Real-time Healthcare Monitoring System Research Articles

Real-time healthcare monitoring system through haversine distance calculation-based global positioning system

Real-time healthcare monitoring system through haversine distance calculation-based global positioning system

Real-time healthcare monitoring system through haversine distance calculation-based global positioning system

Real-time healthcare monitoring system through haversine distance calculation-based global positioning system

Smartphone-based ECG signals encryption for transmission and analyzing via IoMTs

Electrocardiography (ECG) has long been a common method of assessing and diagnosing cardiovascular problems (CaDs). The heart’s electrical activity is visualized in the form of a waveform and its analysis can turn out to provide valuable insights about the functioning and normalcy of a healthy heart or detect a wide range of possible heart risks. This article deals with the Internet of Medical Things (IoMT) based real time healthcare monitoring system which diagnoses the ECG signals remotely and hence manifests essential heart conditions. An electrocardiograph machine captures medical-grade patient heart data. The outcome of the project includes detecting the heart rate, the various interval and segment analysis of the signal, cardiac axis detection as well as prompting the various possible conditions in case of anomalies in the heart activities. In such cases, the system can send an automatic ECG report from the patient to the doctor safely by encrypting this report. It can be further modified to generate a call in case of critical condition and provide urgent medical assistance. During the ECG analysis, the article presented clearly results represented by finding different values for different patients starting from QRS width 96, PR Interval 133, and P amplitude 2.81, and ending last patient test QRS width 93, PR Interval 112, and P amplitude 1.57.

Roll-to-roll graphene films for non-disposable electrocardiogram electrodes

Graphene has good electrical properties, flexibility, and biocompatibility, making it an ideal material to monitor electrocardiogram (ECG) signals. However, the production cost and the feasibility of large-scale production limit the application of graphene electrodes. Here, we demonstrate a roll-to-roll (R2R) method to transfer graphene grown by open-R2R chemical vapor deposition onto an ethylene vinyl acetate/polyethylene terephthalate (EVA/PET) substrate to make non-disposable ECG electrodes. This method can produce a continuous graphene/EVA/PET film with 15 cm width, and the length can reach several meters. The graphene/EVA/PET film has excellent flexibility and transparency (75.08% transmittance at 780 nm). Compared with commercial silver/silver chloride (Ag/AgCl) electrodes, R2R graphene electrodes have lower electrode–skin impedance below 1 kHz and can obtain ECG signals with similar performance to Ag/AgCl electrodes. Besides, R2R graphene electrodes have good washability. After ten times cleaning, the resistance of the R2R graphene electrode only increased by 23.2%, which was lower than that of the previous graphene electrodes. This work has great potential in the long-term and real-time healthcare monitoring system.

Electrochromic Alarm System with Computer Vision in Smart Contact Lens

Recent advances in smart healthcare system using IoT are becoming mandatory with continuous and real time healthcare monitoring system. This system can give signal to the user by sound or stimulation when health condition become severe. As one of them, smart contact lens can be used to monitor vital signals from glucose level of the tear related to diabetes1 and intraocular pressure related to glaucoma2. However, previous researches about smart contact lens used wireless communication for signal transfer which need external receiver and antenna inside. Moreover, research that deals with data transmission to the user by image visualization on the contact lens has not been yet published. Herein, we have demonstrated electrochromic alarm system which uses color change to give direct signal transfer to the user by electrochemical reaction with ions in tear. This system showed clear color change with curved shape in limited spaces. Also, diverse intensities and frequencies of color change were controlled by the various voltages and duration of voltage application to this system. In addition, various color changing patterns can be shown to the user by controlling the duration of voltage application and Morse code was used to transfer words to the user in specific purpose. With the help of computer vision, color changing patterns were detected and interpreted. We believe that our electrochromic alarm system with diverse patterns suggest new method for direct data transmission to the user with the help of computer vision. Also, it can be integrated into smart contact lens with battery and various sensors.References D. H. Keum, S.-K. Kim, J. Koo, G.-H. Lee, C. Jeon, J. W. Mok, B. H. Mun, K. J. Lee, E. Kamrani, C.-K. Joo, S. Shin, J.-Y. Sim, D. Myung, S. H. Yun, Z. Bao, S. K. Hahn, Wireless smart contact lens for diabetic diagnosis and therapy. Sci. Adv. 6, eaba3252 (2020).J. Kim, M. Kim, M.-S. Lee, K. Kim, S. Ji, Y.-T. Kim, J. Park, K. Na, K.-H. Bae, H. K. Kim, F. Bien, C. Y. Lee, J.-U. Park, Wearable smart sensor systems integrated on soft contact lenses for wireless ocular diagnostics. Nat. Commun. 8, 14997 (2017). Figure 1

A review: a new authentication protocol for real-time healthcare monitoring system.

Internet of Things is a fast growing technology and a network of devices in which everything (smart objects or smart devices) are associated to the internet for effective exchange of information between these connected objects. Internet of Things (IoT) serves as a method for healthcare and acts as an essential part in broad range of real-time healthcare monitoring applications. Previous work shows networked sensor devices, either equipped on the body or embedded inside living being or a camera, make possible in gathering real-time information to evaluate physical and mental health state of the patient by collecting body temperature, blood pressure, patient's image, etc. Communicating this collected real-time data to the doctor, making accurate assessment on the data gathered and notifying the patient is challenging task in the IoT. The architechture of Internet of Things comprises of three layers, and it is the network of devices embedded with sensor, software, and electronics, enabling this device to communicate with each other and exchange data over a computer network. The IoT-based real-time healthcare systems are highly vulnerable to cyber-attacks as the numbers of sensors are deployed in an unprotected network. These may even introduce the attacks, which cannot be monitored and controlled. This paper attempts to review the previous work done and a new scheme has been proposed, the new lightweight authentication protocol for smart real-time healthcare. The proposed scheme requires implementation with the authentication protocol. It is important to satisfy the major parameters of security: confidentiality, integrity, authentication, and access control. In this paper our focus is on the authentication of devices.

Reducing waiting time for remote patients in telemedicine with considering treated patients in emergency department based on body sensors technologies and hybrid computational algorithms: Toward scalable and efficient real time healthcare monitoring system.

Scalability challenge in real time healthcare monitoring system relates to several issues. One of the insistent issues is the increasing in the number of patients. Increasing in the patients' number causes long queue and increase the waiting time for the patients in their seeking for healthcare services. Thus, an ethical issue raises as the healthcare providers should provide fast services for all patients. Recent studies have proposed scalable models that are limited to (1) triaging remote patients for the optimal emergency level and (2) prioritizing remote patients with the highest triage level to receive immediate healthcare services. However, these studies have shown limitations, that is, (1) they have not addressed the waiting time for all patients with different triage levels in the same waiting queue; and (2) they have not considered Emergency Department EDs patients. Therefore, considering the remote patients with the treated patients in EDs in one healthcare system is a demand, to efficiently handle all the patients' requests and productively manage the medical resources. This study aims to reduce the waiting time for the remote patients in telemedicine with considering treated patients in EDs. The study presents a scalable telemedicine model to improve the ability of real time healthcare monitoring system in accommodating the increasing number of patients with chronic heart disease by reducing their waiting time for healthcare services, prioritizing the patients who have the most emergency cases and provide all the patients by fast healthcare services. The proposed model called Triaging and Prioritizing Model "TPM". The proposed model "TPM" considers triaging and prioritizing all patients (remote and EDs patients) as two sequential processes. The TPM was formulated to triage the patients based on hybrid algorithms which combine Evidence-Theory with Fuzzy Cluster Means (FCM) and then prioritize the patients based on dedicated computational algorithm. A simulation, on 580 chronic heart diseases patients, was implemented. The patients considered as they have different emergency levels based on four vital data acquisition tools: electrocardiogram sensor, blood pressure sensor, oxygen saturation sensor and a text input as non-sensory based acquisition tool. Computational results show the superiority of the proposed model (TPM) in accommodating large numbers of patients and reducing their waiting time for services compared with relevant benchmark studies. In 1,185min, TPM managed the (580) patients' requests. By contrast, the benchmark managed only 256 patients at the same amount of time. In addition to that, TPM shows improvements in terms of waiting time and services provisioning rates compared with benchmark methods. All patients with the different emergency levels receive services with less waiting time compared with the relevant studies. The proposed model (TPM) model considers both of remote patients and treated patients in EDs efficiently. TPM improves response time for the medical services, reduces waiting time for all patients and consequently, saves more lives.

RETRACTED ARTICLE: A fuzzy model of wearable network real-time health monitoring system on pharmaceutical industry

With the introduction of wearable network technologies, smart healthcare is gradually being realized. Real-time health care monitoring system should be safe, effective, and patient-centered. This paper aims to analyze the opinions and emotions of medical and health products, and to design and develop monitoring systems by crawling multiple websites and reviews in a variety of formats. Data preprocessing is used to preprocess the quantized image, and finally, it is recommended in combination with the analysis results. This system combines a large amount of products’ comment data, combined with MATLAB and other tools to achieve the visualization of big data analysis, by the use of the maximum entropy algorithm for comprehensive analysis and comparison. Support vector machine (SVM) algorithm is used to analyze and compare various parts of the medical image in detail. It is suitable for current medical applications. It can provide advice for consumers to purchase drugs and achieve real-time health monitoring objectives.

Systemic Design Approach to a Real-Time Healthcare Monitoring System: Reducing Unplanned Hospital Readmissions.

Following hospital discharge, millions of patients continue to recover outside formal healthcare organizations (HCOs) in designated transitional care periods (TCPs). Unplanned hospital readmissions of patients during TCPs adversely affects the quality and cost of care. In order to reduce the rates of unplanned hospital readmissions, we propose a real-time patient-centric system, built around applications, to assist discharged patients in remaining at home or in the workplace while being supported by care providers. Discrete-event system modeling techniques and supervisory control theory play fundamental roles in the system’s design. Simulation results and analysis show that the proposed system can be effective in documenting a patient’s condition and health-related behaviors. Most importantly, the system tackles the problem of unplanned hospital readmissions by supporting discharged patients at a lower cost via home/workplace monitoring without sacrificing the quality of care.

Real-Time Health Care Monitoring System using IoT

Incorporation of Information and Communication Technology (ICT) in healthcare industry explored the possibilities to optimize the supply of all the available medical resources and provide reliable, efficient healthcare services to the aged people and patients with physical disabilities and chronic illness. In consumer electronics and growing costs of healthcare a vision of connected e-health has evolved which constitute Personal Health Devices (PHD). Present day mobile devices are capable enough to gather data from various sensors and often play a role in physical fitness gateway and then data are collected in PHDs. The network overhead and suitability of the proposed solution for the different environment is presented which includes the integration of different wireless interfaces with cloud services. The work focuses on adapting the MQTT (Message Queue Telemetry Transport) communication model. This protocol is preferred over CoAP which is one-one protocol because it is one of the lightweight protocols used in TCP/IP and it has the feature of many to many communication models. The evaluation of the work is on a PHD prototype device and feasibility of the solution is discussed. The proposed work is to design and develop a Real-time healthcare monitoring system using IoT which is featured with Random Forest algorithm for heart disease prediction by gathering patient’s data from various PHD sensors and timely alert the caretaker as well as a doctor by sending messages through MQTT. It monitors the patient’s physiological parameters remotely and diagnoses the heart diseases as early as possible.The main motto is to reduce the cost of healthcare and give people the awareness about health and fitness.

Real-time healthcare monitoring system using wireless sensor network

This paper presents the design, implementation and evaluation of a wireless portable healthcare monitoring system. It has a set of medical sensors connected to an embedded microcontroller with a wireless communication module. By scanning the medical sensors, the embedded microcontroller checks if the patient health condition is normal or not. In the case of abnormal condition, the embedded unit transmits the measured signals directly to a medical centre through the internet. According to the patient health condition, a doctor will send medical advice to the patient to address the abnormality of the patient. A prototype system has been designed, implemented, and validated by both laboratory test and comparison with recommended medical standards. A detailed analysis and evaluation of the healthcare unit is given in the paper. The obtained results indicate that the proposed healthcare system is accurate in scanning, clear in monitoring, reliable in communication, and can be used as a portable medical kit for outdoor patient monitoring and supervising, or as a medical station at home.

Real-time healthcare monitoring system using wireless sensor network

This paper presents the design, implementation and evaluation of a wireless portable healthcare monitoring system. It has a set of medical sensors connected to an embedded microcontroller with a wireless communication module. By scanning the medical sensors, the embedded microcontroller checks if the patient health condition is normal or not. In the case of abnormal condition, the embedded unit transmits the measured signals directly to a medical centre through the internet. According to the patient health condition, a doctor will send medical advice to the patient to address the abnormality of the patient. A prototype system has been designed, implemented, and validated by both laboratory test and comparison with recommended medical standards. A detailed analysis and evaluation of the healthcare unit is given in the paper. The obtained results indicate that the proposed healthcare system is accurate in scanning, clear in monitoring, reliable in communication, and can be used as a portable medical kit for outdoor patient monitoring and supervising, or as a medical station at home.

Wireless body area networks towards empowering real-time healthcare monitoring: a survey

The speedy raising insalubrious environment, where peoples have less focus towards own health and physical fitness has impel the need of caregivers and doctors. In addition, increase in elderly population and numerous chronic diseases fortify the need of real-time healthcare system to monitor numerous physiological sign at their doorstep. The advances in sensing, computing and communication technologies coupled with level of comfort, cost reduction, and continuously health monitoring have led to the development of wireless body area networks WBANs. Development of WBANs impels to make use of wearable and implanted sensor devices for various physiological sign monitoring. Furthermore, it provides long term, real-time healthcare monitoring to individual personal without restricting their daily life activities. In this paper, we proposed a general real-time healthcare monitoring system architecture. We also summarised the need, challenges and radio technologies of WBANs, since it is the key factor to achieve low power and low latency.

Wireless body area networks towards empowering real-time healthcare monitoring: a survey

The speedy raising insalubrious environment, where peoples have less focus towards own health and physical fitness has impel the need of caregivers and doctors. In addition, increase in elderly population and numerous chronic diseases fortify the need of real-time healthcare system to monitor numerous physiological sign at their doorstep. The advances in sensing, computing and communication technologies coupled with level of comfort, cost reduction, and continuously health monitoring have led to the development of wireless body area networks (WBANs). Development of WBANs impels to make use of wearable and implanted sensor devices for various physiological sign monitoring. Furthermore, it provides long term, real-time healthcare monitoring to individual personal without restricting their daily life activities. In this paper, we proposed a general real-time healthcare monitoring system architecture. We also summarised the need, challenges and radio technologies of WBANs, since it is the key factor to achieve low power and low latency.