-world) Dataset on Which SLeeP AIDePt-2 was
Trained
Figure 1. Bar Chart of the Frequency of Occurrences of Each
Sleeping Position Class and the Sitting Class in the Real-world Dataset
and Controlled-Setting Dataset. Legend : Real-world dataset shown
in blue, and controlled-setting dataset shown in orange.
Figure 2A. Bar Chart of SLeeP AIDePt-2 Performance Metrics From
the Testing Phase Averaged Across the Five Models’ Test Sets and Across
All Classes. Legend : mAP@0.50 indicates the mean average
precision at an intersection of union of 0.50. mAP@.50-.95 indicates the
mean average precision at intersections of unions between 0.50 and 0.95.
The error bars represent one standard deviation of the respective value
across all measures, which reflects the variability both across models
and classes. The y-axis does not have units because precision, recall,
mAP@0.50, and mAP@.50-.95 are dimensionless values.
Figure 2B. Heatmap of SLeeP AIDePt-2 Performance Metrics
(Columns) From the Testing Phase Averaged Across the Five Models’ Test
Sets For Each of the Predicted Classes (Rows). Legend : AP@0.50
indicates the average precision at an intersection of union of 0.50.
AP@.50-.95 indicates the average precision at intersections of unions
between 0.50 and 0.95. The value of the respective performance metric is
mapped to a colour spectrum from red to yellow to green where values of
0.50 or less are represented by red at the lower end of the spectrum,
values around 0.75 are shades around yellow (oranger if lower than 0.75;
greener if higher than 0.75), and values of 0.90 or more are represented
by green at the higher end of the spectrum. The “all body position
classes average” is provided as the averaged value of the respective
performance metric across the five models’ test sets and the 13 body
position classes. For the “all body position classes average” row, the
value in the AP@0.50 column is the mean AP@0.50, and the value in the
AP@.50-.95 column is the mean AP@.50-.95 since these values represent
averages across multiple classes.
Figure 3. Example Output of SLeeP AIDePt-2 Localising and
Classifying the Sleeping Positions of a Study Participant and Their Bed
Partner as Well as Their Pillows in Eight Different Extracted Frames.Legend : The participant’s and bed partner’s body and pillow
annotations are shown by the coloured boxes (“Ground Truth”, left).
The model’s localization and prediction of the sleeping positions and
pillows, along with its confidence score (between 0 and 1) at the top of
each bounding box, are shown (“Prediction”, right).