802 - Wireless Wearable Vital Sign Monitoring Technologies for the Neonatal Intensive Care Unit (NICU): A Systematic Review

Publication Number: 802.7057

Eva B. Senechal, McGill University Faculty of Medicine and Health Sciences, Montreal, PQ, Canada; Alyssa Maximov, McGill University Faculty of Medicine and Health Sciences, Montréal, PQ, Canada; Emily Jeanne, McGill University Faculty of Medicine and Health Sciences, Montreal, PQ, Canada; Daniel J. Radeschi, McGill University Faculty of Medicine and Health Sciences, Pointe Claire, PQ, Canada; Vivian M.G.O. Azevedo, Universidade Federal de Uberlândia, Uberlandia, Minas Gerais, Brazil; Amanda Gross, McGill University Faculty of Medicine and Health Sciences, Montreal, PQ, Canada; Wissam Shalish, McGill University Faculty of Medicine and Health Sciences, Montreal, PQ, Canada; Robert E. Kearney, McGill University Faculty of Medicine and Health Sciences, Montreal, PQ, Canada; Guilherme Sant'Anna, McGill University, Montreal, PQ, Canada

Background: In the NICU vital signs and other physiological signals are continuously detected using sensors connected to bedside monitors via wires. Wires and cables are cumbersome, limit patient mobility, hinder parents’ ability to interact with their children, and may interfere with Kangaroo Care (KC). With the advent of wireless technologies, there have been efforts to develop wireless vital sign monitoring for the NICU.

Objective: This systematic review aims to identify and describe wireless vital sign monitoring technologies used in the NICU, summarize their performances, and critically appraise for risk of bias and applicability concerns.

Design/Methods: A systematic search of the literature published after 2014 was conducted in August 2024 with the assistance of a librarian, in Medline, Embase, Engineering Village, Cochrane, and Web of Science. All results were extracted into Covidence, a literature review software, where two investigators independently reviewed the articles to determine eligibility for inclusion and extracted data from included articles using a data collection form designed in collaboration with neonatologists and engineers. Risk of bias and applicability concerns were assessed using the QUADAS-2 tool. A descriptive analysis was applied.

Results: Of the 3051 articles identified, 22 were included. All were prospective observational studies, primarily originating from North America (n=11, 50%), specifically from the United States (n=8, 39%). Studies included a median sample size of 18 NICU patients (IQR?). Participants were primarily moderately preterm and low birthweight infants (Table 1). Recording durations had a median of 1.18 hours (IQR:0.38-6.33) per patient (Table 2). Wearable devices were primarily placed on the torso, using a strap or an adhesive. Half of the devices recorded more than one vital sign. The most common vital signs reported were heart rate (HR) and respiratory rate (RR) (Table 2). Most studies were focused on accuracy of a novel wearable device and used Bland Altman analysis (Table 2). The majority of studies had low risk of bias and low applicability concerns (Table 3).

Conclusion(s): Research initiatives to develop wireless vital sign monitoring for NICU patients remain in the early stages with relatively small sample sizes, short monitoring duration and a single focus on validity. Larger studies, including evaluation of feasibility and safety of these devices, are needed to advance the field.

Table 1. Participant Information
*Legend: Data are presented as n (%). In certain cases, more than one study site, or age category was included in study thus each category included was counted, or certain information was not provided and therefore the study was not counted in the results

Table 2. Device Information and Study Methodology
Data are presented as n (%). In certain cases, more than one study site, or age category was included in study thus each category included was counted, or certain information was not provided and therefore the study was not counted in the results

Figure 1. Quality Assessment Tool for Diagnostic Accuracy studies (QUADAS) 2 Assessment
Panel A shows results for risk of bias assessment for each category for included studies, Panel risk of bias assessment for each category (excluding flow and timing) for included studies. All results are presented as percentage of all included studies.