Identifying Patterns of Heart Rate Variability of Healthy Latina Pregnant Individuals Using Tech-based Wearable Smart Device
Skip to main content
eScholarship
Open Access Publications from the University of California

UC Irvine

UC Irvine Electronic Theses and Dissertations bannerUC Irvine

Identifying Patterns of Heart Rate Variability of Healthy Latina Pregnant Individuals Using Tech-based Wearable Smart Device

No data is associated with this publication.
Abstract

Objectives: Autonomic Nervous System (ANS) plays a central role in dynamic adaptation during pregnancy in accordance with the pregnancy demands which otherwise can lead to various pregnancy complications. Despite the importance of understanding the ANS function during pregnancy, literature lack sufficiency in the ANS assessment. In this study we pursued to investigate two aims: Aim 1 (experimental): Identify HRV patterns from a sample of healthy pregnant Latina individuals in Orange County from 20-24 weeks of GA through one week postpartum. Aim 2 (implementational). Tailor the implementation of the tech-based wearable smart device (to collect HRV data) using a participatory approach and evidence-informed strategies to optimize acceptability and adherence during the study. Materia and method: N=16 participants were enrolled into the study from which N=14 (N=13 healthy and n=1 complicated) participants proceed to analysis section. For the analysis of experimental aim, we conducted unsupervised and supervised machine learning modeling. For the implementational aim, we used proportion and relational content analysis to understand the adherence, acceptancy, and personal perspectives of the participants toward smart device application. Results: The results showed that the participants occupied certain space in the cartesian system, and the complicated pregnant individual showed a distinct pattern compared to healthy participants. The findings of T-test indicated that the average HRV and HRV intercept of healthy and non-healthy subjects differed significantly (p<0.05) during 17 weeks of the study. The results of HLM analysis showed a significant positive relationship between days and average HRV regardless of being healthy or complicated, indicating that HRV increases over time significantly. Random forest results showed that factors such as age, height, weight, BMI, sleep, activity, food, and stress can predict HRV in addition to time. the completion rate of the biweekly (anxiety and depression) and monthly (stress) surveys were 100% until after childbirth where the rate dropped to around 80%. The completion rate for daily questions stayed above 80% until 38 weeks of gestational age. Then it gradually decreased toward post-partum. Oura ring wearing rate was above 80% from the beginning of the study until 35 weeks of gestational age except for gestational week of 23 when the rate dropped to 74% across the participants. The wearing time after 35th gestational age, more or less, tend to decrease toward postpartum when the wearing rate was about 31% across all the participants. Enrollment rate was 71.42% and attrition rate was 6.25%. The main themes of relational content analysis were categorized into four categories of personal desire, social acceptancy and desire, support system for health awareness, and conditions associated with the device/platform efficiency. Conclusion: The study findings suggested high adherence and acceptancy that have potential to improve more by indicated implementational strategies. HRV was significantly different between healthy and complicated pregnancies and tend to increase during pregnancy regardless of being healthy. There are other factors that can play roles in predicting HRV in addition to time.

Main Content

This item is under embargo until August 18, 2025.