A Review of Patient Bed Sensors for Monitoring of Vital Signs.

The analysis of biomedical signals is a very challenging task. This review paper is focused on the presentation of various methods where biomedical data, in particular vital signs, could be monitored using sensors mounted to beds. The presented methods to monitor vital signs include those combined with optical fibers, camera systems, pressure sensors, or other sensors, which may provide more efficient patient bed monitoring results. This work also covers the aspects of interference occurrence in the above-mentioned signals and sleep quality monitoring, which play a very important role in the analysis of biomedical signals and the choice of appropriate signal-processing methods. The provided information will help various researchers to understand the importance of vital sign monitoring and will be a thorough and up-to-date summary of these methods. It will also be a foundation for further enhancement of these methods.

Prognostic value of heart rate variability for risk of serious adverse events in continuously monitored hospital patients.

Technological advances allow continuous vital sign monitoring at the general ward, but traditional vital signs alone may not predict serious adverse events (SAE). This study investigated continuous heart rate variability (HRV) monitoring's predictive value for SAEs in acute medical and major surgical patients. Data was collected from four prospective observational studies and two randomized controlled trials using a single-lead ECG. The primary outcome was any SAE, secondary outcomes included all-cause mortality and specific non-fatal SAE groups, all within 30 days. Subgroup analyses of medical and surgical patients were performed. The primary analysis compared the last 24 h preceding an SAE with the last 24 h of measurements in patients without an SAE. The area under a receiver operating characteristics curve (AUROC) quantified predictive performance, interpretated as low prognostic ability (0.5-0.7), moderate prognostic ability (0.7-0.9), or high prognostic ability (> 0.9). Of 1402 assessed patients, 923 were analysed, with 297 (32%) experiencing at least one SAE. The best performing threshold had an AUROC of 0.67 (95% confidence interval (CI) 0.63-0.71) for predicting cardiovascular SAEs. In the surgical subgroup, the best performing threshold had an AUROC of 0.70 (95% CI 0.60-0.81) for neurologic SAE prediction. In the medical subgroup, thresholds for all-cause mortality, cardiovascular, infectious, and neurologic SAEs had moderate prognostic ability, and the best performing threshold had an AUROC of 0.85 (95% CI 0.76-0.95) for predicting neurologic SAEs. Predicting SAEs based on the accumulated time below thresholds for individual continuously measured HRV parameters demonstrated overall low prognostic ability in high-risk hospitalized patients. Certain HRV thresholds had moderate prognostic ability for prediction of specific SAEs in the medical subgroup.

Evaluation of video-based rPPG in challenging environments: Artifact mitigation and network resilience.

Video-based remote photoplethysmography (rPPG) has emerged as a promising technology for non-contact vital sign monitoring, especially under controlled conditions. However, the accurate measurement of vital signs in real-world scenarios faces several challenges, including artifacts induced by videocodecs, low-light noise, degradation, low dynamic range, occlusions, and hardware and network constraints. In this article, a systematic and comprehensive investigation of these issues is conducted, measuring their detrimental effects on the quality of rPPG measurements. Additionally, practical strategies are proposed for mitigating these challenges to improve the dependability and resilience of video-based rPPG systems. Methods for effective biosignal recovery in the presence of network limitations are detailed, along with denoising and inpainting techniques aimed at preserving video frame integrity. Compared to previous studies, this paper addresses a broader range of variables and demonstrates improved accuracy across various rPPG methods, emphasizing generalizability for practical applications in diverse scenarios with varying data quality. Extensive evaluations and direct comparisons demonstrate the effectiveness of these approaches in enhancing rPPG measurements under challenging environments, contributing to the development of more reliable and effective remote vital sign monitoring technologies.

Remote Vital Sign Monitoring in Admission Avoidance Hospital at Home: A Systematic Review.

OBJECTIVES: To examine randomized controlled trials (RCTs) of "hospital at home" (HAH) for admission avoidance in adults presenting with acute physical illness to identify the use of vital sign monitoring approaches and evidence for their effectiveness. DESIGN: Systematic review. SETTING AND PARTICIPANTS: This review compared strategies for vital sign monitoring in admission avoidance HAH for adults presenting with acute physical illness. Vital sign monitoring can support HAH acute multidisciplinary care by contributing to safety, determining requirement of further assessment, and guiding clinical decisions. There are a wide range of systems currently available, including reliable and automated continuous remote monitoring using wearable devices. METHODS: Eligible studies were identified through updated database and trial registries searches (March 2, 2016, to February 15, 2023), and existing systematic reviews. Risk of bias was assessed using the Cochrane risk of bias 2 tool. Random effects meta-analyses were performed, and narrative summaries provided stratified by vital sign monitoring approach. RESULTS: Twenty-one eligible RCTs (3459 participants) were identified. Two approaches to vital sign monitoring were characterized: manual and automated. Reporting was insufficient in the majority of studies for classification. For HAH compared to hospital care, 6-monthly mortality risk ratio (RR) was 0.94 (95% CI 0.78-1.12), 3-monthly readmission to hospital RR 1.02 (0.77-1.35), and length of stay mean difference 1.91 days (0.71-3.12). Readmission to hospital was reduced in the automated monitoring subgroup (RR 0.30 95% CI 0.11-0.86). CONCLUSIONS AND IMPLICATIONS: This review highlights gaps in the reporting and evidence base informing remote vital sign monitoring in alternatives to admission for acute illness, despite expanding implementation in clinical practice. Although continuous vital sign monitoring using wearable devices may offer added benefit, its use in existing RCTs is limited. Recommendations for the implementation and evaluation of remote monitoring in future clinical trials are proposed.

Development of a Tetherless Bioimpedance Device That Uses Morphologic Changes to Predict Blood Flow Restrictions Mimicking Peripheral Artery Disease Progression.

A tetherless multi-targeted bioimpedance device was designed, modeled, built, and tested for measuring arterial pulse and, using morphological analysis, its potential for monitoring blood flow restrictions that mimic Peripheral Artery Disease (PAD) was assessed across multiple peripheral arteries. Specifically, we first developed a small form factor, tetherless, bioimpedance device, based on high-frequency structure simulator (HFSS) simulations. After designing and building the device we then tested it in vivo on human subjects on multiple arteries and found that we did not need to modify the gain on the device compared to the bench top system. Further, it was found that changes in the morphology of the bioimpedance signal over time, depicted through the ratio of the first and second harmonic in the signal frequency, could be used to predict blood flow restrictions that mimic peripheral artery disease (PAD). The HFSS simulations helped guide the modulation frequency selection and the placement of the bioimpedance electrodes. We built the device and compared it to two commercially available bioimpedance devices and it was shown to demonstrate a distinct advantage in its multi-target capability, enabling more accurate pulse measurements from different arteries without the need for tuning the circuit for each artery. Comparing the ratio of the 1st and 2nd harmonics as a function of the blood flow restriction, the two commercial devices showed a maximum error across arteries of between 22% and 27% depending on the measurement location, whereas our system consistently displayed a stable value of just below 4%. With this system, there is the potential for comprehensive and personalized medical examinations for PAD at the point of care (POC).

Human Activity Recognition in a Free-Living Environment Using an Ear-Worn Motion Sensor.

Human activity recognition (HAR) technology enables continuous behavior monitoring, which is particularly valuable in healthcare. This study investigates the viability of using an ear-worn motion sensor for classifying daily activities, including lying, sitting/standing, walking, ascending stairs, descending stairs, and running. Fifty healthy participants (between 20 and 47 years old) engaged in these activities while under monitoring. Various machine learning algorithms, ranging from interpretable shallow models to state-of-the-art deep learning approaches designed for HAR (i.e., DeepConvLSTM and ConvTransformer), were employed for classification. The results demonstrate the ear sensor's efficacy, with deep learning models achieving a 98% accuracy rate of classification. The obtained classification models are agnostic regarding which ear the sensor is worn and robust against moderate variations in sensor orientation (e.g., due to differences in auricle anatomy), meaning no initial calibration of the sensor orientation is required. The study underscores the ear's efficacy as a suitable site for monitoring human daily activity and suggests its potential for combining HAR with in-ear vital sign monitoring. This approach offers a practical method for comprehensive health monitoring by integrating sensors in a single anatomical location. This integration facilitates individualized health assessments, with potential applications in tele-monitoring, personalized health insights, and optimizing athletic training regimes.

Improving patient outcomes following vital sign monitoring protocol failure: A retrospective cohort study.

Background and Aims: Vital sign monitoring needs to be timely and correct to recognize deteriorating patients early and trigger the relevant clinical response. The aim of this study is to retrospectively evaluate compliance specifically toward the regional vital sign monitoring protocol the so called early warning score protocol (EWS-protocol) 72 h before a medical emergency team response (MET-response) and thereby illuminate whether poor compliance translates into a worse patient outcome. Methods: It was investigated all eligible patients that underwent MET responses during the calendar year 2019. The inclusion criteria encompassed somatic patients above 18 years of age admitted to the hospital and detailed evaluations of the medical records of the included patients were conducted. Results: Four hundred and twenty-nine MET-responses were included in the final analysis. EWS-protocol failure was observed for more than half the patients within all the time frames assessed. Thirty-day mortality was significantly higher for patients subject to EWS protocol failure in the timeframes 24-16, 16-8, 8-0 h before MET response. Adjusting for admission length, age, and gender, patients subject to EWS-protocol failure had an odds ratio (OR) of 1.9, 2.0, 2.1, 2.3 for mortality in the time frames 72-48, 24-16, 16-8, and 8-0 h before the MET-response, respectively. The adjusted OR for ICU-admission was 1.7, and 1.6 for patients subject to EWS-protocol failure in the time frames 16-8 and 8-0 h before MET-response, respectively. Conclusion: According to all the data analysis in this article, there is evidence that compliance toward the NEWS-protocol is poor. EWS-protocol failure is associated with a significant higher mortality and ICU-admission rate.

Effectiveness of a Smartphone App-Based Intervention With Bluetooth-Connected Monitoring Devices and a Feedback System in Heart Failure (SMART-HF Trial): Randomized Controlled Trial.

BACKGROUND: Current heart failure (HF) guidelines recommend a multidisciplinary approach, discharge education, and self-management for HF. However, the recommendations are challenging to implement in real-world clinical settings. OBJECTIVE: We developed a mobile health (mHealth) platform for HF self-care to evaluate whether a smartphone app-based intervention with Bluetooth-connected monitoring devices and a feedback system can help improve HF symptoms. METHODS: In this prospective, randomized, multicenter study, we enrolled patients 20 years of age and older, hospitalized for acute HF, and who could use a smartphone from 7 tertiary hospitals in South Korea. In the intervention group (n=39), the apps were automatically paired with Bluetooth-connected monitoring devices. The patients could enter information on vital signs, HF symptoms, diet, medications, and exercise regimen into the app daily and receive feedback or alerts on their input. In the control group (n=38), patients could only enter their blood pressure, heart rate, and weight using conventional, non-Bluetooth devices and could not receive any feedback or alerts from the app. The primary end point was the change in dyspnea symptom scores from baseline to 4 weeks, assessed using a questionnaire. RESULTS: At 4 weeks, the change in dyspnea symptom score from baseline was significantly greater in the intervention group than in the control group (mean -1.3, SD 2.1 vs mean -0.3, SD 2.3; P=.048). A significant reduction was found in body water composition from baseline to the final measurement in the intervention group (baseline level mean 7.4, SD 2.5 vs final level mean 6.6, SD 2.5; P=.003). App adherence, which was assessed based on log-in or the percentage of days when symptoms were first observed, was higher in the intervention group than in the control group. Composite end points, including death, rehospitalization, and urgent HF visits, were not significantly different between the 2 groups. CONCLUSIONS: The mobile-based health platform with Bluetooth-connected monitoring devices and a feedback system demonstrated improvement in dyspnea symptoms in patients with HF. This study provides evidence and rationale for implementing mobile app-based self-care strategies and feedback for patients with HF. TRIAL REGISTRATION: ClinicalTrials.gov NCT05668000; https://clinicaltrials.gov/study/NCT05668000.

Three Years of Continuous Vital Signs Monitoring on the General Surgical Ward: Is It Sustainable? A Qualitative Study.

Continuous monitoring of vital signs using a wireless wearable device was implemented in 2018 at a surgical care unit of an academic hospital. This study aimed at gaining insight into nurses' and patients' perspectives regarding the use and innovation of a continuous vital signs monitoring system, three years after its introduction. This qualitative study was performed in a surgical, non-intensive care unit of an academic hospital in 2021. Key-user nurses (nurses with additional training and expertise with the device) and patients were selected for semi-structured interviews, and nurses from the ward were selected for a focus group interview using a topic list. Transcripts of the audio tapes were deductively analysed using four dimensions for adoptions of information and communication technologies (ICT) devices in healthcare. The device provided feelings of safety for nurses and patients. Nurses and patients had a few issues with the device, including the size and the battery life. Nurses gained knowledge and skills in using the system for measurement and interpretations. They perceived the system as a tool to improve the recognition of clinical decline. The use of the system could be further developed regarding the technical device's characteristics, nurses' interpretation of the data and the of type of alarms, the information needs of patients, and clarification of the definition and standardization of continuous monitoring. Three years after the introduction, wireless continuous vital signs monitoring is the new standard of care according to the end-users at the general surgical ward.

Indicators of patient deterioration in poorly resourced private hospitals: Which vital sign to watch? A retrospective case-control study.

BACKGROUND: Patient vital signs are a measure of wellness if monitored regularly and accurately. Staff shortages in poorly resourced regional hospitals often result in inadequate patient monitoring, putting patients at risk of undetected deterioration. OBJECTIVE: This study aims to explore the pattern and completeness of vital sign monitoring and the contribution of each vital sign in predicting clinical deterioration events in resource-poor regional/rural hospitals. METHOD: Using a retrospective case-control study design, we compared 24 h of vital sign data from deteriorating and nondeteriorating patients from two poorly-resourced regional hospitals. Descriptive statistics, t-tests, and analysis of variance are used to compare patient-monitoring frequency and completeness. The contribution of each vital sign in predicting patient deterioration was determined using the Area Under the Receiver Operator Characteristic curve and binary logistical regression analysis. RESULTS: Deteriorating patients were monitored more frequently (9.58 [7.02] times) in the 24-h period than nondeteriorating patients (4.93 [2.66] times). However, the completeness of vital sign documentation was higher in nondeteriorating (85.2%) than in deteriorating patients (57.7%). Body temperature was the most frequently omitted vital sign. Patient deterioration was positively linked to the frequency of abnormal vital signs and the number of abnormal vital signs per set (Area Under the Receiver Operator Characteristic curve: 0.872 and 0.867, respectively). No single vital sign strongly predicts patient outcomes. However, a supplementary oxygen value of >3 L/min and a heart rate of >139 beats/min were the best predictors of patient deterioration. CONCLUSION: Given the poor resourcing and often geographical remoteness of small regional hospitals, it is prudent that the nursing staff are made aware of the vital signs that best indicate deterioration for the cohort of patients in their care. Tachycardic patients on supplementary oxygen are at high risk of deterioration.

Video plethysmography for contactless measurement of respiratory rate in surgical patients.

The accurate recording of respiratory rate (RR) without contact is important for patient care. The current methods for RR measurement such as capnography, pneumography, and plethysmography require patient contact, are cumbersome, or not accurate for widespread clinical use. Video Plethysmography (VPPG) is a novel automated technology that measures RR using a facial video without contact. The objective of our study was to determine whether VPPG can feasibly and accurately measure RR without contact in surgical patients at a clinical setting. After research ethics approval, 216 patients undergoing ambulatory surgery consented to the study. Patients had a 1.5 min video of their faces taken via an iPad preoperatively, which was analyzed using VPPG to obtain RR information. The RR prediction by VPPG was compared to 60-s manual counting of breathing by research assistants. We found that VPPG predicted RR with 88.8% accuracy and a bias of 1.40 ± 1.96 breaths per minute. A significant and high correlation (0.87) was observed between VPPG-predicted and manually recorded RR. These results did not change with the ethnicity of patients. The success rate of the VPPG technology was 99.1%. Contactless RR monitoring of surgical patients at a hospital setting using VPPG is accurate and feasible, making this technology an attractive alternative to the current approaches to RR monitoring. Future developments should focus on improving reliability of the technology.

Video plethysmography for contactless blood pressure and heart rate measurement in perioperative care.

The purpose of this study was to evaluate the feasibility and accuracy of remote Video Plethysmography (VPPG) for contactless measurements of blood pressure (BP) and heart rate (HR) in adult surgical patients in a hospital setting. An iPad Pro was used to record a 1.5-minute facial video of the participant's face and VPPG was used to extract vital signs measurements. A standard medical device (Welch Allyn) was used for comparison to measure BP and HR. Trial registration: NCT05165381. Two-hundred-sixteen participants consented and completed the contactless BP and HR monitoring (mean age 54.1 ± 16.8 years, 58% male). The consent rate was 75% and VPPG was 99% successful in capturing BP and HR. VPPG predicted SBP, DBP, and HR with a measurement bias ± SD, -8.18 ± 16.44 mmHg, - 6.65 ± 9.59 mmHg, 0.09 ± 6.47 beats/min respectively. Pearson's correlation for all measurements between VPPG and standard medical device was significant. Correlation for SBP was moderate (0.48), DBP was weak (0.29), and HR was strong (0.85). Most patients were satisfied with the non-contact technology with an average rating of 8.7/10 and would recommend it for clinical use. VPPG was highly accurate in measuring HR, and is currently not accurate in measuring BP in surgical patients. The VPPG BP algorithm showed limitations in capturing individual variations in blood pressure, highlighting the need for further improvements to render it clinically effective across all ranges. Contactless vital signs monitoring was well-received and earned a high satisfaction score.

The Evaluation of Remote Monitoring Technology Across Participants With Different Skin Tones.

BACKGROUND: Many research studies seek to improve vital sign monitoring to enhance the conditions under which doctors and caregivers track patients' health. Non-invasive and contactless monitoring has emerged as an optimal solution for this problem, with telemedicine, self-monitoring, and well-being tools being the next generation of technology in the biomedical field. However, there is worldwide concern about the general purpose and bias toward a certain demographic group of these techniques. In particular, skin tone and the accuracy of monitoring dark skin tone groups have been key questions among researchers, with the lack of results and studies contributing to this uncertainty. METHODS: This paper proposes a benchmark for remote monitoring solutions against a medical device across different skin tone people. Around 330 videos from 90 patients were analyzed, and heart rate (HR) and heart rate variability (HRV) were compared across different subgroups. The Fitzpatrick scale (1-6) was used to classify participants into three skin tone groups: 1 and 2, 3 and 4, and 5 and 6. RESULTS: The results showed that our proposed methodology could estimate heart rate with a mean absolute error of 3 bpm across all samples and subgroups. Moreover, for heart rate variability (HRV) metrics, we achieved the following results: in terms of mobility assistive equipment (MAE), the HRV-inter-beat interval (IBI) was 10 ms, the HRV-standard deviation of normal to normal heartbeats (SDNN) was 14 ms, and the HRV-root mean square of successive differences (RMSSD) between normal heartbeats was 22 ms. No significant performance decrease was found for any skin tone group, and there was no error trend toward a certain group. CONCLUSIONS: The study showed that our methodology meets acceptable agreement levels for the proposed metrics. Furthermore, the experiments showed that skin tone did not impact the results, which remained within the same range across all groups. Moreover, it enables the end users to understand their general well-being and improve their overall health.

A Real-Time Evaluation Algorithm for Noncontact Heart Rate Variability Monitoring.

Noncontact vital sign monitoring based on radar has attracted great interest in many fields. Heart Rate Variability (HRV), which measures the fluctuation of heartbeat intervals, has been considered as an important indicator for general health evaluation. This paper proposes a new algorithm for HRV monitoring in which frequency-modulated continuous-wave (FMCW) radar is used to separate echo signals from different distances, and the beamforming technique is adopted to improve signal quality. After the phase reflecting the chest wall motion is demodulated, the acceleration is calculated to enhance the heartbeat and suppress the impact of respiration. The time interval of each heartbeat is estimated based on the smoothed acceleration waveform. Finally, a joint optimization algorithm was developed and is used to precisely segment the acceleration signal for analyzing HRV. Experimental results from 10 participants show the potential of the proposed algorithm for obtaining a noncontact HRV estimation with high accuracy. The proposed algorithm can measure the interbeat interval (IBI) with a root mean square error (RMSE) of 14.9 ms and accurately estimate HRV parameters with an RMSE of 3.24 ms for MEAN (the average value of the IBI), 4.91 ms for the standard deviation of normal to normal (SDNN), and 9.10 ms for the root mean square of successive differences (RMSSD). These results demonstrate the effectiveness and feasibility of the proposed method in emotion recognition, sleep monitoring, and heart disease diagnosis.

Nmr-VSM: Non-Touch Motion-Robust Vital Sign Monitoring via UWB Radar Based on Deep Learning.

In recent years, biometric radar has gained increasing attention in the field of non-touch vital sign monitoring due to its high accuracy and strong ability to detect fine-grained movements. However, most current research on biometric radar can only achieve heart rate or respiration rate monitoring in static environments, which have strict monitoring requirements and single monitoring parameters. Moreover, most studies have not applied the collected data despite their significant potential for applications. In this paper, we introduce a non-touch motion-robust vital sign monitoring system via ultra-wideband (UWB) radar based on deep learning. Nmr-VSM not only enables multi-dimensional vital sign monitoring under human motion environments but also implements cardiac anomaly detection. The design of Nmr-VSM includes three key components. Firstly, we design a UWB radar that can perform multi-dimensional vital sign monitoring, including heart rate, respiratory rate, distance, and motion status. Secondly, we collect real experimental data and analyze the impact of eight factors, such as motion status and distance, on heart rate monitoring. We then propose a deep neural network (DNN)-based heart rate data correction model that achieves high robustness in motion environments. Finally, we model the heart rate variability (HRV) of the human body and propose a convolutional neural network (CNN)-based anomaly detection model that achieves low-latency detection of heart diseases, such as ventricular tachycardia and ventricular fibrillation. Experimental results in a real environment demonstrate that Nmr-VSM can not only accurately monitor heart rate but also achieve anomaly detection with low latency.

Understanding the effects of overnight vital signs monitoring on sleep duration and disruptions in hospitalized children: A scoping review.

PROBLEM: Overnight vital signs are typically taken every four hours on pediatric acute care units, despite limited evidence supporting the efficacy of this practice. Vital signs are often ordered and collected without considering the patient's clinical status or potential impact that they may have on sleep. We sought to understand the impact that overnight vital sign monitoring has on sleep duration and disruptions among hospitalized children in an acute care setting. ELIGIBILITY CRITERIA: We conducted a scoping review using the Preferred Reporting Items for Systematic Reviews and Meta-analysis Protocols extension for scoping reviews (PRISMA-ScR). Studies were included if they addressed the relationship between vital signs monitoring and sleep among children hospitalized in an acute care unit. SAMPLE: Eleven studies from 2012 to 2022 were included in the final review. RESULTS: Vital signs monitoring is the most common sleep disruptor among hospitalized children in acute care units and early evidence suggests that minimizing overnight vital signs may be a safe intervention for clinically stable children. Methods for measuring sleep duration and disruptions are heterogenous and validated tools are not often used. Finally, nurses report comfort with forgoing overnight vital signs when their patient's clinical status is stable. CONCLUSION: Despite a lack of evidence regarding the efficacy of every 4 h vital signs, overnight vital signs monitoring is consistently the greatest disruptor to sleep for hospitalized children. IMPLICATIONS: Nurses should play a central role in guiding vital signs monitoring that maintains safety and improves sleep in hospitalized children.

Home-Made, Self-Powered, Skin-Attachable Sensing Platform for Diverse Vital Sign Monitoring.

Wearable electronic sensors that can perform real-time, continuous, and high-fidelity monitoring of diverse biophysical signals from the human body are burgeoning and exhibit great potential to transform traditional clinical healthcare. However, such emerging devices often suffer from strict requirements of special precursor materials and sophisticated fabrication procedures. Here, we present a new paradigm of a self-powered, skin-attachable, and multifunctional sensing platform that can be fully created just at home with daily necessities. Its operating mechanism is based on mechanical/thermal regulation of the potential difference output of a primary electrochemical cell. This proposed sensing platform is totally self-powered and can be conformally attached to the skin for continuous monitoring of both mechanical and thermal stimulations. A wide spectrum of vital physiological signs of the human body, including body temperature, heart/pulse rate, respiratory rate, coughing, and body motions, can be continuously monitored and analyzed with this home-made sensing platform. This study demonstrates that the lab-conducted professional and expensive scientific research can also be accomplished at home, opening up new opportunities for home-centered healthcare in low-resource environments. Moreover, this work can serve as a handy and cost-efficient prototype for classroom education and clinical training purposes.

Process Evaluation of a Wireless Wearable Continuous Vital Signs Monitoring Intervention in 2 General Hospital Wards: Mixed Methods Study.

BACKGROUND: Continuous monitoring of vital signs (CMVS) using wearable wireless sensors is increasingly available to patients in general wards and can improve outcomes and reduce nurse workload. To assess the potential impact of such systems, successful implementation is important. We developed a CMVS intervention and implementation strategy and evaluated its success in 2 general wards. OBJECTIVE: We aimed to assess and compare intervention fidelity in 2 wards (internal medicine and general surgery) of a large teaching hospital. METHODS: A mixed methods sequential explanatory design was used. After thorough training and preparation, CMVS was implemented-in parallel with the standard intermittent manual measurements-and executed for 6 months in each ward. Heart rate and respiratory rate were measured using a chest-worn wearable sensor, and vital sign trends were visualized on a digital platform. Trends were routinely assessed and reported each nursing shift without automated alarms. The primary outcome was intervention fidelity, defined as the proportion of written reports and related nurse activities in case of deviating trends comparing early (months 1-2), mid- (months 3-4), and late (months 5-6) implementation periods. Explanatory interviews with nurses were conducted. RESULTS: The implementation strategy was executed as planned. A total of 358 patients were included, resulting in 45,113 monitored hours during 6142 nurse shifts. In total, 10.3% (37/358) of the sensors were replaced prematurely because of technical failure. Mean intervention fidelity was 70.7% (SD 20.4%) and higher in the surgical ward (73.6%, SD 18.1% vs 64.1%, SD 23.7%; P<.001). Fidelity decreased over the implementation period in the internal medicine ward (76%, 57%, and 48% at early, mid-, and late implementation, respectively; P<.001) but not significantly in the surgical ward (76% at early implementation vs 74% at midimplementation [P=.56] vs 70.7% at late implementation [P=.07]). No nursing activities were needed based on vital sign trends for 68.7% (246/358) of the patients. In 174 reports of 31.3% (112/358) of the patients, observed deviating trends led to 101 additional bedside assessments of patients and 73 consultations by physicians. The main themes that emerged during interviews (n=21) included the relative priority of CMVS in nurse work, the importance of nursing assessment, the relatively limited perceived benefits for patient care, and experienced mediocre usability of the technology. CONCLUSIONS: We successfully implemented a system for CMVS at scale in 2 hospital wards, but our results show that intervention fidelity decreased over time, more in the internal medicine ward than in the surgical ward. This decrease appeared to depend on multiple ward-specific factors. Nurses' perceptions regarding the value and benefits of the intervention varied. Implications for optimal implementation of CMVS include engaging nurses early, seamless integration into electronic health records, and sophisticated decision support tools for vital sign trend interpretation.

Multi-Layer Beam Scanning Leaky Wave Antenna for Remote Vital Signs Detection at 60 GHz.

A multi-layer beam-scanning leaky wave antenna (LWA) for remote vital sign monitoring (RVSM) at 60 GHz using a single-tone continuous-wave (CW) Doppler radar has been developed in a typical dynamic environment. The antenna's components are: a partially reflecting surface (PRS), high-impedance surfaces (HISs), and a plain dielectric slab. A dipole antenna works as a source together with these elements to produce a gain of 24 dBi, a frequency beam scanning range of 30°, and precise remote vital sign monitoring (RVSM) up to 4 m across the operating frequency range (58-66 GHz). The antenna requirements for the DR are summarised in a typical dynamic scenario where a patient is to have continuous monitoring remotely, while sleeping. During the continuous health monitoring process, the patient has the freedom to move up to one meter away from the fixed sensor position.The proposed multi-layer LWA system was placed at a distance of 2 m and 4 m from the test subject to confirm the suitability of the developed antenna for dynamic RVSM applications. A proper setting of the operating frequency range (58 to 66 GHz) enabled the detection of both heart beats and respiration rates of the subject within a 30° angular range.

Advanced wireless monitoring for children in the cardiac perioperative setting.

INTRODUCTION: More than 40,000 children undergo surgical interventions annually for the treatment of congenital heart defects. Intraoperative and postoperative vital sign monitoring is a cornerstone of pediatric care. METHODS: A single-arm prospective observational study was performed. Pediatric patients undergoing a procedure with a planned admission to the Cardiac Intensive Care Unit at Lurie Children's Hospital (Chicago, IL) were eligible for enrollment. Participant vital signs were monitored using standard equipment and an FDA-cleared experimental device (ANNE® ) consisting of a wireless patch positioned at the suprasternal notch and index finger or foot. The primary goal of the study was to assess real-world feasibility of wireless sensors in pediatric patients with congenital cardiac defects. RESULTS: A total of 13 patients were enrolled, ranging in age from 4 months to 16 years with a median age of 4 years. Overall, 54% (n = 7) were female and the most common anomaly in the cohort was an atrial septal defect (n = 6). The mean admission length was 3 days (range 2-6), resulting in more than 1000 h of vital sign monitoring (⟩60,000 data points). Bland-Altman plots were generated for heart rate and respiratory rate to assess beat-to-beast differences between the standard equipment and the experimental sensors. CONCLUSIONS: Novel, wireless, flexible sensors demonstrated comparable performance to standard monitoring equipment in a cohort of pediatric patients with congenital cardiac heart defects undergoing surgery.