Remote Monitoring Of Vital Signs Research Articles

Layered Architecture for Internet of Things-based Healthcare System: A Systematic Literature Review

Internet of Things (IoT), known as a new paradigm, has shown to have a significant role in healthcare domains including remote vital sign monitoring systems, physical activity tracking, early disease diagnosis, and prevention of disease risks. Therefore, designing an integrated healthcare system based on Internet of Things is highly dependent on designing a layered architecture pattern. However, there are no comprehensive studies on Internet of Things layered architecture in the healthcare industry. The purpose of this study was to identify and scrutinize different types of layered architecture of Internet of Things in healthcare in terms of functions, and technologies. We evaluated studies proposing layered architecture of Internet of Things based on security aspects (security requirements and solutions). A systematic literature review was conducted by searching IEEE, PubMed, Scopus and Web of Science between 2005 and 2019. We were able to find 47 academic studies based on inclusion and exclusion criteria. We systematically reviewed applied functions and technologies and categorized them into three main layers namely, the perception, network, and application layers. This study also presented a comprehensive classification of sensor types. Only 28 out of 47 studies proposing Internet of Things architecture addressed security aspects among which privacy, authentication, and access control, confidentiality, and integrity had the highest rank. The layered architecture of Internet of Things is needed to provide an integrated framework for healthcare system, make better communication, and enhance the information management process. We suggest several potential solutions for future research directions according to technical, management, and security challenges

Home monitoring of vital signs and generation of alerts in a cohort of people living with dementia

AbstractBackgroundPeople with dementia (PwD) are at increased risk of adverse medical events (e.g. infections and falls). These often cause clinical deterioration, and potentially preventable admissions. Remote home monitoring of vital signs using internet‐of‐things technology can identify risk factors for these events – something particular pertinent during the COVID‐19 pandemic. We present data from an on‐going UK Dementia Research Institute and Technology Integrated Health Management (DRI‐TIHM) project. We aim to define algorithms that generate automated alerts, like the hospital‐based NEWS system (Morgan, 1997, Clin Intensive Car), and provide more proactive care for PwD.MethodPwD recorded their systolic/diastolic blood pressure (SBP/DBP), heart rate (HR), temperature (BTM), bodyweight (BW) and oxygen saturation (Sats) daily (figure 1) and data were collected centrally. A ‘monitoring team’ followed algorithms in response to alerts and advised medical attention if required. Events such as infections, were logged and correlated with the data. The dataset was then used to calculate the number of alerts that would have been raised if different thresholds were used.Result52 PwD living at home were included. Patients had a range of dementia diagnoses, most commonly Alzheimer’s disease. In total, 89,894 measurements were collected over 556 days (figure 2). During the pandemic, a sub‐group were given Sats probes and these produced a significant number of false positive results (figure 4f). On sub‐group analysis, PwD with Parkinson’s disease dementia had significantly lower SBP and DBP (p=0.004 and p=0.01 respectively, Mann‐Whitney U) (figure 3a), one of whom suffered from repeated falls (figure 3b).Pilot data were used to set alert thresholds. Average values and number of alerts for each domain are shown (table 1). We then modelled the effect of different thresholds, based on NEWS, to the number of alerts generated (figure 4, table 2). This is informative in optimising sensitivity and specificity of alerts whilst considering the burden on the monitoring service.ConclusionRemote monitoring can be implemented for PwD. These data can be used to generate clinical alerts that may signify adverse medical outcomes. The thresholds need to be adjusted to optimise efficiency in the context of varying reliability of home monitoring devices.

Remote Monitoring of Patient Respiration with Mask Attachment—A Pragmatic Solution for Medical Facilities

Remote monitoring of vital signs in infectious patients minimizes the risks of viral transmissions to healthcare professionals. Donning face masks could reduce the risk of viral transmissions and is currently practiced in medical facilities. An acoustic-sensing device was attached to face masks to assist medical facilities in remotely monitoring patients’ respiration rate and wheeze occurrence. Usability and functionality studies of the modified face mask were evaluated on 16 healthy participants. Participants were blindfolded throughout the data collection process. Respiratory rates of the participants were evaluated for one minute. The wheeze detection algorithm was assessed by playing 176 wheezes and 176 normal breaths through a foam mannequin. No discomfort was reported from the participants who used the modified mask. The mean error of respiratory rate was found to be 2.0 ± 1.3 breath per minute. The overall accuracy of the wheeze detection algorithm was 91.9%. The microphone sensor that was first designed to be chest-worn has been proven versatile to be adopted as a mask attachment. The current findings support and suggest the use of the proposed mask attachment in medical facilities. This application can be especially helpful in managing a sudden influx of patients in the face of a pandemic.

Continuous Remote Patient Monitoring Shows Early Cardiovascular Changes in COVID-19 Patients.

COVID-19 exerts deleterious cardiopulmonary effects, leading to a worse prognosis in the most affected. This retrospective multi-center observational cohort study aimed to analyze the trajectories of key vitals amongst hospitalized COVID-19 patients using a chest-patch wearable providing continuous remote patient monitoring of numerous vital signs. The study was conducted in five COVID-19 isolation units. A total of 492 COVID-19 patients were included in the final analysis. Physiological parameters were measured every 15 min. More than 3 million measurements were collected including heart rate, systolic and diastolic blood pressure, cardiac output, cardiac index, systemic vascular resistance, respiratory rate, blood oxygen saturation, and body temperature. Cardiovascular deterioration appeared early after admission and in parallel with changes in the respiratory parameters, showing a significant difference in trajectories within sub-populations at high risk. Early detection of cardiovascular deterioration of COVID-19 patients is achievable when using frequent remote patient monitoring.

Remote vital signs data monitoring during home blood transfusion: A pilot study.

Background and aimsOur study aimed to establish safer methods to manage home blood transfusion by using a remote vital signs data monitoring system. Home care is administered for patients with various medical disorders; however, home blood transfusion remains challenging owing to the risk of transfusion‐related complications.MethodsWe set up a remote vital signs data monitoring system to improve the safety of home blood transfusions. Using an Internet‐based vital signs data monitoring system, the heart rate, electrocardiography, respiration rate, and percutaneous oxygen saturation (SpO2) were monitored and recorded during the entire home transfusion period.ResultsTen transfusions in three patients were monitored; two of the patients had an abnormality in a single vital sign (decreased SpO2 decrease and increased respiratory rate); these were not transfusion‐related complications. Vital sign anomalies also occur because of errors in using the measurement device and noise associated with body movements. The presence of abnormalities in at least two vital signs among SpO2 decrease, tachycardia, and increased respiratory rate that persisted for >5 minutes was defined as a complicated vital sign abnormality (CVSA). There were no severe transfusion‐related complications with CVSA in the present study.ConclusionThis study indicates the feasibility and sustainability of real‐time remote monitoring of vital signs for the safety of home transfusion. Although CVSA may function as an indicator of severe transfusion‐related complications, these findings need to be confirmed with further studies.

Telemedicine for Anesthesiologists.

Telemedicine represents an area of rapid growth in anesthesiology. Remote preoperative evaluation is associated with high patient and physician satisfaction scores, reduced patient travel and wait times, and similar procedure cancellation rates compared with in-person clinic evaluation. Preoperative tele-evaluation has facilitated a return to normal function during the coronavirus disease 2019 (COVID-19) pandemic. Intraoperatively, remote vital sign monitoring and telecommunications technology combined with a care team model allows provision of expert care in areas experiencing a shortage of anesthesiologists. Virtual intensive care units provide overflow capability for postoperative patients, whereas patient smartphones can reduce the need for in-person evaluation.

For patients with heart failure, does remote monitoring of vital signs prevent hospital admissions?

For patients with heart failure, does remote monitoring of vital signs prevent hospital admissions?

TELECOVID: Remote Vital Signs Monitoring of COVID-19 Risk Patients in Home Isolation With an In-Ear Wearable

The TELECOVID study (https://www.telecovid.de) is designed to remotely monitor the physiological health status of COVID-19 positive-risk patients in home isolation. Key vital parameters are measured day and night using an in-ear biosensor technology. These data are streamed to the clinic in real time to enable timely interaction in case of deterioration.

AI-enabled remote monitoring of vital signs for COVID-19: methods, prospects and challenges

The COVID-19 pandemic has overwhelmed the existing healthcare infrastructure in many parts of the world. Healthcare professionals are not only over-burdened but also at a high risk of nosocomial transmission from COVID-19 patients. Screening and monitoring the health of a large number of susceptible or infected individuals is a challenging task. Although professional medical attention and hospitalization are necessary for high-risk COVID-19 patients, home isolation is an effective strategy for low and medium risk patients as well as for those who are at risk of infection and have been quarantined. However, this necessitates effective techniques for remotely monitoring the patients’ symptoms. Recent advances in Machine Learning (ML) and Deep Learning (DL) have strengthened the power of imaging techniques and can be used to remotely perform several tasks that previously required the physical presence of a medical professional. In this work, we study the prospects of vital signs monitoring for COVID-19 infected as well as quarantined individuals by using DL and image/signal-processing techniques, many of which can be deployed using simple cameras and sensors available on a smartphone or a personal computer, without the need of specialized equipment. We demonstrate the potential of ML-enabled workflows for several vital signs such as heart and respiratory rates, cough, blood pressure, and oxygen saturation. We also discuss the challenges involved in implementing ML-enabled techniques.

Remote Vital Sign Monitoring in Accidents

Remote Vital Sign Monitoring in Accidents

Fabry–Perot Beam Scanning Antenna for Remote Vital Sign Detection at 60 GHz

A beam scanning Fabry-Perot leaky-wave antenna (LWA) is designed at 60 GHz-band for single tone continuous-wave Doppler radar (DR)-based remote vital sign monitoring (RVSM) in a dynamic environment. A brief analysis is presented on antenna requirements for the DR in a typical dynamic scenario where a continuous RVSM is desired of a patient during sleep. The antenna is designed based on the drawn requirements with sufficiently high gain (>18 dBi) and wide beam scanning (12°) over the operating frequency band (62-65 GHz) for accurate RVSM up to 3 m distance. The patient under continuous health monitoring has a flexibility to change his/her position within 1 m angular distance from the fixed sensor position. Detailed RVSM measurements have been carried out with the proposed antenna system at 2 m and 3 m distances from the subject to verify the designed antenna's suitability for dynamic RVSM application. It has been shown that both the breathing rate (BR) and heartbeat rate (HR) can be successfully detected within 20° of the angular range by tuning the operating frequency from 62 to 65 GHz.

Can continuous remote vital sign monitoring reduce the number of room visits to patients suspected of COVID-19: A quasi-experimental study

BackgroundContinuous remote monitoring of vital signs on the hospital ward gained popularity during the Severe Acute Respiratory Syndrome coronavirus 2 pandemic due to its ability to support early detection of respiratory failure, and the possibility to do so without physical contact between patient and clinician. The effect of continuous monitoring on patient room visits has not been established yet. ObjectivesTo assess the impact of continuous monitoring on the number of patient room visits for patients suspected of Corona Virus Disease 2019 (COVID-19) and the use of personal protection equipment. Design and methodsWe performed a before-after study at a ward with private rooms for patients suspected of COVID-19 at a tertiary hospital in Nijmegen, The Netherlands. Non-participant observers observed hospital staff during day, evening and night shifts to record patient room visits and personal protection equipment usage. After eleven days, wearable continuous vital sign monitoring was introduced. An interrupted time series analysis was applied to evaluate the effect of continuous monitoring on the number of patient room visits, visits for obtaining vital signs (Modified Early Warning Score visits) and the amount of personal protection equipment used. ResultsDuring the 45 day study period, 86 shifts were observed. During each shift, approximately six rooms were included. A total of 2347 patient room visits were recorded. The slope coefficient for the number of patient room visits did not change after introducing continuous vital sign monitoring (B -0.003, 95% confidence interval -0.022/0.016). The slope coefficients of the number of Modified Early Warning Score visits and the amount of personal protection equipment used did not change either (B -0.002, 95% confidence interval -0.021/0.017 and B 0.046, 95% confidence interval -0.008/0.099). The number of Modified Early Warning Score visits did show a decline over the entire study period, however this decline was not influenced by the intervention. Evening and night shifts were associated with fewer patient room visits compared to day shifts. ConclusionIntroduction of continuous vital sign monitoring at a general ward for patients with suspected COVID-19 did not reduce the number of patient room visits or the usage of personal protection equipment by hospital staff. The number of Modified Early Warning Score visits declined over time, but this was not related to the introduction of continuous monitoring. Detailed analysis of the influence of continuous monitoring on the workflow of hospital staff reveals key points to increase efficacy of this intervention.

Artificial Intelligence-enabled Wearable Medical Devices, Clinical and Diagnostic Decision Support Systems, and Internet of Things-based Healthcare Applications in COVID-19 Prevention, Screening, and Treatment

Building our argument by drawing on data collected from Accenture, GlobalWebIndex, GoMo Health, KPMG, McKinsey, Oracle, Sermo, STAT, Statista, and Workplace Intelligence, we performed analyses and made estimates regarding how predictive big data analytics, body sensor networks, medical wearable devices, decision support systems, and wireless sensing applications can be harnessed in real-time continuous remote monitoring of patients vital signs configuring clinical data in pervasive mobile patient-centric healthcare. Introduction The extensive data of COVID-19 patients can be assimilated and inspected by cutting-edge machine learning algorithms to grasp the pattern of viral transmission, optimize diagnostic swiftness and precision, advance adequate therapeutic methods, and identify the most vulnerable individuals according to personalized genetic and physiological features. Methodology and Empirical Analysis Building our argument by drawing on data collected from Accenture, Global-WebIndex, GoMo Health, KPMG, McKinsey, Oracle, Sermo, STAT, Statista, and Workplace Intelligence, we performed analyses and made estimates regarding how predictive big data analytics, body sensor networks, medical wearable devices, decision support systems, and wireless sensing applications can be harnessed in real-time continuous remote monitoring of patients' vital signs configuring clinical data in pervasive mobile patient-centric healthcare. Study Design, Survey Methods, and Materials The interviews were conducted online and data were weighted by five variables (age, race/ethnicity, gender, education, and geographic region) using the Census Bureau's American Community Survey to reflect reliably and accurately the demographic composition of the United States.

Data-Centric Load and QoS-Aware Body-to-Body Network Routing Protocol for Mass Casualty Incident

Triage is the most important requirement of Mass Casualty Incident (MCI) where monitoring the vital signs of casualty is the crucial aspect to assess the severity of their current medical conditions. One of the most significant challenges in the triage center is to provide effective remote monitoring of vital signs of mass casualties. To overcome this challenge, there is a necessity to design a dynamic routing protocol that supports data-centric quality parameters such as delay and reliability as well network-specific quality parameters such as throughput and network lifetime over an ad hoc network. The proposed protocol handles data-centric quality parameters by jointly considering the link and node cost of the neighboring nodes. Further, the protocol handles network-specific quality parameters by including load distribution along with buffer management based on the medical condition of the casualties and beaconless routing mechanism. Furthermore, the proposed approach focuses on the transmission of vital signs of critical casualties while also avoiding network congestion and extending network lifespan. The experimentation results show that the proposed protocol is efficient in handling end-to-end delay, the packet transmission ratio of the critical casualties vital signs as compared to the existing state-of-the-art approaches.

Chronic disease management in heart failure: focus on telemedicine and remote monitoring.

In the context of the COVID-19 pandemic, many barriers to telemedicine disappeared. Virtual visits and telemonitoring strategies became routine. Evidence is accumulating regarding the safety and efficacy of virtual visits to replace in-person visits. A structured approach to virtual encounters is recommended. Telemonitoring includes patient reported remote vital sign monitoring, information from wearable devices, cardiac implantable electronic devices and invasive remote hemodynamic monitoring. The intensity of the monitoring should match the risk profile of the patient. Attention to cultural and educational barriers is important to prevent disparities in telehealth implementation.

Wireless Remote Home Monitoring of Vital Signs in Patients Discharged Early After Esophagectomy: Observational Feasibility Study.

BackgroundHospital stays after major surgery are shorter than ever before. Although enhanced recovery and early discharge have many benefits, some complications will now first manifest themselves in home settings. Remote patient monitoring with wearable sensors in the first days after hospital discharge may capture clinical deterioration earlier but is largely uncharted territory.ObjectiveThis study aimed to assess the technical feasibility of patients, discharged after esophagectomy, being remotely monitored at home with a wireless patch sensor and the experiences of these patients. In addition, we determined whether observing vital signs with a wireless patch sensor influences clinical decision making.MethodsIn an observational feasibility study, vital signs of patients were monitored with a wearable patch sensor (VitalPatch, VitalConnect Inc) during the first 7 days at home after esophagectomy and discharge from hospital. Vital signs trends were shared with the surgical team once a day, and they were asked to check the patient’s condition by phone each morning. Patient experiences were evaluated with a questionnaire, and technical feasibility was analyzed on a daily basis as the percentage of data loss and gap durations. In addition, the number of patients for whom a change in clinical decision was made based on the results of remote vital signs monitoring at home was assessed.ResultsPatients (N=20) completed 7 days each of home monitoring with the wearable patch sensor. Each of the patients had good recovery at home, and remotely observed vital signs trends did not alter clinical decision making. Patients appreciated that surgeons checked their vital signs daily (mean 4.4/5) and were happy to be called by the surgical team each day (mean 4.5/5). Wearability of the patch was high (mean 4.4/5), and no reports of skin irritation were mentioned. Overall data loss of vital signs measurements at home was 25%; both data loss and gap duration varied considerably among patients.ConclusionsRemote monitoring of vital signs combined with telephone support from the surgical team was feasible and well perceived by all patients. Future studies need to evaluate the impact of home monitoring on patient outcome as well as the cost-effectiveness of this new approach.

EHealth in transplantation.

eHealth ("electronic" Health) is a new field in medicine that has the potential to change medical care, increase efficiency, and reduce costs. In this review, we analyzed the current status of eHealth in transplantation by performing a PubMed search over the last 5years with a focus on clinical studies for post-transplant care. We retrieved 463 manuscripts, of which 52 clinical reports and eight randomized controlled trials were identified. Most studies were on kidney (n=19), followed by liver (n=10), solid organ (n=7), bone-marrow (n=6), and lung transplantation (n=6). Eleven articles included adolescents/children. Investigated eHealth features covered the whole spectrum with mobile applications for patients (n=24) and video consultations (n=18) being most frequent. Prominent topics for patient apps were self-management (n=16), adherence (n=14), symptom-reporting (11), remote monitoring of vital signs (n=8), educational (n=7), and drug reminder (n=7). In this review, we discuss opportunities and strengths of such new eHealth solutions, the implications for successful implementation into the healthcare process, the human factor, data protection, and finally, the need for better evidence from prospective clinical trials in order to confirm the claims on better patient care, potential efficiency gains and cost savings.

Vital Sign Monitoring Using FMCW Radar in Various Sleeping Scenarios.

Remote monitoring of vital signs for studying sleep is a user-friendly alternative to monitoring with sensors attached to the skin. For instance, remote monitoring can allow unconstrained movement during sleep, whereas detectors requiring a physical contact may detach and interrupt the measurement and affect sleep itself. This study evaluates the performance of a cost-effective frequency modulated continuous wave (FMCW) radar in remote monitoring of heart rate and respiration in scenarios resembling a set of normal and abnormal physiological conditions during sleep. We evaluate the vital signs of ten subjects in different lying positions during various tasks. Specifically, we aim for a broad range of both heart and respiration rates to replicate various real-life scenarios and to test the robustness of the selected vital sign extraction methods consisting of fast Fourier transform based cepstral and autocorrelation analyses. As compared to the reference signals obtained using Embla titanium, a certified medical device, we achieved an overall relative mean absolute error of % (86% correlation) and % (91% correlation) for the heart rate and respiration rate, respectively. Our results promote radar-based clinical monitoring by showing that the proposed radar technology and signal processing methods accurately capture even such alarming vital signs as minimal respiration. Furthermore, we show that common parameters for heart rate variability can also be accurately extracted from the radar signal, enabling further sleep analyses.

Evidence and Recommendations on the Use of Telemedicine for the Management of Arterial Hypertension: An International Expert Position Paper.

Telemedicine allows the remote exchange of medical data between patients and healthcare professionals. It is used to increase patients' access to care and provide effective healthcare services at a distance. During the recent coronavirus disease 2019 (COVID-19) pandemic, telemedicine has thrived and emerged worldwide as an indispensable resource to improve the management of isolated patients due to lockdown or shielding, including those with hypertension. The best proposed healthcare model for telemedicine in hypertension management should include remote monitoring and transmission of vital signs (notably blood pressure) and medication adherence plus education on lifestyle and risk factors, with video consultation as an option. The use of mixed automated feedback services with supervision of a multidisciplinary clinical team (physician, nurse, or pharmacist) is the ideal approach. The indications include screening for suspected hypertension, management of older adults, medically underserved people, high-risk hypertensive patients, patients with multiple diseases, and those isolated due to pandemics or national emergencies.

A UHF/UWB Hybrid RFID Tag With a 51-m Energy-Harvesting Sensitivity for Remote Vital-Sign Monitoring.

A novel ultra-high frequency (UHF)/ultra-wideband (UWB) hybrid RFID tag is reported for object-specific remote vital-sign monitoring application. The tag achieves a record energy-harvesting sensitivity at UHF band by codesigning a meander dipole antenna and a passive rectifier. The especially high quality-factor makes the frontend sensitive to near-field motions such as heartbeats and respiration in a wearable setting. The custom CMOS IC of approximately 1-μW power consumption builds around a low-power UWB transmitter and converts variations of the supply voltage to the impulse repetition rate. The tag consisting of the IC and UHF/UWB antennas requires no other discrete components and features a size of 4.2 cm × 2.9 cm and a weight of 0.93 g. A long-distance experiment verifies that the tag can be wirelessly powered up at 51 meters from a 4-W equivalent-isotropic-radiation-power (EIRP) UHF transmitter. Remote vital-sign monitoring is validated on a human subject, in which the UHF power source is placed 2 meters away from the subject with a power emission of less than 20 dBm. This work proposes a first-of-its-kind remote vital-sign monitoring scheme based on a noncontact wearable tag. The design of the far-field energy-harvesting frontend with a record sensitivity serves as a reference for future works on battery-free remote sensors.