HRV and salivary cortisol data in pregnant women

Objective: To develop a machine learning algorithm utilizing heart rate
variability (HRV) and salivary cortisol to detect the presence of acute
stress among pregnant women that may be applied to future clinical
research. Methods: ECG signals and salivary cortisol were analyzed from 29
pregnant women as part of a crossover study involving a standardized acute
psychological stress exposure and a control non-stress condition. A
filter-based features selection method was used to identify the importance
of different features [heart rate (HR), time- and frequency-domain HRV
parameters and salivary cortisol] for stress assessment and reduce the
computational complexity. Five machine learning algorithms were
implemented to assess the presence of stress with and without salivary
cortisol values. Results: On graphical visualization, an obvious
difference in heart rate (HR), HRV parameters and cortisol were evident
among 17 participants between the two visits, which helped the stress
assessment model to distinguish between stress and non-stress exposures
with greater accuracy. Eight participants did not display a clear
difference in HR and HRV parameters but displayed a large increase in
cortisol following stress compared to the non-stress conditions. The
remaining four participants did not demonstrate an obvious difference in
any feature. Six out of nine features emerged from the feature selection
method: cortisol, three time-domain HRV parameters, and two
frequency-domain parameters. Cortisol was the strongest contributing
feature, increasing the assessment accuracy by 10.3% on average across all
five classifiers. The highest assessment accuracy achieved was 92.3%, and
the highest average assessment accuracy was 76.5%. Conclusion: Salivary
cortisol contributed to a significant increase in accuracy of the
assessment model compared to using a range of HRV parameters alone. Our
machine learning model demonstrates acceptable accuracy in detection of
acute stress among pregnant women when combining salivary cortisol with HR
and HRV parameters.