Principal Component Analysis of Dynamic Thermography Data from Pregnant and Non-Pregnant Women

In this work we propose a novel approach for the analysis of dynamic thermography data based on the application of principal component analysis to thermal video data. The proposed approach is applied to thermal video recordings of the abdominal region of pregnant and non-pregnant female participants, and reveals consistent temperature trends across participants that to date have not been reported. Both for the pregnant and non-pregnant participants, the first principal component was found to describe approximately 80% of the total variance, and when combined, the first three principal components explained more than 90% of the total variance. The presence of consistent temporal components across participants is indicative of common passive as well as active underlying mechanisms that give rise to the observed temperature patterns. The outcome of this investigation supports further development and application of the proposed method in obstetrics and other medical fields.