Smart Healthcare Monitoring System

Abhishek, Kumar; Chattree, Gaurav; Sasikumar, P

doi:10.1007/s11277-018-5699-0

Cited by 24 publications

(13 citation statements)

References 8 publications

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“…This proposed ECG monitoring system mainly uses the IoT technology to achieve real-time monitoring of ECG signals, analyze the data and establish a platform for remote communications between doctors and patients, which can perform prevention and treatment of cardiovascular disease [27]. As shown in Fig.…”

Section: B Overviewmentioning

confidence: 99%

A Wearable ECG Monitor for Deep Learning Based Real-Time Cardiovascular Disease Detection

Wang¹,

Lin²,

Yan³

et al. 2022

Preprint

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Cardiovascular disease has become one of the most significant threats endangering human life and health. Recently, Electrocardiogram (ECG) monitoring has been transformed into remote cardiac monitoring by Holter surveillance. However, the widely used Holter can bring a great deal of discomfort and inconvenience to the individuals who carry them. We developed a new wireless ECG patch in this work and applied a deep learning framework based on the Convolutional Neural Network (CNN) and Long Short-term Memory (LSTM) models. However, we find that the models using the existing techniques are not able to differentiate two main heartbeat types (Supraventricular premature beat and Atrial fibrillation) in our newly obtained dataset, resulting in low accuracy of 58.0 %. We proposed a semisupervised method to process the badly labelled data samples with using the confidence-level-based training. The experiment results conclude that the proposed method can approach an average accuracy of 90.2 %, i.e., 5.4 % higher than the accuracy of conventional ECG classification methods.

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Section: B Overviewmentioning

confidence: 99%

A Wearable ECG Monitor for Deep Learning Based Real-Time Cardiovascular Disease Detection

Wang¹,

Lin²,

Yan³

et al. 2022

Preprint

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“…However, no security measures are taken into consideration in this system. Afterward, Kumar et al [57] introduced a smart healthcare monitoring system where patients and doctors can interact through a camera. The health parameters from input sensors (HR and temperature sensor) are sent to the processing module (Raspberry Pi) and displayed on LCD.…”

Section: A Wearable Devices For Health Monitoringmentioning

confidence: 99%

Smart Healthcare in the Age of AI: Recent Advances, Challenges, and Future Prospects

Mahmoud¹,

et al. 2021

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The significant increase in the number of individuals with chronic ailments (including the elderly and disabled) has dictated an urgent need for an innovative model for healthcare systems. The evolved model will be more personalized and less reliant on traditional brick-and-mortar healthcare institutions such as hospitals, nursing homes, and long-term healthcare centers. The smart healthcare system is a topic of recently growing interest and has become increasingly required due to major developments in modern technologies, especially in artificial intelligence (AI) and machine learning (ML). This paper is aimed to discuss the current state-of-the-art smart healthcare systems highlighting major areas like wearable and smartphone devices for health monitoring, machine learning for disease diagnosis, and the assistive frameworks, including social robots developed for the ambient assisted living environment. Additionally, the paper demonstrates software integration architectures that are very significant to create smart healthcare systems, integrating seamlessly the benefit of data analytics and other tools of AI. The explained developed systems focus on several facets: the contribution of each developed framework, the detailed working procedure, the performance as outcomes, and the comparative merits and limitations. The current research challenges with potential future directions are addressed to highlight the drawbacks of existing systems and the possible methods to introduce novel frameworks, respectively. This review aims at providing comprehensive insights into the recent developments of smart healthcare systems to equip experts to contribute to the field.

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“…is application furthermore displays the patients' temperature and heartbeat traced live information with timestamps over the Internetwork [18]. A system comprising different sensors to measure health parameters like temperature and heart rate as input has been proposed [19]. Responses taken from sensors are managed in raspberry pi and presented on LCD.…”

Section: Related Workmentioning

confidence: 99%

Enhancing Healthcare through Detection and Prevention of COVID-19 Using Internet of Things and Mobile Application

Chen

Khan

Abbas

et al. 2021

Mobile Information Systems

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The main symptoms of COVID-19 are high temperature, throat infection, and irregular heartbeat. An integrated wearable device has been presented in this paper for the measurement of temperature and heartbeat in real time using different sensors and NodeMCU ESP8266. For temperature, the DHT11 sensor is used and, for heartbeat, the pulse sensor is used. After reading the data from the sensors processed by NodeMCU ESP8266, it is sent to the firebase database using wireless connection (Wi-Fi module). From the database, the data are displayed in an android application. On the basis of certain conditions of the data, the user as well as the administrator is notified regarding the user’s current health. For the social distancing, an ultrasonic sensor is used. The sensor will warn the user, if he/she is in close contact with someone within a specified distance. The user’s current location is also tracked using the location services of android. A module named COVID-meter, based on the disease.sh-Open Disease Data API, was also included in the research for reading of real-time data of different countries related to COVID-19 like total cases, total deaths, total recovered patients, and so on. The proposed device can be used in both populated and rural areas, but in rural areas it will be much more important because people are unable to reach a doctor on time; thus, they can check their health conditions remotely using the proposed device.

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Smart Healthcare Monitoring System

Cited by 24 publications

References 8 publications

A Wearable ECG Monitor for Deep Learning Based Real-Time Cardiovascular Disease Detection

A Wearable ECG Monitor for Deep Learning Based Real-Time Cardiovascular Disease Detection

Smart Healthcare in the Age of AI: Recent Advances, Challenges, and Future Prospects

Enhancing Healthcare through Detection and Prevention of COVID-19 Using Internet of Things and Mobile Application

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