How Wearable Sensors Can Support the Research on Foetal and Pregnancy Outcomes: A Scoping Review

Maugeri, Andrea; Barchitta, Martina; Agodi, Antonella

doi:10.3390/jpm13020218

Cited by 7 publications

(4 citation statements)

References 55 publications

(193 reference statements)

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“…The expansion of the digital health technology (DHT) space over the past decade has given rise to novel, remote tools that can be worn on the person including wearables and smartphone apps, herein referred to as 'personal DHTs'. Personal DHTs can be used to capture rich, semi-continuous multimodal (of different types) health-related information [9] that is uniquely relevant to pregnancy [10]. Consumer-grade wearables are capable of tracking semi-continuous measures of physiology (e.g.…”

Section: Introductionmentioning

confidence: 99%

Does anyone fit the average? Describing the heterogeneity of pregnancy symptoms using wearables and mobile apps

Goodday,

Yang,

Karlin

et al. 2024

Preprint

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Wearables, apps and other remote smart devices can capture rich, objective physiologic, metabolic, and behavioral information that is particularly relevant to pregnancy. The objectives of this paper were to 1) characterize individual level pregnancy self-reported symptoms and objective features from wearables compared to the aggregate; 2) determine whether pregnancy self-reported symptoms and objective features can differentiate pregnancy-related conditions; and 3) describe associations between self-reported symptoms and objective features. Data are from the Better Understanding the Metamorphosis of Pregnancy study, which followed individuals from preconception to three-months postpartum. Participants (18-40 years) were provided with an Oura smart ring, a Garmin smartwatch, and a Bodyport Cardiac Scale. They also used a study smartphone app with surveys and tasks to measure symptoms. Analyses included descriptive spaghetti plots for both individual-level data and cohort averages for select weekly reported symptoms and objective measures from wearables. This data was further stratified by pregnancy-related clinical conditions such as preeclampsia and preterm birth. Mean Spearman correlations between pairs of self-reported symptoms and objective features were estimated. Self-reported symptoms and objective features during pregnancy were highly heterogeneous between individuals. While some aggregate trends were notable, including an inflection in heart rate variability approximately eight weeks prior to delivery, these average trends were highly variable at the n-of-1 level, even among healthy individuals. Pregnancy conditions were not well differentiated by objective features. With the exception of self-reported swelling and body fluid volume, self-reported symptoms and objective features were weakly correlated (mean Spearman correlations <0.1). High heterogeneity and complexities of associations between subjective experiences and objective features across individuals pose challenges for researchers and highlights the dangers in reliance on aggregate approaches in the use of wearable data in pregnant individuals. Innovation in machine learning and AI approaches at the n-of-1 level could help to accelerate the field.

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Section: Introductionmentioning

confidence: 99%

Does anyone fit the average? Describing the heterogeneity of pregnancy symptoms using wearables and mobile apps

Goodday,

Yang,

Karlin

et al. 2024

Preprint

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“…The primary benefits of doing this were improved work efficiency of health professionals (HPs) and better quality of life for women with GDM. Moreover, some studies [ 7 – 11 ] show that women extensively utilize health technologies during pregnancy to access crucial information, monitor their well-being, and address pregnancy-related concerns. Health apps, wearable devices, and telemedicine platforms have made it possible for pregnant individuals to track their prenatal progress, receive personalized health recommendations, and connect with healthcare professionals remotely [ 7 – 11 ].…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, some studies [ 7 – 11 ] show that women extensively utilize health technologies during pregnancy to access crucial information, monitor their well-being, and address pregnancy-related concerns. Health apps, wearable devices, and telemedicine platforms have made it possible for pregnant individuals to track their prenatal progress, receive personalized health recommendations, and connect with healthcare professionals remotely [ 7 – 11 ]. Using these technologies, women stay informed about their pregnancy’s development, receive timely medical support, and actively engage in managing their health.…”

Section: Introductionmentioning

confidence: 99%

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Barriers and facilitators of using health information technologies by women: a scoping review

Moulaei,

Bahaadinbeigy

2023

BMC Med Inform Decis Mak

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Background and aim Health information technologies play a vital role in addressing diverse health needs among women, offering a wide array of services tailored to their specific requirements. Despite the potential benefits, the widespread utilization of these technologies by women faces numerous barriers and challenges. These barriers can cause women to either reduce their usage of health technologies or refrain from using them altogether. Therefore, this review was done with the aim of identifying and classifying barriers and facilitators. Methods Some databases, including PubMed, Web of Sciences, and Scopus were searched using related keywords. Then, according to the inclusion and exclusion criteria, the articles were evaluated and selected. Finally, the barriers and facilitators were identified and classified. Results Out of 14,399 articles, finally 35 articles were included in the review. In general, 375 barriers (232 items) and facilitators (143 items) were extracted from the studies. After merging similar items, 121 barriers (51 items) and facilitators (70 items) identified were organized into five main themes (management, technological, legal and regulatory, personal, and data and information management). The most important barriers were “privacy, confidentiality, and security concerns” (n = 24), “deficiencies and limitations of infrastructure, software, hardware, and network” (n = 19), “sociocultural challenges” (n = 15), and “poor economic status” (n = 15). Moreover, the most important facilitators were “increasing awareness, skills and continuous education of women” (n = 17, in personal theme), “providing training services” (n = 14, in management theme), “simple, usable, and user-friendly design of technologies” (n = 14, in technological theme), and “providing financial or non-financial incentives (motivation) for women” (n = 14, in personal theme). Conclusion This review showed that in order to use technologies, women face many barriers, either specific to women (such as gender inequality) or general (such as lack of technical skills). To overcome these barriers, policymakers, managers of organizations and medical centers, and designers of health systems can consider the facilitators identified in this review.

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The impact of healthy pregnancy on features of heart rate variability and pulse wave morphology derived from wrist-worn photoplethysmography

Bester,

Almario Escorcia,

Fonseca

et al. 2023

Sci Rep

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Due to the association between dysfunctional maternal autonomic regulation and pregnancy complications, tracking non-invasive features of autonomic regulation derived from wrist-worn photoplethysmography (PPG) measurements may allow for the early detection of deteriorations in maternal health. However, even though a plethora of these features—specifically, features describing heart rate variability (HRV) and the morphology of the PPG waveform (morphological features)—exist in the literature, it is unclear which of these may be valuable for tracking maternal health. As an initial step towards clarity, we compute comprehensive sets of HRV and morphological features from nighttime PPG measurements. From these, using logistic regression and stepwise forward feature elimination, we identify the features that best differentiate healthy pregnant women from non-pregnant women, since these likely capture physiological adaptations necessary for sustaining healthy pregnancy. Overall, morphological features were more valuable for discriminating between pregnant and non-pregnant women than HRV features (area under the receiver operating characteristics curve of 0.825 and 0.74, respectively), with the systolic pulse wave deterioration being the most valuable single feature, followed by mean heart rate (HR). Additionally, we stratified the analysis by sleep stages and found that using features calculated only from periods of deep sleep enhanced the differences between the two groups. In conclusion, we postulate that in addition to HRV features, morphological features may also be useful in tracking maternal health and suggest specific features to be included in future research concerning maternal health.

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How Wearable Sensors Can Support the Research on Foetal and Pregnancy Outcomes: A Scoping Review

Cited by 7 publications

References 55 publications

Does anyone fit the average? Describing the heterogeneity of pregnancy symptoms using wearables and mobile apps

Does anyone fit the average? Describing the heterogeneity of pregnancy symptoms using wearables and mobile apps

Barriers and facilitators of using health information technologies by women: a scoping review

The impact of healthy pregnancy on features of heart rate variability and pulse wave morphology derived from wrist-worn photoplethysmography

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