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Proceedings ArticleDOI

Smart Health Monitoring System through IOT

04 Apr 2019-pp 0968-0970
TL;DR: The main aim of this work is to provide an extensive research in capturing the sensor data’s, analyzing the data and providing a feedback to patients based on different health parameters.
Abstract: IOT is one of the booming field in forthcoming years and plays a major role in the field of health care. IOT helps in connecting the people by empowering their health and wealth in a smart way through wearable gadgets. Recent improvement in wireless sensor networks have created a new trend in internet of things. Smart health is important application in Internet of things. Patients with abnormal health conditions can be quickly monitored through smart health care system and provide a rapid solution for the patients. This type of solutions can be encountered through wearable gadgets that continuously monitor the activity and condition of the patient in a predictable method. The main aim of this work is to provide an extensive research in capturing the sensor data’s, analyzing the data and providing a feedback to patients based on different health parameters.
Citations
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Journal ArticleDOI
TL;DR: The security and the performance analysis demonstrate that the proposed scheme supports better assistance to BSHs while maintaining security.

80 citations

Proceedings ArticleDOI
01 Feb 2020
TL;DR: The proposed hardware as well as software system helps patient to predict heart disease in early stages and will be helpful for mass screening system in villages where hospital facilties are not available, i.e., rural areas.
Abstract: Coronary illness is that the principle purpose for death around the world. Human services field contains a tremendous measure of information, for handling those information certain methods are utilized. Handling or processing is one in all methods regularly utilized. This strategy predicts the emerging potential outcomes of cardiovascular ailment. The results of this strategy are to foresee the previous cardiovascular malady. The task manages IOT using sensor (pulse sensor to watch pulse) with Arduino and furthermore the outcome can be checked in sequential screen. With the use of IFTTT the readings of sensor are perused in google sheet which is then changed over into csv go looking like data. The datasets utilized are grouped as far as therapeutic parameters which are additionally utilized for preparing and testing the information. This strategy assesses those parameters utilizing information preparing order method. With the work of AI calculations and classification. Initially, the dataset is dissected, watched and screened, at that point the obtained information is handled in python programming utilizing Machine Learning Algorithm to be specific Decision Tree Algorithm and Random backwoods classifier Algorithm. SVM (Support vector machine) shows the higher outcome as far as exactness for identifying heart illness. Henceforth the proposed framework is demonstrated to be solid one for foreseeing prior heart disease. The proposed hardware as well as software system helps patient to predict heart disease in early stages. It will be helpful for mass screening system in villages where hospital facilties are not available, i.e., rural areas.

42 citations

Journal ArticleDOI
TL;DR: This research work provides an overview of IoMT with emphasis on various enabling techniques used in smart healthcare systems (SHS), such as radio frequency identification (RFID), artificial intelligence (AI), and blockchain.
Abstract: Internet of Medical Thing (IoMT) is the most emerging era of the Internet of Thing (IoT), which is exponentially gaining researchers' attention with every passing day because of its wide applicability in Smart Healthcare systems (SHS). Because of the current pandemic situation, it is highly risky for an individual to visit the doctor for every small problem. Hence, using IoMT devices, we can easily monitor our day-to-day health records, and thereby initial precautions can be taken on our own. IoMT is playing a crucial role within the healthcare industry to increase the accuracy, reliability, and productivity of electronic devices. This research work provides an overview of IoMT with emphasis on various enabling techniques used in smart healthcare systems (SHS), such as radio frequency identification (RFID), artificial intelligence (AI), and blockchain. We are providing a comparative analysis of various IoMT architectures proposed by several researchers. Also, we have defined various health domains of IoMT, including the analysis of different sensors with their application environment, merits, and demerits. In addition, we have figured out key protocol design challenges, which are to be considered during the implementation of an IoMT network-based smart healthcare system. Considering these challenges, we prepared a comparative study for different data collection techniques that can be used to maintain the accuracy of collected data. In addition, this research work also provides a comprehensive study for maintaining the energy efficiency of an AI-based IoMT framework based on various parameters, such as the amount of energy consumed, packet delivery ratio, battery lifetime, quality of service, power drain, network throughput, delay, and transmission rate. Finally, we have provided different correlation equations for finding the accuracy and efficiency within the IoMT-based healthcare system using artificial intelligence. We have compared different data collection algorithms graphically based on their accuracy and error rate. Similarly, different energy efficiency algorithms are also graphically compared based on their energy consumption and packet loss percentage. We have analyzed our references used in this study, which are graphically represented based on their distribution of publication year and publication avenue.

23 citations

Proceedings ArticleDOI
05 Nov 2020
TL;DR: In this paper, the authors proposed a user-friendly app-based solution that collects real-time information and defines a pervasive cost-effective system developed with the aid of sensors and Internet of Things.
Abstract: With the profligate enhancement in the Internet of Things (IoT), people are able to diligently connect, communicate and remotely monitor and control devices via the Internet. This stupendous advancement has become a boon in solving everyday problems in the Healthcare Industry, through Medical Internet of Things (M-IoT). In the present-day scenario, one of the pressing challenges surfacing is to provide a holistic and self-reliant healthcare system designed for the elderly. This emphasizes a single and reliable system that could effectively cater to the requirements of senior citizens who need some health assistance with everyday activities. This paper proposes a user-friendly app-based solution that collects real-time information and defines a pervasive cost-effective system developed with the aid of sensors and Internet of Things. A survey of fever symptoms is done for people aged above 50 years and Machine Learning analysis is performed to recognize the best model. The proposed system thus keenly aims to keep the family members well-informed about the patient.

15 citations

Book ChapterDOI
01 Jan 2021
TL;DR: In this article, a smart healthcare monitoring system for patients by implanting wireless sensors on the body which collect different vital physiological parameters such as heart rate, blood pressure, body temperature, glucose level etc.
Abstract: This chapter presents a smart healthcare monitoring system for patients by implanting wireless sensors on the body which collect different vital physiological parameters such as heart rate, blood pressure, body temperature, glucose level etc. The sensors are controlled by the Internet of Things devices and communicate the patient’s health record to the monitoring station using 5G services. This 5G service helps to enable the immediate treatment for the critical patient with no time. In addition, the rate of detection of the critical condition of the patient is enhanced with the application of machine learning models for better and efficient prediction. Therefore, the improvement of healthcare monitoring system enhances human life value by integrating advanced and cutting edge technologies as a consequence of which the frequent visit of patients to the hospitals or emergency units can be reduced.

11 citations

References
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Journal ArticleDOI
TL;DR: Experimental results reveal that the proposed system is reliable in collecting and displaying real-time ECG data, which can aid in the primary diagnosis of certain heart diseases.
Abstract: Public healthcare has been paid an increasing attention given the exponential growth human population and medical expenses It is well known that an effective health monitoring system can detect abnormalities of health conditions in time and make diagnoses according to the gleaned data As a vital approach to diagnose heart diseases, ECG monitoring is widely studied and applied However, nearly all existing portable ECG monitoring systems cannot work without a mobile application, which is responsible for data collection and display In this paper, we propose a new method for ECG monitoring based on Internet-of-Things (IoT) techniques ECG data are gathered using a wearable monitoring node and are transmitted directly to the IoT cloud using Wi-Fi Both the HTTP and MQTT protocols are employed in the IoT cloud in order to provide visual and timely ECG data to users Nearly all smart terminals with a web browser can acquire ECG data conveniently, which has greatly alleviated the cross-platform issue Experiments are carried out on healthy volunteers in order to verify the reliability of the entire system Experimental results reveal that the proposed system is reliable in collecting and displaying real-time ECG data, which can aid in the primary diagnosis of certain heart diseases

365 citations

Journal ArticleDOI
TL;DR: Typical applications powered by smart clothing and big data clouds are presented, such as medical emergency response, emotion care, disease diagnosis, and real-time tactile interaction.
Abstract: Traditional wearable devices have various shortcomings, such as uncomfortableness for long-term wearing, and insufficient accuracy, etc. Thus, health monitoring through traditional wearable devices is hard to be sustainable. In order to obtain healthcare big data by sustainable health monitoring, we design "Smart Clothing", facilitating unobtrusive collection of various physiological indicators of human body. To provide pervasive intelligence for smart clothing system, mobile healthcare cloud platform is constructed by the use of mobile internet, cloud computing and big data analytics. This paper introduces design details, key technologies and practical implementation methods of smart clothing system. Typical applications powered by smart clothing and big data clouds are presented, such as medical emergency response, emotion care, disease diagnosis, and real-time tactile interaction. Especially, electrocardiograph signals collected by smart clothing are used for mood monitoring and emotion detection. Finally, we highlight some of the design challenges and open issues that still need to be addressed to make smart clothing ubiquitous for a wide range of applications.

318 citations


"Smart Health Monitoring System thro..." refers methods in this paper

  • ...Here we are decoding the ECG, PPG HR data’s in that android application by parsing the raw data[10]....

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Journal ArticleDOI
TL;DR: The use of patient images and emotional detection to assist patients and elderly people within an in-home healthcare context is discussed and the prototype which runs on multiple computing platforms is outlined, showing results that demonstrate the feasibility of this approach.

195 citations


"Smart Health Monitoring System thro..." refers background in this paper

  • ...connected with the smart phone via android application[8]....

    [...]

Journal ArticleDOI
TL;DR: A voice pathology detection system is proposed inside the monitoring framework using a local binary pattern on a Mel-spectrum representation of the voice signal, and an extreme learning machine classifier to detect the pathology.
Abstract: The integration of the IoT and cloud technology is very important to have a better solution for an uninterrupted, secured, seamless, and ubiquitous framework. The complementary nature of the IoT and the could in terms of storage, processing, accessibility, security, service sharing, and components makes the convergence suitable for many applications. The advancement of mobile technologies adds a degree of flexibility to this solution. The health industry is one of the venues that can benefit from IoT–Cloud technology, because of the scarcity of specialized doctors and the physical movement restrictions of patients, among other factors. In this article, as a case study, we discuss the feasibility of and propose a solution for voice pathology monitoring of people using IoT–cloud. More specifically, a voice pathology detection system is proposed inside the monitoring framework using a local binary pattern on a Mel-spectrum representation of the voice signal, and an extreme learning machine classifier to detect the pathology. The proposed monitoring framework can achieve high accuracy of detection, and it is easy to use.

191 citations


"Smart Health Monitoring System thro..." refers background in this paper

  • ...It can automate the web application tasks there are various automation applets are there for various instances[12]....

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Journal ArticleDOI
TL;DR: The authors analyze the characteristics of wearable applications for IoT scenarios and describe the interaction patterns that should occur between wearable or mobile devices and smart objects.
Abstract: In the next few years, the Internet of Things (IoT) will become a reality, merging the social, physical, and cyber worlds to enable new applications and forms of interaction between humans and connected, smart sensing and actuating devices As billions of smart objects become deployed pervasively in the environment, users should be able to discover and interact with objects in their proximity in a seamless and transparent way Although smartphones have become an extremely popular computing device, smart wearable devices, such as Google Glass and the Apple watch, are now providing even more effective means to bridge the gap between humans and smart objects The authors analyze the characteristics of wearable applications for IoT scenarios and describe the interaction patterns that should occur between wearable or mobile devices and smart objects The authors also present an implementation of a wearable-based Web of Things application used to evaluate the described interaction patterns in a smart environment, deployed within their department's IoT testbed

37 citations


"Smart Health Monitoring System thro..." refers background in this paper

  • ...automation, building automation, intelligent cities and health care[2-4]....

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  • ...This paper widely explains about the communication and interaction part of smart watch and how wearables are connected wirelessly to a gateway and also it explains how this smart watch is connected to smart phone with appropriate android application via BLE( Bluetooth low energy) [3]....

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