IoT-Based Fall and ECG Monitoring System: Wireless Communication System Based Firebase Realtime Database

Al‐Kababji, Ayman; Shidqi, Lisan; Boukhennoufa, Issam; Amira, Abbes; Bensaali, Fayçal; Gastli, Mohamed Sadok; Jarouf, Abdulah; Aboueata, Walid; Abdalla, Alhusain

doi:10.1109/smartworld-uic-atc-scalcom-iop-sci.2019.00267

Cited by 15 publications

(10 citation statements)

References 15 publications

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“…They have proposed a unique method called compressive sensing that can optimize power consumption and provide optimal performance in ECG monitoring. IoT-based fall detection and ECG monitoring system has also been reported in [ 76 ] that uses a cloud-based server and a mobile application. This system was designed to provide real-time monitoring to elderly patients by continuously checking their ECG and accelerometer data.…”

Section: Services and Application Of Hiotmentioning

confidence: 99%

IoT-Based Applications in Healthcare Devices

Pradhan

Bhattacharyya

Pal

2021

Journal of Healthcare Engineering

239

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The last decade has witnessed extensive research in the field of healthcare services and their technological upgradation. To be more specific, the Internet of Things (IoT) has shown potential application in connecting various medical devices, sensors, and healthcare professionals to provide quality medical services in a remote location. This has improved patient safety, reduced healthcare costs, enhanced the accessibility of healthcare services, and increased operational efficiency in the healthcare industry. The current study gives an up-to-date summary of the potential healthcare applications of IoT- (HIoT-) based technologies. Herein, the advancement of the application of the HIoT has been reported from the perspective of enabling technologies, healthcare services, and applications in solving various healthcare issues. Moreover, potential challenges and issues in the HIoT system are also discussed. In sum, the current study provides a comprehensive source of information regarding the different fields of application of HIoT intending to help future researchers, who have the interest to work and make advancements in the field to gain insight into the topic.

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Section: Services and Application Of Hiotmentioning

confidence: 99%

IoT-Based Applications in Healthcare Devices

Pradhan

Bhattacharyya

Pal

2021

Journal of Healthcare Engineering

239

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“…The proposed communication structure in Figure 3 highlights interlinked entities within the cloud-hosted database platform, and illustrates the role of both the ODROID-XU4 and the user's mobile application for data visualization [9]. As illustrated by Figure 3, the elderly-to-caregiver communication system involves the link from the Shimmer3ECG, the ODROID-XU4 as the gateway and the cloud-hosted Firebase Realtime database up to the Vitals Monitoring mobile application.…”

Section: Software Implementationmentioning

confidence: 99%

“…Not only that, but for the first time in human history, in 2019, people aged 65 or more have exceeded the number of children below five [1]. This is a life-changing in [9]. This demonstrates that a complete automated monitoring system can be implemented on a device that the majority of, if not all, people have.…”

Section: Introductionmentioning

confidence: 99%

An IoT-based framework for remote fall monitoring

Al‐Kababji

Amira

Bensaali

et al. 2021

Biomedical Signal Processing and Control

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Fall detection is a serious healthcare issue that needs to be solved. Falling without quick medical intervention would lower elderly's chances of survival, especially if living alone. Hence, the need is there for developing fall detection algorithms with high accuracy. This paper presents a novel IoT-based system for fall detection that includes a sensing device transmitting data to a mobile application through a cloud-connected gateway device. Then, the focus is shifted to the algorithmic aspect where multiple features are extracted from 3-axis accelerometer data taken from existing datasets. The results emphasize on the significance of Continuous Wavelet Transform (CWT) as an influential feature for determining falls. CWT, Signal Energy (SE), Signal Magnitude Area (SMA), and Signal Vector Magnitude (SVM) features have shown promising classification results using K-Nearest Neighbors (KNN) and E-Nearest Neighbors (ENN). For all performance metrics (accuracy, recall, precision, specificity, and F 1 Score), the achieved results are higher than 95% for a dataset of small size, while more than 98.47% score is achieved in the aforementioned criteria over the UniMiB-SHAR dataset by the same algorithms, where the classification time for a single test record is extremely efficient and is real-time.

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“…During the growth of artificial intelligence and its integration with sensors, machine learning (ML) techniques have experienced significant changes in wearable health monitoring systems based on IoT [52], [53], [54], [55], [56]. To track basic health parameters, IoT-based sensors are used to classify many diseases such as chronic illnesses, diabetes, and many more.…”

Section: Ecg Monitoring and Machine Learningmentioning

confidence: 99%

Smart Healthcare for ECG Telemonitoring System

Saeed¹,

Ameen

2021

JSCDM

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Cardiovascular disorders are one of the major causes of sad death among older and middle-aged people. Over the past two decades, health monitoring services have evolved quickly and had the ability to change the way health care is currently provided. However, the most challenging aspect of the mobile and wearable sensor-based human activity recognition pipeline is the extraction of the related features. Feature extraction decreases both computational complexity and time. Deep learning techniques are used for automatic feature learning in a variety of fields, including health, image classification, and, most recently, for the extraction and classification of complex and straightforward human activity recognition in smart health care. This paper reviews the recent state of the art in electrocardiogram (ECG) smart health monitoring systems based on the Internet of things with the machine and deep learning techniques. Moreover, the paper provided possible research and challenges that can help researchers advance state of art in future work.

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IoT-Based Fall and ECG Monitoring System: Wireless Communication System Based Firebase Realtime Database

Cited by 15 publications

References 15 publications

IoT-Based Applications in Healthcare Devices

IoT-Based Applications in Healthcare Devices

An IoT-based framework for remote fall monitoring

Smart Healthcare for ECG Telemonitoring System

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