A Wearable Wireless ECG Monitoring System With Dynamic Transmission Power Control for Long-Term Homecare

Wang, Yishan; Doleschel, Sammy; Wunderlich, Ralf; Heinen, Stefan

doi:10.1007/s10916-015-0223-5

Cited by 30 publications

(7 citation statements)

References 29 publications

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“…Several research works on wearable ECG monitoring have been developed in the literature [25,29,[125][126][127][128]. These works can be classified into textile-based systems, such as [29,128], and contactless based systems, such as [126].…”

Section: Ambulatory Ecg Monitoring Systemsmentioning

confidence: 99%

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ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges

Serhani

Kassabi

Ismail

et al. 2020

Sensors

231

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Health monitoring and its related technologies is an attractive research area. The electrocardiogram (ECG) has always been a popular measurement scheme to assess and diagnose cardiovascular diseases (CVDs). The number of ECG monitoring systems in the literature is expanding exponentially. Hence, it is very hard for researchers and healthcare experts to choose, compare, and evaluate systems that serve their needs and fulfill the monitoring requirements. This accentuates the need for a verified reference guiding the design, classification, and analysis of ECG monitoring systems, serving both researchers and professionals in the field. In this paper, we propose a comprehensive, expert-verified taxonomy of ECG monitoring systems and conduct an extensive, systematic review of the literature. This provides evidence-based support for critically understanding ECG monitoring systems’ components, contexts, features, and challenges. Hence, a generic architectural model for ECG monitoring systems is proposed, an extensive analysis of ECG monitoring systems’ value chain is conducted, and a thorough review of the relevant literature, classified against the experts’ taxonomy, is presented, highlighting challenges and current trends. Finally, we identify key challenges and emphasize the importance of smart monitoring systems that leverage new technologies, including deep learning, artificial intelligence (AI), Big Data and Internet of Things (IoT), to provide efficient, cost-aware, and fully connected monitoring systems.

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Section: Ambulatory Ecg Monitoring Systemsmentioning

confidence: 99%

“…Various research initiatives proposed solutions that integrate wearable devices within an ECG monitoring system [14,21,22,29,30,[125][126][127]147]. These solutions are either integrated within an ambulatory setup, home environment, or patient/user setup and are used for the monitoring of various vital signs.…”

Section: Monitoring Devicesmentioning

confidence: 99%

ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges

Serhani

Kassabi

Ismail

et al. 2020

Sensors

231

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“…baseline wander noise, muscle noise) removal from raw ECG signals. Wang et al [43] presented a health monitoring system using wearable wireless ECG sensors with dynamic transmission power control. They employed 3-Lead electrode placements to identify the best electrode positions.…”

Section: Related Workmentioning

confidence: 99%

A lightweight QRS detector for single lead ECG signals using a max-min difference algorithm

Pandit

Zhang

Liu

et al. 2017

Computer Methods and Programs in Biomedicine

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Northumbria University has developed Northumbria Research Link (NRL) to enable users to access the University's research output. Copyright © and moral rights for items on NRL are retained by the individual author(s) and/or other copyright owners. Single copies of full items can be reproduced, displayed or performed, and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided the authors, title and full bibliographic details are given, as well as a hyperlink and/or URL to the original metadata page. The content must not be changed in any way. Full items must not be sold commercially in any format or medium without formal permission of the copyright holder. The full policy is available online: http://nrl.northumbria.ac.uk/policies.html This document may differ from the final, published version of the research and has been made available online in accordance with publisher policies. To read and/or cite from the published version of the research, please visit the publisher's website (a subscription may be required.) A Lightweight QRS AbstractBackground and Objectives: Detection of the R-peak pertaining to the QRS complex of an ECG signal plays an important role for the diagnosis of a patient's heart condition. To accurately identify the QRS locations from the acquired raw ECG signals, we need to handle a number of challenges, which include noise, baseline wander, varying peak amplitudes, and signal abnormality. This research aims to address these challenges by developing an efficient lightweight algorithm for QRS (i.e., R-peak) detection from raw ECG signals. Methods:A lightweight real-time sliding window-based Max-Min Difference (MMD) algorithm for QRS detection from Lead II ECG signals is proposed. Targeting to achieve the best trade-off between computational efficiency and detection accuracy, the proposed algorithm consists of five key steps for QRS detection, namely, baseline correction, MMD curve generation, dynamic threshold computation, R-peak detection, and error correction. Five annotated databases from Physionet are used for evaluating the proposed algorithm in R-peak detection. Integrated with a feature extraction technique and a neural network classifier, the proposed ORS detection algorithm has also been extended to undertake normal and abnormal heartbeat detection from ECG signals. Results:The proposed algorithm exhibits a high degree of robustness in QRS detection and achieves an average sensitivity of 99.62% and an average positive predictivity of 99.67%. Its performance compares favorably with those from the existing state-of-the-art models reported in the literature. In regards to normal and abnormal heartbeat detection, the proposed QRS detection algorithm in combination with the feature extraction technique and neural network classifier achieves an overall accuracy rate of 93.44% based on an empirical evaluation using the MIT-BIH Arrhythmia data set with 10-fold cross validation. Conclusio...

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“…It can also be used to communicate with other systems using transmitter and receiver. In previous designs proposed, for short term monitoring of ECG for 10 sec or 1-2 minutes MSP430 microcontroller was used [34, 71] and for long-term monitoring TI CC2530 system [37], CC2431 [132], DSP [128], DSP chip TMS320VC5509A [133], TMS320F2812 [134], TMDX5505eZDsp/VC5505eZdsp [33], MSP430 (monitoring for 45 days) [68], MSP430F5515 [129], MSP430F1232 [43], MSP430FG439 [135], MSP430F2418 [136], MSP430F5529 [66] (monitoring for 88 h) [39], MSP430F5419A (monitoring for 48 h) [137], ATmega8 [41], ATmega328 [42], Arduino UNO (ATmega328) [47], ATmega8L [28, 31, 32], Concerto MCU [65], Revitive Device [27], PIC18LF4620 [69], Altera EP2C35 Nios II soft-core CPU based FPGA [138], ARM9 [139], ADuC842 [140], C8051F021 [141], 32-bit ARM Cortex M0 CPU (monitoring for 24 h) [30], and STM32 chip as the system controller with ARM Cortex-M3 core (monitoring for 44 h) [67] were used.…”

Section: Designing Of External Cardiac Loop Recordermentioning

confidence: 99%

An Engineering Perspective of External Cardiac Loop Recorder: A Systematic Review

Srinivasulu

Sriraam

2016

Journal of Medical Engineering

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External cardiac loop recorder (ELR) is a kind of ECG monitoring system that records cardiac activities of a subject continuously for a long time. When the heart palpitations are not the frequent and nonspecific character, it is difficult to diagnose the disease. In such a case, ELR is used for long-term monitoring of heart signal of the patient. But the cost of ELR is very high. Therefore, it is not prominently available in developing countries like India. Since the design of ELR includes the ECG electrodes, instrumentation amplifier, analog to digital converter, and signal processing unit, a comparative review of each part of the ELR is presented in this paper in order to design a cost effective, low power, and compact kind of ELR. This review will also give different choices available for selecting and designing each part of the ELR system. Finally, the review will suggest the better choice for designing a cost effective external cardiac loop recorder that helps to make it available even for rural people in India.

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A Wearable Wireless ECG Monitoring System With Dynamic Transmission Power Control for Long-Term Homecare

Cited by 30 publications

References 29 publications

ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges

ECG Monitoring Systems: Review, Architecture, Processes, and Key Challenges

A lightweight QRS detector for single lead ECG signals using a max-min difference algorithm

An Engineering Perspective of External Cardiac Loop Recorder: A Systematic Review

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