Remote Monitoring Of Vital Signs Research Articles

The ECG Signal Monitoring System Using Machine Learning Methods and LoRa Technology

An electrocardiogram (ECG) is the first step in diagnosing heart disease. Heart rhythm abnormalities are among the early signs of heart disease, which can contribute to a patient’s heart attack, stroke, or sudden death. The importance of the ECGs has increased with the development of technologies based on machine learning and remote monitoring of vital signs. In particular, early detection of arrhythmias is of great importance when it comes to diagnosing a patient with heart disease. This is made possible through recognizing and classifying pathological patterns in the ECG signal. This paper presents a system for mobile monitoring of ECG signals enriched with the results of the study of the application of machine learning models from the group of Tree-based ML techniques and Neural Networks in the context of heart disease classification. The research was carried out through the use of the publicly available PTB-XL database of the ECG signals. The results were analyzed in the context of classification accuracy for 2, 5 and 15 classes of heart disease. Moreover, a novelty in the work is the proposal of machine learning techniques and architectures neural networks, which, have been selected to be applicable to IoT devices. It has been proven that the proposed solution can run in real time on IoT devices.

A Guide to Measuring Heart and Respiratory Rates Based on Off-the-Shelf Photoplethysmographic Hardware and Open-Source Software.

The remote monitoring of vital signs via wearable devices holds significant potential for alleviating the strain on hospital resources and elder-care facilities. Among the various techniques available, photoplethysmography stands out as particularly promising for assessing vital signs such as heart rate, respiratory rate, oxygen saturation, and blood pressure. Despite the efficacy of this method, many commercially available wearables, bearing Conformité Européenne marks and the approval of the Food and Drug Administration, are often integrated within proprietary, closed data ecosystems and are very expensive. In an effort to democratize access to affordable wearable devices, our research endeavored to develop an open-source photoplethysmographic sensor utilizing off-the-shelf hardware and open-source software components. The primary aim of this investigation was to ascertain whether the combination of off-the-shelf hardware components and open-source software yielded vital-sign measurements (specifically heart rate and respiratory rate) comparable to those obtained from more expensive, commercially endorsed medical devices. Conducted as a prospective, single-center study, the research involved the assessment of fifteen participants for three minutes in four distinct positions, supine, seated, standing, and walking in place. The sensor consisted of four PulseSensors measuring photoplethysmographic signals with green light in reflection mode. Subsequent signal processing utilized various open-source Python packages. The heart rate assessment involved the comparison of three distinct methodologies, while the respiratory rate analysis entailed the evaluation of fifteen different algorithmic combinations. For one-minute average heart rates' determination, the Neurokit process pipeline achieved the best results in a seated position with a Spearman's coefficient of 0.9 and a mean difference of 0.59 BPM. For the respiratory rate, the combined utilization of Neurokit and Charlton algorithms yielded the most favorable outcomes with a Spearman's coefficient of 0.82 and a mean difference of 1.90 BrPM. This research found that off-the-shelf components are able to produce comparable results for heart and respiratory rates to those of commercial and approved medical wearables.

Wireless Patient Health Monitoring System

Wireless Patient Health Monitoring Systems (WPHMS) have emerged as transformative solutions in modern healthcare, facilitating continuous and remote monitoring of patients' vital signs in real-time. This paper presents a comprehensive exploration of a Wireless Patient Health Monitoring System leveraging the Blynk app, a versatile IoT platform. The system is designed to enable seamless data collection, transmission, and visualization of critical health parameters such as pulse rate, temperature, and blood pressure. By integrating cutting-edge hardware components with intuitive software interfaces, the proposed system offers unprecedented flexibility and accessibility in patient monitoring, transcending the limitations of traditional wired monitoring systems. The research begins with a thorough review of existing literature on wireless healthcare technologies, highlighting the evolution of patient monitoring systems and the role of IoT platforms in revolutionizing healthcare delivery. Building upon this foundation, the paper proceeds to outline the hardware architecture of the WPHMS, detailing the selection and integration of microcontroller boards, sensor modules.

IOT and AI Implementations on Remote Healthcare Monitoring System

Abstract: "IoT and AI Implementations on Remote Healthcare Monitoring System using Raspberry Pi 3" seeks to revolutionize healthcare by integrating cutting-edge technologies into a cohesive system for remote patient monitoring. Leveraging the power of Raspberry Pi 3, Internet of Things (IoT) devices will be employed to collect real-time health data from patients in diverse locations. This data will then undergo sophisticated analysis through Artificial Intelligence (AI) algorithms, enhancing the system's ability to identify anomalies, trends, and potential health risks with a high degree of accuracy. The Raspberry Pi 3 serves as a versatile and cost-effective hub, managing the connectivity and processing requirements of the IoT devices. The system aims to provide continuous and proactive healthcare support by enabling remote monitoring of vital signs and timely interventions based on AI- driven insights. The outcomes of this project not only contribute to the advancement of healthcare technology but also address the growing need for scalable and accessible healthcare solutions in a rapidly evolving digital landscape.

A Low-Cost Wearable Device to Estimate Body Temperature Based on Wrist Temperature.

The remote monitoring of vital signs and healthcare provision has become an urgent necessity due to the impact of the COVID-19 pandemic on the world. Blood oxygen level, heart rate, and body temperature data are crucial for managing the disease and ensuring timely medical care. This study proposes a low-cost wearable device employing non-contact sensors to monitor, process, and visualize critical variables, focusing on body temperature measurement as a key health indicator. The wearable device developed offers a non-invasive and continuous method to gather wrist and forehead temperature data. However, since there is a discrepancy between wrist and actual forehead temperature, this study incorporates statistical methods and machine learning to estimate the core forehead temperature from the wrist. This research collects 2130 samples from 30 volunteers, and both the statistical least squares method and machine learning via linear regression are applied to analyze these data. It is observed that all models achieve a significant fit, but the third-degree polynomial model stands out in both approaches. It achieves an R2 value of 0.9769 in the statistical analysis and 0.9791 in machine learning.

A Wearable Internet of Things Device for Noninvasive Remote Monitoring of Vital Signs Related to Heart Failure

Cardiovascular disease is one of the leading causes of death in the world. Heart failure is a cardiovascular disease in which the heart is unable to pump sufficient blood to fulfill the body’s requirements and can lead to fluid overload. Traditional solutions are not adequate to address the progression of heart failure. Herein, we report a body-mounted wearable sensor to monitor the parameters related to heart failure. These include heart rate, blood oxygen saturation, thoracic impedance, and activity status. The device is compact and wearable and measures the parameters continuously in real time. The device is an Internet of Things (IoT) device connected with a cloud-based database enabling the parameters to be visualized on a mobile application.

IoT Based Health Monitoring System

Abstract: The rapid advancements in the Internet of Things (IoT) have paved the way for revolutionary healthcare solutions. This paper proposes an IoT-based health monitoring system aimed at providing continuous and remote monitoring of patients' vital signs and physiological parameters. This real-time data collection and analysis empowers proactive healthcare, enhancing patient safety and quality of life.

Activity recognition for clinical remote vital sign monitoring based on a single in-ear sensor

Activity recognition for clinical remote vital sign monitoring based on a single in-ear sensor

Evaluation of the nurse-assisted eHealth intervention ‘eHealth@Hospital-2-Home’ on self-care by patients with heart failure and colorectal cancer post-hospital discharge: protocol for a randomised controlled trial

BackgroundPatients with heart failure (HF) and colorectal cancer (CRC) are prone to comorbidity, a high rate of readmission, and complex healthcare needs. Self-care for people with HF and CRC after hospitalisation can be challenging, and patients may leave the hospital unprepared to self-manage their disease at home. eHealth solutions may be a beneficial tool to engage patients in self-care.MethodsA randomised controlled trial with an embedded evaluation of intervention engagement and cost-effectiveness will be conducted to investigate the effect of eHealth intervention after hospital discharge on the self-efficacy of self-care. Eligible patients with HF or CRC will be recruited before discharge from two Norwegian university hospitals. The intervention group will use a nurse-assisted intervention—eHealth@Hospital-2-Home—for six weeks. The intervention includes remote monitoring of vital signs; patients’ self-reports of symptoms, health and well-being; secure messaging between patients and hospital-based nurse navigators; and access to specific HF and CRC health-related information. The control group will receive routine care. Data collection will take place before the intervention (baseline), at the end of the intervention (Post-1), and at six months (Post-2). The primary outcome will be self-efficacy in self-care. The secondary outcomes will include measures of burden of treatment, health-related quality of life and 30- and 90-day readmissions. Sub-study analyses are planned in the HF patient population with primary outcomes of self-care behaviour and secondary outcomes of medication adherence, and readmission at 30 days, 90 days and 6 months. Patients’ and nurse navigators’ engagement and experiences with the eHealth intervention and cost-effectiveness will be investigated. Data will be analysed according to intention-to-treat principles. Qualitative data will be analysed using thematic analysis.DiscussionThis protocol will examine the effects of the eHealth@ Hospital-2-Home intervention on self-care in two prevalent patient groups, HF and CRC. It will allow the exploration of a generic framework for an eHealth intervention after hospital discharge, which could be adapted to other patient groups, upscaled, and implemented into clinical practice.Trial registrationClinical trials.gov (ID 301472).

Health Professional Perspectives on Communication and Monitoring During Interfacility Neonatal Transport

Adverse events occur in a majority of pediatric critical care ambulance transports. For neonatal interfacility transports in particular, Medical Control Physicians overseeing the transfer are located remotely and must respond to referrals, updates, and questions over the phone. Technology options not currently utilized for neonatal interfacility transport may enhance communication and monitoring before and/or during transit. To identify the most beneficial new technologies, two activities were performed with the health professionals involved in transport: interviews and design workshops. The individual interviews focused on current processes and communication preferences. The design workshops brought together an interprofessional group of health professionals involved in transport to discuss an idealized state of transport and agree on priorities for the greatest needs to address. Health professionals agreed that the most desirable technologies enable remote vital sign monitoring, enable remote video visibility of the patient, and aid in the decision on where to send the patient.

Surgical High Dependency Admissions after Elective Laparoscopic Colorectal Resections: Is It Truly Necessary?

Surgical high dependency (SHD) allows for intermediate care provision between general ward (GW) and intensive care unit (ICU) for surgical patients but no universally accepted admission criteria exists. Unnecessary SHD admissions should be minimized to limit resource wastage and maintain spare critical care capacity. This study evaluates the utility of SHD admissions following elective laparoscopic colectomy by comparing post-operative outcomes and interventions performed between SHD and GW patients. A retrospective review of all colorectal cancer patients who underwent elective laparoscopic colectomy in our institution between January 2019 and December 2021 was conducted. Patients converted to open surgery or admitted to IC post-operatively were excluded. Peri-operative parameters and outcomes between patients admitted to GW and SHD post-operatively were evaluated. The cohort comprised 393 patients. There were 153 patients (38.93%) who required SHD admission. SHD patients had higher American Society of Anesthesiology (ASA) scores, body mass index, age and intra-operative blood loss. Majority of post-operative morbidity were minor (Clavien-Dindo II or lower) in both groups and the interventions required were safely instituted in both SHD and GW. None of the patients in the cohort required inotropic or ventilatory support in the SHD. GW patients were "healthier" but post-operative morbidity and interventions required were similar to the SHD group. Nonetheless, treatment delays, absence of continuous monitoring, and decreased nurse-to-patient ratio may be significant for patients with limited physiological reserves. Further studies should evaluate safety and cost-effectiveness of managing high risk surgical patients in GW using continuous remote vital signs monitoring.

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.

Satellite-Linked Remote Physiologic Monitoring During Simulated Rural Ground Ambulance and Rotor Wing Transports

Telemedicine and remote monitoring are rapidly gaining momentum in health care, including in-home and postdischarge monitoring. However, remote monitoring for telemedicine teams and receiving medical centers is yet to reach emergency medical services. When transporting a critically ill patient, continuous vital sign monitoring may be helpful to enhance receiving center collaboration and change care delivery before arrival when necessary. Our primary objective was to demonstrate successful transmission and reception of real-time physiologic summary data to a hospital base station during ambulance transport using a low-energy Bluetooth wireless wearable device linked to iridium satellite communications. We completed our proof-of-concept study on 2 simulated ground ambulance transports and 1 helicopter flight in rural areas surrounding Rochester, Minnesota. Each simulated transport used Mayo Clinic–developed wearable devices paired one-to-one with a physiologic communication kit. Electrocardiographic and photoplethysmographic waveforms were processed on the wearables every 5 minutes, with vital sign data generated and transmitted to an iridium satellite and relayed to a base station network–protected computer and mobile application with real-time display of summary and location. Data and geolocation were tracked in real time with a mobile application during the simulated transport, and summary data packets were saved on Mayo Clinic servers. During the 3 simulated rural transports, all (n=7; 100%) wearables successfully captured, recorded, and transmitted raw waveform physiologic signals. All devices transmitted successfully via the iridium satellite to the base station network–protected computer and mobile application. In all, 106 (69%) of 154 transmissions were successfully processed. Our project demonstrated successful remote monitoring of physiologic vital signs during transport in rural, low–cellular signal areas. The use of live remote monitoring should be explored to understand its utility in practice and outcomes.

РОЛЬ СУБЪЕКТИВНЫХ И ОБЪЕКТИВНЫХ КРИТЕРИЕВ В ОЦЕНКЕ СОСТОЯНИЯ БОЛЬНЫХ БРОНХООБСТРУКТИВНЫМИ ЗАБОЛЕВАНИЯМИ В УСЛОВИЯХ УДАЛЕННОГО МОНИТОРИНГА

Introduction. Wearable or home electronic devices with the function of transmitting information at a distance are used for the purpose of remote dynamic monitoring of the condition of patients. Aim. To determine the effectiveness of the use of "new" criteria for assessing the health status of patients with broncho-obstructive diseases in order to monitor remotely. Material and methods. 28 patients with broncho-obstructive diseases who were admitted for inpatient treatment were examined. Most of them had comorbidities, mainly cardiovascular pathology. A general clinical examination and special research methods were performed: an interactive survey using the respiratory module of the Electronic Polyclinic program, remote monitoring of vital signs using a smart watch and a mobile application for recording and transmitting information, a 6-minute walk test with simultaneous recording of vital signs with using a smart watch, a questionnaire and a scale for assessing the usability of the System usability scale system. The analysis of the results was performed by using the Statistica 13.0 software package. Results and discussion. Interactive survey corresponded to the severity of dyspnea according to the mMRC and Borg scales. The 6-minute walk test showed a significant limitation of physical activity and an increase in heart rate. The deep sleep phase has been limited. The CRP index averaged 7.78±8.48 µg/l. More than 85% of patients expressed their willingness to continue observation. The results of the correlation analysis demonstrated a direct relationship with the patient's physical activity assessment and the results of the 6-minute walk test, and an inverse relationship with the 6-minute walk test result and the patients' age, severity of respiratory failure and CRP concentration. The duration of deep sleep is inversely correlated with the SpO2 value. Our studies made it possible to compare the obtained data with the results of traditional methods of examining a patient, to confirm the position that the physical activity of a patient with broncho-obstructive disease is connected with indicators of the function of external respiration, and also that the total duration of sleep of COPD patients mainly consists of light sleep with a decrease in the duration of deep sleep. An inverse relationship was found with the duration of deep sleep and the concentration of CRP and the value of SpO2. The described monitoring system allows you to timely adjust the treatment regimen, reduce the number of hospitalizations, the risk of exacerbation or death.Conclusion. Additional instrumental control of vital parameters increases the efficiency of the system of long-term remote monitoring of patients with broncho-obstructive diseases. the indicators represent the severity of the symptoms of the disease and the degree of violations of the indicators of the function of external respiration.

Multimodal Remote Home Monitoring of Lung Transplant Recipients during COVID-19 Vaccinations: Usability Pilot Study of the COVIDA Desk Incorporating Wearable Devices.

Background and Objectives: Remote patient monitoring (RPM) of vital signs and symptoms for lung transplant recipients (LTRs) has become increasingly relevant in many situations. Nevertheless, RPM research integrating multisensory home monitoring in LTRs is scarce. We developed a novel multisensory home monitoring device and tested it in the context of COVID-19 vaccinations. We hypothesize that multisensory RPM and smartphone-based questionnaire feedback on signs and symptoms will be well accepted among LTRs. To assess the usability and acceptability of a remote monitoring system consisting of wearable devices, including home spirometry and a smartphone-based questionnaire application for symptom and vital sign monitoring using wearable devices, during the first and second SARS-CoV-2 vaccination. Materials and Methods: Observational usability pilot study for six weeks of home monitoring with the COVIDA Desk for LTRs. During the first week after the vaccination, intensive monitoring was performed by recording data on physical activity, spirometry, temperature, pulse oximetry and self-reported symptoms, signs and additional measurements. During the subsequent days, the number of monitoring assessments was reduced. LTRs reported on their perceptions of the usability of the monitoring device through a purpose-designed questionnaire. Results: Ten LTRs planning to receive the first COVID-19 vaccinations were recruited. For the intensive monitoring study phase, LTRs recorded symptoms, signs and additional measurements. The most frequent adverse events reported were local pain, fatigue, sleep disturbance and headache. The duration of these symptoms was 5-8 days post-vaccination. Adherence to the main monitoring devices was high. LTRs rated usability as high. The majority were willing to continue monitoring. Conclusions: The COVIDA Desk showed favorable technical performance and was well accepted by the LTRs during the vaccination phase of the pandemic. The feasibility of the RPM system deployment was proven by the rapid recruitment uptake, technical performance (i.e., low number of errors), favorable user experience questionnaires and detailed individual user feedback.

Digital Health Technologies for Post-Discharge Care after Heart Failure Hospitalisation to Relieve Symptoms and Improve Clinical Outcomes.

The prevention of recurrent heart failure (HF) hospitalisations is of particular importance, as each such successive event may increase the risk of death. Effective care planning during the vulnerable phase after discharge is crucial for symptom control and improving patient prognosis. Many clinical trials have focused on telemedicine interventions in HF, with varying effects on the primary endpoints. However, the evidence of the effectiveness of telemedicine solutions in cardiology is growing. The scope of this review is to present complementary telemedicine modalities that can support outpatient care of patients recently hospitalised due to worsening HF. Remote disease management models, such as video (tele) consultations, structured telephone support, and remote monitoring of vital signs, were presented as core components of telecare. Invasive and non-invasive monitoring of volume status was described as an important step forward to prevent congestion-the main cause of clinical decompensation. The idea of virtual wards, combining these facilities with in-person visits, strengthens the opportunity for education and enhancement to promote more intensive self-care. Electronic platforms provide coordination of tasks within multidisciplinary teams and structured data that can be effectively used to develop predictive algorithms based on advanced digital science, such as artificial intelligence. The rapid progress in informatics, telematics, and device technologies provides a wide range of possibilities for further development in this area. However, there are still existing gaps regarding the use of telemedicine solutions in HF patients, and future randomised telemedicine trials and real-life registries are still definitely needed.

Impact of remote vital sign monitoring on health outcomes in acute respiratory infection and exacerbation of chronic respiratory conditions: systematic review and meta-analysis.

Our aim was to investigate the effectiveness of virtual wards on health outcomes in patients with acute respiratory infection. We searched four electronic databases from January 2000 to March 2021 for randomised controlled trials (RCTs). We included studies in people with acute respiratory illness or an acute exacerbation of a chronic respiratory illness, where a patient or carer measured vital signs (oximetry, blood pressure, pulse) for initial diagnosis and/or asynchronous monitoring, in a person living in private housing or a care home. We performed random-effects meta-analysis for mortality. We reviewed 5834 abstracts and 107 full texts. Nine RCTs were judged to be relevant for inclusion, in which sample sizes ranged from 37 to 389 (total n=1627) and mean ages ranged between 61 and 77 years. Five were judged to be at low risk of bias. Five RCTs had fewer hospital admissions in the intervention (monitoring) group, out of which two studies reported a significant difference. Two studies reported more admissions in the intervention group, with one reporting a significant difference. We were unable to perform a meta-analysis on healthcare utilisation and hospitalisation data due to lack of outcome definition in the primary studies and variable outcome measurements. We judged two studies to be at low risk of bias. The pooled summary risk ratio for mortality was 0.90 (95% CI 0.55-1.48). The limited literature for remote monitoring of vital signs in acute respiratory illness provides weak evidence that these interventions have a variable impact on hospitalisations and healthcare utilisation, and may reduce mortality.

Innovating Healthcare IoT with a Secure Blockchain Consensus Algorithm based on Verifiable Random Ranking

The Internet of Things (IoT) is helping the healthcare industry innovate. Medical professionals are no longer confined to hospitals or physical locations. IoT devices are used in healthcare for remote monitoring of vital signs, transmission and reception of private data, and other similar applications. Protection from cyber threats is the most vital aspect of IoT device operation. Malicious activities result in the leakage of sensitive data and the malfunctioning of devices, which becomes a critical issue. As a result, it is now a serious endeavor to create effective solutions that can safeguard the data and record exchange networks of every IoT device. To address some critical issues with current consensus algorithms, this paper proposes the verifiable random ranking (VRR) based Secure Blockchain Consensus (SBC) mechanism. In place of conventional algorithms, we developed new techniques for managing active nodes and evaluating node reliability and robustness. Our experiments show that the VRR-SBC algorithm speeds up consensus, improves security, and reduces the price of verification. The results of the simulation demonstrate the usefulness of the blockchain era for limited devices and provide an opportunity to assess the scope of the consensus algorithm's applicability.

Assessment of Remote Vital Sign Monitoring and Alarms in a Real-World Healthcare at Home Dataset.

The importance of vital sign monitoring to detect deterioration increases during healthcare at home. Continuous monitoring with wearables increases assessment frequency but may create information overload for clinicians. The goal of this work was to demonstrate the impact of vital sign observation frequency and alarm settings on alarms in a real-world dataset. Vital signs were collected from 76 patients admitted to healthcare at home programs using the Current Health (CH) platform; its wearable continuously measured respiratory rate (RR), pulse rate (PR), and oxygen saturation (SpO2). Total alarms, alarm rate, patient rate, and detection time were calculated for three alarm rulesets to detect changes in SpO2, PR, and RR under four vital sign observation frequencies and four window sizes for the alarm algorithms' median filter. Total alarms ranged from 65 to 3113. The alarm rate and early detection increased with the observation frequency for all alarm rulesets. Median filter windows reduced alarms triggered by normal fluctuations in vital signs without compromising the granularity of time between assessments. Frequent assessments enabled with continuous monitoring support early intervention but need to pair with settings that balance sensitivity, specificity, clinical risk, and provider capacity to respond when a patient is home to minimize clinician burden.

Potential for remote vital sign monitoring to improve hospital patient sleep: A feasibility study

BackgroundEven low-acuity patients suffer from disrupted sleep in the hospital in part due to routine overnight vital sign (VS) checks. When invasive monitoring is not needed, vital sign monitoring devices (VSMDs) similar to consumer-grade health monitors may play a role in promoting sleep, which can aid healing and recovery. MethodsWe provided one VSMD to neuroscience ward patients during their hospital stays and used surveys to assess patient and nurse attitudes toward the device and the impact of the device on patient comfort. We also compared VSMD-streamed vS data to nurse-recorded vS data in the chart to evaluate the consistency of data streaming and data concordance between the device and nurse-collected vital sign values. Findings21 patients and 15 nurses enrolled. Overall, patients and nurses responded positively to the device and patients preferred wearing the device to receiving manual vital checks overnight. The most common device-related cause of sleep disruption per patients was device weight (29%). Device vS were concordant with nurse vS on average but there was significant variance in agreement between nurse and device values. InterpretationPatients and nurses feel positively about the use of VSMDs and their use in the hospital. The device we tested may be limited in its sleep promotion by its weight and patient comfort assessment. Further research is needed to assess the precision of the device in measuring vital signs when used in a clinical setting. Future studies should compare VSMD models and assess their impacts on patient sleep in the absence of manual vS checks overnight. FundingFunding provided by the Sara & Evan Williams Foundation Endowed Neurohospitalist Chair at UCSF.