In the United States, standard prenatal care recommendations include a health care provider visit every 4 weeks until 28 weeks’ gestation, every 2 weeks until 36 weeks’ gestation, and weekly from 36 weeks’ gestation until birth. Research shows that telehealth has been used to supplement prenatal care in areas with limited health care access, and it has been shown that patients who are able to have a combination of virtual and in-person health care provider visits over the course of their obstetrics care have higher satisfaction levels with their care [1,2]. Patients who require childcare or travel long distances to receive care also benefit from a telehealth model, as it allows them to receive health care on a more consistent basis [3]. A fetal heart monitoring device could be used as a supplementary method of fetal monitoring for those patients who are not able to access a traditional clinic easily or who may need to be monitored more frequently. This could be a more feasible option, bridging the access gap in areas with limited antenatal health care access.

Fetal monitoring is used throughout pregnancy to assess fetal well-being and oxygenation status. Doppler ultrasound technology, first introduced for clinical fetal monitoring in the 1970s, remains one of the most commonly used tools during both routine prenatal care and labor. The device operates by emitting ultrasound waves through a handheld transducer; differences between the transmitted and reflected wave frequencies are used for analysis (the Doppler shift) [4]. This allows clinicians to evaluate the movement of fetal cardiac walls and valves, providing real-time information about fetal heart activity. Over the past several decades, the use of Doppler ultrasound has contributed to earlier detection of fetal compromise and improved perinatal outcomes, particularly when incorporated into standardized antenatal care monitoring protocols [5,6].

Unlike intermittent Doppler ultrasound, which is typically used during clinic visits, fetal electrocardiogram (fECG) enables longer-duration monitoring by capturing electrical cardiac signals [7,8]. As Doppler technology is not used for continuous fetal monitoring due to risk of harming the fetus due to overheating, fetal monitoring tools such as fECG may be safer alternatives for continuous monitoring [9,10]. The fECG comprises electrical signals that can be sensed using noninvasive sensors that are placed on the abdomen of a pregnant patient. The electrical signals that comprise the fECG are very similar to those that comprise the adult echocardiogram heart rhythms, but they create a weaker signal. As the fECG signals are weaker, algorithms are used to separate the fECG signals from the maternal and bodily noise signals [11].

While fECG has demonstrated feasibility for fetal heart rate detection, its clinical effectiveness and role in routine prenatal care are still being evaluated. Remote fECG monitoring should therefore be viewed as a complementary approach rather than a replacement for established antenatal assessment methods.

A significant factor contributing to antepartum care health disparities is the prevalence of maternity care deserts, where there is limited or no access to obstetrical services or health care providers [12]. Low reimbursement rates, financial issues, and lack of obstetrical and anesthesia providers have forced many hospitals to close their obstetrical units. Those who are pregnant are sometimes forced to drive longer distances to access prenatal services, which also contributes to poor outcomes [13-15]. Additionally, individuals living in rural and underserved urban communities generally face worse health outcomes than those in well-resourced urban areas [16-18]. This disparity may be driven by limited access to health care, unemployment, financial hardship, and educational inequities [5].

Maternal health outcomes are worse in rural areas, and fetal outcomes are also affected. [19]. Unfortunately, when maternal health outcomes during pregnancy are worsened, this can adversely affect fetal health outcomes during pregnancy. Maternal health issues that are directly related to pregnancy (preeclampsia, gestational diabetes, etc) and underlying chronic health issues are some of the top contributors to maternal and fetal morbidity and mortality [20].

Fetal monitoring is a vital aspect of antepartum care. Technology in this area has greatly advanced in the previous decades [21]. Current fetal monitoring techniques, such as Doppler monitoring, can be bulky and restrict maternal movement during the monitoring period. During Doppler monitoring, the device is fastened to the maternal abdomen using an elastic band. It is important that the device be applied with care to optimize the accuracy of readings [22]. One thing to note about Doppler monitoring is that during the monitoring period, the patient is required to be immobile to increase the accuracy of readings [23].

During the third week of pregnancy, the fetal heart begins to develop. By the seventh week, it has developed into its structure of 4 chambers. The fetal heart rate can be detected by Doppler ultrasound beginning at 10 weeks of pregnancy. Routine monitoring of the fetal heart begins around 18 weeks of pregnancy [5].

Congenital heart defects (CHDs) are the foremost factor leading to fetal mortality from age 0 to 1 year [24]. They often impact the individual in a lifelong manner, and some are more complex than others, needing advanced treatment techniques and accurate monitoring. Ventricular septal defects, which cause heart malformation, are the most common type of defect, impacting 1% of babies born per year [24,25]. Ventricular septal defects cause a hole between the ventricles of the heart; they can exist by themselves, or they can comprise one of multiple CHDs affecting a patient [26]. CHD treatment has improved in recent years, and an important contributing factor to this improvement has been early detection. Early detection is essential, as it allows health care providers to create a treatment plan and monitor the baby before the baby is critically affected by the defect [5,27].

Difficulties in accessing care in rural areas can lead to lower rates of CHD detection in rural areas compared to urban areas [28]. Inability to access maternal fetal medicine specialists in rural areas can also impede early diagnosis. To address this health care gap and increase access to maternal and antenatal health care, remote monitoring may be a feasible alternative to allow health care providers to screen earlier for CHD and monitor higher-risk patients more frequently.

Telehealth services include any health care experience that is aided by telecommunication (video or audio communication) [29]. Telehealth is currently used in a variety of ways to enhance obstetrics care through apps that allow for services such as health care diary entries, remote blood pressure monitoring, and fertility tracking. Numerous studies have also explored the practice of remote fetal monitoring during antepartum care [30,31]. Remote monitoring and telehealth virtual visits with health care providers can help to increase patient access to care and reduce the need for in-person health care appointments [2,32].

During the COVID-19 pandemic, telehealth use greatly increased; however, this increase was more profound in urban communities than in rural communities. Barriers such as internet access and less widespread use of telehealth in rural communities have led to people in rural areas not fully benefiting from this technology [29]. In the future, telehealth can be used to bridge the rural health care access gap, allowing for increased rates of maternal and perinatal health care [33].

Remote fetal monitoring technologies have been proposed as a potential adjunct to prenatal care, particularly in settings where access to in-person services is limited [34]. Rather than directly preventing maternal mortality, such technologies may support earlier detection of fetal concerns, facilitate monitoring in higher-risk pregnancies, and reduce logistical burdens associated with frequent clinic visits [30,35,36]. In several experimental trials where remote and in-hospital fetal monitoring technologies were compared, participants in the remote fetal monitoring groups voiced higher levels of satisfaction; additionally, health outcome differences between the hospital and remote groups were not statistically significant, indicating that remote fetal monitoring may provide a viable supplement to in-person clinical monitoring [37,38].

This study aimed to evaluate the acceptability of a wireless fetal heart monitor among women of reproductive age for monitoring fetal heart rate throughout pregnancy. A wireless fetal heart monitor could allow mothers to be more comfortable and feel more in control during their prenatal monitoring sessions. This wireless fetal monitor would be placed on the maternal abdomen. The device would use an algorithm to extract the fetal heart data from the maternal heart data and bodily noise. The wireless fetal heart monitor would use fECG technology to monitor the fetal heart signals. This technology differs from techniques such as Doppler ultrasound that are traditionally used during fetal monitoring sessions. As previously discussed, it collects the electrical signals from the maternal abdomen. These signals are separated using a standardized algorithm, allowing the extracted fECG to be analyzed independently of the maternal ECG [11].

This extracted fECG would be transmitted via an app to health care providers, with the goal of allowing for increased health care accessibility and monitoring of the fetal heart. The wireless fetal monitor could allow women who have low health care access to have more consistent care. The device is intended to be multifunctional to match the needs of the patient population and clinical setting, as it could be used for both continuous monitoring and intermittent use, as well as in multiple settings, including both in-patient and home-based care. To inform device development, a survey was designed, distributed, and analyzed among women of reproductive age. Although participation was not limited to individuals who were currently pregnant, the broader population was included to provide a foundational understanding to support future research and device development. The questionnaire was developed to address the question “What is the level of acceptability of a fetal monitoring device among women of reproductive age based on survey data?”

The questionnaire complements concurrent research on the development of a wearable fetal monitoring device by helping to determine the optimal device size and specifications. This allows for the development of a device that best serves the target population and will be practical for everyday use.

Responses were collected via snowball recruitment of participants. The study aim, along with a QR code linking to the questionnaire, was disseminated through posters in public spaces and electronic newsletters. Participant inclusion criteria included being a woman of reproductive age (18-49 years) and the ability to read English. Responses were collected from September 2023 to January 2024.

An incentive of US $20 in the form of a prepaid gift card was provided to participants who completed the survey. To maintain anonymity of survey respondents, compensation information was not collected with participant responses. At the end of the survey, a link was provided to all respondents. Instructions were provided to participants indicating that participants who desired to receive compensation for their survey completion could follow the link to a compensation survey. This survey was separate from the acceptability survey and allowed for participant responses to maintain anonymity. Participants who filled out the compensation survey were provided with compensation, which was a prepaid gift card that was mailed to participants. Follow-up was conducted to ensure that participants received compensation.

Survey responses were analyzed using SPSS Statistics (version29; IBM Corp). Descriptive statistics were used to summarize participant characteristics and survey responses. Associations between health literacy and device acceptability, as well as between age group and acceptability, were examined using the chi-square test. Qualitative responses to the open-ended survey question were analyzed using thematic analysis to identify key themes.

Participant location (urban or rural) was determined using the submission IP address. The zip code location of the IP address was determined using an IP geolocation tool [45]. The urban or rural designation of the zip code was found using the Rural Health Information Hub. Counties with a population of 5000 or fewer inhabitants were considered rural for the purposes of the survey analysis [46]. Responses were individually analyzed to determine the classification of their locations.

Of the initial responses received, incomplete surveys and responses identified as automated or invalid were excluded prior to analysis. Only surveys meeting eligibility criteria and completing acceptability items were included in the final analyses.

This study was reviewed and approved by the Wichita State University Institutional Review Board (institutional review board number: 5260). Informed consent was obtained electronically prior to survey participation. Survey responses were anonymous, and no identifying information was collected. Data were stored securely and analyzed in deidentified form. Participants received a US $20 prepaid gift card as compensation through a separate survey mechanism to preserve anonymity.

A total of 163 participants completed the questionnaire. Demographic analyses were conducted using the full sample (N=163). Of these participants, 103 completed the device acceptability items and were included in acceptability analyses. On average, the survey participants completed it in 5.1 (SD 3.03) minutes, and 103 participants provided responses to questions gauging acceptability of the device. The total response numbers for each question varied slightly, as the questions were optional to complete.

The survey was limited to female participants aged 18 to 49 years. Participants’ age, ethnicity, and education level were collected. Participants’ internet access levels were also assessed. The median age of survey respondents was greater than 30 years (Table 1).

The race or ethnicity breakdown for the survey participants included American Indian or Alaska Native: 11.4% (19/163), Asian: 7.4% (12/163), Black or African American: 13.4% (22/163), Hispanic or Latinx: 14.8% (24/163), Middle Eastern or North African: 1.3% (2/163), White: 49.7% (81/163), and 2 or more races or ethnicities: 2% (3/163). These percentages were similar to the percentage breakdown of the US population. The 2020 US Census recorded the following percentages for race and ethnicity: White: 57.8%, Black or African American: 12.1%, Hispanic or Latinx: 18.7%, American Indian or Alaska Native: 0.7%, Asian: 5.9%, 2 or more: 4.1%, and other: 0.6% [47]. The distributed survey included Middle Eastern or North African as a racial option. This designation was included with White in the 2020 Census, but it will be given its own designation in the 2030 Census [48].

The participant education levels were as follows: high school degree or equivalent: 2% (3/163), some college but no degree: 42.6% (69/163), associate degree: 10.8% (18/163), bachelor’s degree: 21.6% (35/163), and graduate degree: 23% (38/163). This is slightly higher than the US national average that was recorded in the 2020 Census [47].

Most participants demonstrated high health literacy (83/103, 80.6%), while 19.4% (20/103) were classified as having less than high health literacy. There was no statistically significant association between health literacy and device acceptability (χ²₁=0.8; P=.34). Although a higher proportion of participants with high health literacy reported acceptability (55/83, 66.3%) compared to those with low health literacy (11/20, 55%), this difference was not statistically significant (χ²₁=0.8; P=.34).

Among participants included in the acceptability analysis (n=103), participants aged 30 to 49 years demonstrated a higher rate of device acceptability (40/54, 74.1%) than younger participants aged 18 to 29 years (26/49, 53.1%; Table 2). A chi-square test of independence indicated a statistically significant association between age group and device acceptability (χ²₁=4.9; P=.03), with participants aged 30 to 49 years demonstrating higher acceptability than those aged 18 to 29 years. Regarding device features, 70.7% (73/103) of participants preferred a device measuring 2.5 × 7.6 cm or smaller, indicating a preference for a smaller device. In total, 73.6% (120/163) of participants indicated that they would be comfortable with wearing the device daily. In gauging device convenience, 14.7% (24/163) strongly disagreed and 28.8% (47/163) somewhat disagreed that the monitor would limit their daily activities. Additionally, 49.7% (81/163) agreed to some degree that the device would be “compatible with most aspects of my activity.”

When participants were asked about how they would feel about using the device for the first time, 11% (18/163) somewhat agreed and 2.5% (4/163) strongly agreed that they would feel anxious. However, 21.5% (35/163) strongly disagreed with feeling anxious about using a device they had not previously used. Over half of the respondents agreed that learning to use the device seemed easy.

Responses to an open-ended question asking participants to voice doubts about the device indicated concern for privacy. Of the 23 participants who provided a written response, 6 participants voiced concern for data from the monitor being shared with third parties, insurance companies, or any entity outside of their care team. Participants stated concern about the process of learning more about how to use the device, as well as worry about potential side effects. Finally, concerns were raised about the accuracy of the device.

This formative survey examined perceived acceptability of a wearable fetal heart monitoring device among women of reproductive age. Overall, acceptability was moderate, with higher acceptance among older respondents and strong preferences for smaller, unobtrusive device designs.

As found in the survey, increasing acceptability levels were positively correlated with increasing age. A total of 163 participants completed the survey, with 103 responses to acceptability questions; older women aged 30 to 49 years showed higher rates of acceptability (n=40, 74.1%) than young women aged 18 to 29 years (n=26, 53.1%). Participant feedback involving concerns of the target population regarding the wearability, usability, and safety of the device will be considered when developing the fetal monitoring device.

Overall acceptability was moderate to high, suggesting general openness to remote fetal monitoring technologies among the surveyed population. Higher acceptability observed among women aged 30 to 49 years compared to those aged 18 to 29 years may reflect greater perceived clinical value of monitoring or varying levels of trust in cloud-based storage and digital health technologies. Strong preference for a small and low-profile device highlights the importance of minimizing physical burden and visibility to support comfort and use.

Findings should be interpreted as reflecting perceptions of acceptability, not actual use or clinical effectiveness, as participants evaluated a hypothetical device rather than the actual technology. Furthermore, findings should be interpreted through a broad viewpoint, as the study population included all women of reproductive age, not specifically those who were pregnant at the time of the study or had been pregnant before. The perceptions of acceptability that were evaluated provide a foundation for more targeted acceptability research.

When interpreting the questionnaire results, it should be noted that implications for device use and care in underserved areas are future oriented and were not empirically demonstrated in this study. Additionally, as the surveyed sample was not limited to those who were pregnant at the time of the survey or those who have had pregnancy experience, the results have decreased direct relevance to the target device users.

Assessing acceptability during early‑stage development provides critical guidance for user-centered design prior to feasibility, effectiveness, and implementation testing. Incorporating user-identified preferences, particularly related to device size and wearability, may increase adoption and sustained use of wearable fetal monitoring technologies. Age-related differences in acceptability suggest the need for tailored communication or education strategies to address perceived value and technology concerns among younger users.

Although not directly evaluated in this study, devices developed with user input may hold future potential to support prenatal care access in underserved or rural populations, supporting targeted investigation.

Most respondents were from urban areas (with a population >5000 residents) [46]. Given prior evidence of rural-urban differences in health care access and health literacy, the observed health literacy and device acceptability estimates may be higher than would have been observed in a sample with greater rural representation. People who live in rural locations have slower medical responses to health care emergencies such as stroke [16]. There are fewer specialists who work in rural areas, leading to a lack of proper health care availability [17]. In a study on rural health care use in the United States, patients residing in rural areas were generally found to have lower levels of health care use and worse health statuses than their urban counterparts [18]. All of these factors can contribute to rural health literacy levels, and this can create a reduced average health literacy level among patients residing in rural areas when compared to patients residing in urban areas [49].

Although remote fetal monitoring may be especially relevant in rural or underserved contexts, most respondents in this study resided in urban areas. As such, findings should be interpreted as reflecting general perceptions of acceptability rather than preferences specific to rural populations. The potential relevance of this technology for rural care represents a future application that warrants targeted investigation.

The survey included a highly educated population, and most respondents were from urban areas. This may have impacted the responses that were received, creating a skewed representation of anticipated device acceptability.

Survey distribution presented some challenges, as sharing the link online created a risk of bot-generated invalid responses. There was a survey that was implemented before this survey, but it was overwhelmed by bot responses, and the results were discarded in favor of creating a new survey and reimplementing it. Furthermore, the distribution methods used (snowball recruitment, postering, and social media) may not have created a fully representative sample of the target population.

As respondents were not required to be currently pregnant or to have recent pregnancy experience, findings reflect anticipated acceptability rather than experiential usability during pregnancy.

This questionnaire was one component of an interdisciplinary effort to develop a remote fetal monitoring device. The next phase of this project will involve prototype development and testing. Findings from the questionnaire are being used to inform device design, with the goal of ensuring it aligns with patient preferences and needs.

Future research would benefit from limiting respondents to pregnant individuals to more directly assess acceptability within the intended user population. The current survey also provides a foundation for refining future instruments that will evaluate user experience and acceptability during prototype testing.

As remote monitoring devices are introduced in clinical and home settings, patient education will be essential to successful adoption. Survey findings suggest that individuals with higher health literacy may be more receptive to using a fetal monitoring device, underscoring the importance of clear communication and patient-centered education strategies.

These findings provide preliminary insight into perceived acceptability and patient-centered preferences for a hypothetical wearable fetal heart rate monitoring device among women of reproductive age. The results may inform early-stage design and device development by highlighting features related to usability, comfort, and convenience that are important to potential users. Participant feedback offers initial guidance for aligning device development with user expectations. However, these findings should be interpreted in light of the study’s limitations and as exploratory.

Future research is needed to evaluate acceptability among pregnant populations in real-world settings, as well as to examine how acceptability relates to actual device use and clinical outcomes.