scholarly journals Remote Arrhythmia Detection for Eldercare in Malaysia

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8197
Author(s):  
Kevin Thomas Chew ◽  
Valliappan Raman ◽  
Patrick Hang Hui Then
Keyword(s):  
Classification Scheme ◽  
Vital Signs ◽  
Modern Society ◽  
Two Phase ◽  
Detection Rates ◽  
Arrhythmia Detection ◽  
Elderly Individuals ◽  
Phase Classification ◽  
Cause Of Deaths ◽  
Remote Patient

Cardiovascular disease continues to be one of the most prevalent medical conditions in modern society, especially among elderly citizens. As the leading cause of deaths worldwide, further improvements to the early detection and prevention of these cardiovascular diseases is of the utmost importance for reducing the death toll. In particular, the remote and continuous monitoring of vital signs such as electrocardiograms are critical for improving the detection rates and speed of abnormalities while improving accessibility for elderly individuals. In this paper, we consider the design and deployment characteristics of a remote patient monitoring system for arrhythmia detection in elderly individuals. Thus, we developed a scalable system architecture to support remote streaming of ECG signals at near real-time. Additionally, a two-phase classification scheme is proposed to improve the performance of existing ECG classification algorithms. A prototype of the system was deployed at the Sarawak General Hospital, remotely collecting data from 27 unique patients. Evaluations indicate that the two-phase classification scheme improves algorithm performance when applied to the MIT-BIH Arrhythmia Database and the remotely collected single-lead ECG recordings.

IoT based e-Healthcare System to Enable Remote Patient Care based on Cloud Server

2017 ◽  
Vol 7 (7) ◽  
pp. 36
Author(s):  
P.Venu Gopala Rao ◽  
Eslavath Raja ◽  
Ramakrishna Gandi ◽  
G. Ravi Kumar
Keyword(s):  
Low Cost ◽  
Vital Signs ◽  
Smart Phone ◽  
Medical Professional ◽  
Design Parameters ◽  
Cloud Server ◽  
Significant Area ◽  
Efficient Data ◽  
System Data ◽  
Remote Patient

IoT (Internet of Things) has become most significant area of research to design an efficient data enabled services with the help of sensors. In this paper, a low-cost system design for e-healthcare service to process the sensitive health data is presented. Vital signs of the human body are measured from the patient location and shared with a registered medical professional for consultation. Temperature and heart rate are the major signals obtained from a patient for the initial build of the system. Data is sent to a cloud server where processing and analysis is provided for the medical professional to analyze. Secure transmission and dissemination of data through the cloud server is provided with an authentication system and the patient could be able to track his data through a smart phone on connecting to the cloud server. A prototype of the system along with its design parameters has been discussed.

Implementing Internet of Things in a Remote Patient Medical Monitoring System

2018 ◽  
Vol 6 (8) ◽  
pp. 159 ◽  
Author(s):  
Ifeoma V. Ngonadi
Keyword(s):  
Internet Of Things ◽  
Monitoring System ◽  
Medical Records ◽  
Research Work ◽  
Healthcare Delivery ◽  
Vital Signs ◽  
Personal Digital Assistant ◽  
Computer Applications ◽  
Medical Monitoring ◽  
Remote Patient

The Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. Remote patient monitoring enables the monitoring of patients’ vital signs outside the conventional clinical settings which may increase access to care and decrease healthcare delivery costs. This paper focuses on implementing internet of things in a remote patient medical monitoring system. This was achieved by writing two computer applications in java in which one simulates a mobile phone called the Intelligent Personal Digital Assistant (IPDA) which uses a data structure that includes age, smoking habits and alcohol intake to simulate readings for blood pressure, pulse rate and mean arterial pressure continuously every twenty five which it sends to the server. The second java application protects the patients’ medical records as they travel through the networks by employing a symmetric key encryption algorithm which encrypts the patients’ medical records as they are generated and can only be decrypted in the server only by authorized personnel. The result of this research work is the implementation of internet of things in a remote patient medical monitoring system where patients’ vital signs are generated and transferred to the server continuously without human intervention.

scholarly journals Remote Patient Monitoring Using Radio Frequency Identification (RFID) Technology and Machine Learning for Early Detection of Suicidal Behaviour in Mental Health Facilities

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 776
Author(s):  
Xiaohui Tao ◽  
Thanveer Basha Shaik ◽  
Niall Higgins ◽  
Raj Gururajan ◽  
Xujuan Zhou
Keyword(s):  
Mental Health ◽  
Machine Learning ◽  
Radio Frequency Identification ◽  
Patient Monitoring ◽  
Vital Signs ◽  
Remote Patient Monitoring ◽  
Rfid Technology ◽  
Rpm System ◽  
Frequency Identification ◽  
Remote Patient

Remote Patient Monitoring (RPM) has gained great popularity with an aim to measure vital signs and gain patient related information in clinics. RPM can be achieved with noninvasive digital technology without hindering a patient’s daily activities and can enhance the efficiency of healthcare delivery in acute clinical settings. In this study, an RPM system was built using radio frequency identification (RFID) technology for early detection of suicidal behaviour in a hospital-based mental health facility. A range of machine learning models such as Linear Regression, Decision Tree, Random Forest, and XGBoost were investigated to help determine the optimum fixed positions of RFID reader–antennas in a simulated hospital ward. Empirical experiments showed that Decision Tree had the best performance compared to Random Forest and XGBoost models. An Ensemble Learning model was also developed, took advantage of these machine learning models based on their individual performance. The research set a path to analyse dynamic moving RFID tags and builds an RPM system to help retrieve patient vital signs such as heart rate, pulse rate, respiration rate and subtle motions to make this research state-of-the-art in terms of managing acute suicidal and self-harm behaviour in a mental health ward.

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

2021 ◽  
Vol 10 (18) ◽  
pp. 4218
Author(s):  
Arik Eisenkraft ◽  
Yasmin Maor ◽  
Keren Constantini ◽  
Nir Goldstein ◽  
Dean Nachman ◽  
...  
Keyword(s):  
Patient Monitoring ◽  
Vital Signs ◽  
Final Analysis ◽  
Remote Patient Monitoring ◽  
Blood Oxygen Saturation ◽  
Respiratory Parameters ◽  
Significant Difference ◽  
Observational Cohort ◽  
Remote Patient ◽  
Worse Prognosis

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.

scholarly journals Remote Blood Pressure Monitoring With a Wearable Photoplethysmographic Device (Senbiosys): Protocol for a Single-Center Prospective Clinical Trial (Preprint)

2021 ◽  
Author(s):  
Sara Schukraft ◽  
Assim Boukhayma ◽  
Stéphane Cook ◽  
Antonino Caizzone
Keyword(s):  
Blood Pressure ◽  
Blood Pressure Monitoring ◽  
Prospective Trial ◽  
Vital Signs ◽  
Adult Patients ◽  
Arterial Catheter ◽  
Single Center ◽  
New Device ◽  
Remote Patient ◽  
User Friendly

BACKGROUND Wearable devices can provide user-friendly, accurate, and continuous blood pressure (BP) monitoring to assess patients’ vital signs and achieve remote patient management. Remote BP monitoring can substantially improve BP control. The newest cuffless BP monitoring devices have emerged in patient care using photoplethysmography. OBJECTIVE The Senbiosys trial aims to compare BP measurements of a new device capturing a photoplethysmography signal on the finger versus invasive measurements performed in patients with an arterial catheter in the intensive care unit (ICU) or referred for a coronarography at the Hospital of Fribourg. METHODS The Senbiosys study is a single-center, single-arm, prospective trial. The study population consists of adult patients undergoing coronarography or patients in the ICU with an arterial catheter in place. This study will enroll 35 adult patients, including 25 patients addressed for a coronarography and 10 patients in the ICU. The primary outcome is the assessment of mean bias (95% CI) for systolic BP, diastolic BP, and mean BP between noninvasive and invasive BP measurements. Secondary outcomes include a reliability index (Qualification Index) for BP epochs and count of qualified epochs. RESULTS Patient recruitment started in June 2021. Results are expected to be published by December 2021. CONCLUSIONS The findings of the Senbiosys trial are expected to improve remote BP monitoring. The diagnosis and treatment of hypertension should benefit from these advancements. CLINICALTRIAL ClinicalTrials.gov NCT04379986; https://clinicaltrials.gov/ct2/show/NCT04379986 INTERNATIONAL REGISTERED REPORT PRR1-10.2196/30051

Low-power radio telemetry: the potential for remote patient monitoring

1996 ◽  
Vol 2 (4) ◽  
pp. 185-191 ◽  
Author(s):  
W G Scanlon ◽  
N E Evans ◽  
G C Crumley ◽  
Z M Mccreesh
Keyword(s):  
Patient Monitoring ◽  
Radio Telemetry ◽  
Vital Signs ◽  
Clinical Results ◽  
Full Duplex ◽  
Remote Patient Monitoring ◽  
Monitoring Equipment ◽  
Future Developments ◽  
Remote Patient

Radio-based signalling devices will play an important role in future generations of remote patient monitoring equipment, both at home and in hospital. Ultimately, it will be possible to sample vital signs from patients, whatever their location and without them necessarily being aware that a measurement is being taken. This paper reviews current methods for the transmission by radio of physiological parameters over ranges of 0.3, 3 and 30 m, and describes the radiofrequency hardware required and the carrier frequencies commonly used. Future developments, including full duplex systems and the use of more advanced modulation schemes, are described. The paper concludes with a case study of a human temperature telemeter built to indicate ovulation. Clinical results clearly show the advantage to be had in adopting radio biotelemetry in this instance.

Sensing of Vital Signs and Transmission Using Wireless Networks

2010 ◽  
pp. 180-207
Author(s):  
Yousef Jasemian
Keyword(s):  
Health System ◽  
Vital Signs ◽  
Healthcare Personnel ◽  
Mobile Healthcare ◽  
Individualized Care ◽  
Patient Monitoring System ◽  
Remote Patient ◽  
User Friendly ◽  
Monitoring Devices

People living with chronic medical conditions, or with conditions requiring short term monitoring, need regular and individualized care to maintain their normal lifestyles. Mobile healthcare is a solution for providing patients’ mobility while their health is being monitored. Existing studies show that mobile healthcare can bring significant economic savings, improve the quality of care, and consequently the patient’s quality of life. However, despite all progresses in advanced information and telecommunication technologies, there are still very few functioning commercial wireless mobile monitoring devices present on the market, which most work off-line, are not proper for m-health services and there are still many issues to be dealt with. This chapter deals with a comprehensive investigation of feasibility of wireless and cellular telecommunication technologies and services in a real-time m-health system. The chapter bases its investigation, results, discussion and argumentation on an already developed remote patient monitoring system by the author. The implemented m-health system has been evaluated and validated by a number of well defined tests and experiments. The designed and implemented system fulfils the requirements. The suggested system is reliable, functions with a clinically acceptable performance, and transfers medical data with a reasonable quality, even though the system was tested under totally uncontrolled circumstances during the patients’ daily activities. Both the patients and the involved healthcare personnel expressed their confidence in using it. It is concluded that the system is applicable in clinical setup, and might be generalized in clinical practice. Finally, the chapter suggests improvement approaches for more reliable, more secure, more user-friendly and higher performance of an m-health system in future.

scholarly journals A Review on Wearable and Contactless Sensing for COVID-19 With Policy Challenges

2021 ◽  
Vol 2 ◽  
Author(s):  
Sagar Suresh Kumar ◽  
Kia Dashtipour ◽  
Qammer H. Abbasi ◽  
Muhammad A. Imran ◽  
Wasim Ahmad
Keyword(s):  
Patient Monitoring ◽  
Vital Signs ◽  
Risk Groups ◽  
Developed Countries ◽  
Cross Infection ◽  
Remote Patient Monitoring ◽  
Healthcare Facilities ◽  
Emergency Situations ◽  
The Us ◽  
Remote Patient

The COVID-19 pandemic has affected more than 100 million people worldwide, with around 500,000 cases reported daily. This has led to the overwhelming of healthcare systems even in developed countries such as the US, UK, etc. Remote monitoring of COVID-19 patients with non-serious symptoms can help reduce the burden on healthcare facilities and make them available for high risk groups and the seriously affected. The pandemic has accelerated the demand for the remote patient monitoring (RPM) technologies, and the market is expected to reach 2.14 billion in 2027 from the value of 786.4 million in 2019. In RPM programs, there are two types of sensors that can be used: wearable and contactless. The former, which is currently more widely used, is not only more obtrusive and uncomfortable, but can also lead to cross-infection through patient contact. These two types of technologies are discussed and compared for each vital sign. In the respiratory system, the vital signs are the respiratory rate (RR) and oxygen saturation (SpO2), while for the latter, they are the heart rate/rhythm and the blood pressure (BP). Then, the discussion is broadened to policy level changes needed to expedite the use of such technologies for remote patient monitoring (RPM) in the world. Around 80% of countries' RPM programs are either informal or in a pilot phase, and thus lack policies and an established regulatory framework to implement their programs. The various policies needed to initiate, deliver, and reimburse RPM programs during emergency situations and outbreaks are discussed. Finally, technologies such as contactless systems, robotics, and Internet-of-things (IoT) that will revolutionize healthcare in the future by reducing the interaction between physicians and patients and cross-infection are discussed.

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