Supporting lifestyle change in obese pregnant mothers through the wearable internet-of-things (SLIM) -intervention for overweight pregnant women: Study protocol for a quasi-experimental trial

Abstract

Objectives To assess, in terms of self-efficacy in weight management, the effectiveness of the SLIM lifestyle intervention among overweight or obese women during pregnancy and after delivery, and further to exploit machine learning and event mining approaches to build personalized models. Additionally, the aim is to evaluate the implementation of the SLIM intervention. Methods This prospective trial, which is a non-randomized, quasi-experimental, pre-post intervention, includes an embedded mixed-method process evaluation. The SLIM Intervention is delivered by public health nurses (n = 9) working in maternity clinics. The public health nurses recruited overweight women (n = 54) at their first antenatal visit using convenience sampling. The core components of the intervention i.e. health technology, motivational interviewing, feedback, and goal setting, are utilized in antenatal visits in maternity clinics starting from gestational week 15 or less and continuing to 12 weeks after delivery. Mixed effect models are used to evaluate change over time in self-efficacy, weight management and weight change. Simple mediation models are used to assess calories consumed and moderate to vigorous physical activity (MVPA) as mediators between self-efficacy and weight change. Signal processing and machine learning techniques are exploited to extract events from the data collected via the Oura ring and smartphone-based questionnaires. Discussion The SLIM intervention was developed in collaboration with overweight women and public health nurses working in maternity clinics. This study evaluates the effectiveness of the intervention among overweight women in increasing self-efficacy and achieving a healthy weight; thus, impacting the healthy lifestyle and long-term health of the whole family. The long-term objective is to contribute to women’s health by supporting weight-management through behavior change via interventions conducted in maternity clinics. Trial registration The trial was registered at the Clinicaltrials.gov register platform (ID NCT04826861) on 17 March 2021.

Preterm Birth Risk Stratification through Longitudinal Heart Rate and HRV Monitoring in Daily Life

“…Instead of ECG, photoplethysmography (PPG) is applied as the prominent method for acquiring HRV parameters through wearables 40 . The continuous monitoring of pregnant women using wearable devices allows for the exploration of various pregnancy issues, such as stress 28,41 , hypertension 42 , mental problems 43 , and obesity 44 . Moreover, it enables the assessments of maternal sleep 45 , physical activity 46,47 , and fetal parameters, including heart activity [48][49][50] and movement 51,52 .…”