Using PPG Signals and Wearable Devices for Atrial Fibrillation Screening

Yang, Chengming; Veiga, César; Rodríguez-Andina, Juan J.; Fariña, José; Íñiguez, Andrés; Yin, Shen

doi:10.1109/tie.2018.2889614

Cited by 60 publications

(39 citation statements)

References 21 publications

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“…Photoplethysmography (PPG), as a noninvasive circulatory signal, is a highly popular alternative solution to ECG. The PPG technology is an optical technique that serves as an alternative to traditional ECG, which reflects ECG by measuring changes in the volume of blood vessels caused by beating heart [16,169]. PPG is a proven way to measure heart rate (HR), respiratory rate, tissue perfusion, and some vascular and heart diseases, which makes PPG technique very attractive in assessing vascular disease, especially for vascular aging, hypertension and atherosclerosis [170].…”

Section: The Trend Of Portability and The Eise Of Photoplethysmographmentioning

confidence: 99%

“…In recent years, the fast development of machine learning methods has brought new opportunities to medical signal analysis [13], making ECG analysis more intelligent and efficient [14]. At present, wearable medical devices in healthcare can even replace 12-lead ECG acquisition devices [15,16], which can detect some common cardiovascular diseases, such as atrial fibrillation, arrhythmia, and stress.…”

Section: Introductionmentioning

confidence: 99%

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Computational Diagnostic Techniques for Electrocardiogram Signal Analysis

Xie

Zhou

et al. 2020

Sensors

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Cardiovascular diseases (CVDs), including asymptomatic myocardial ischemia, angina, myocardial infarction, and ischemic heart failure, are the leading cause of death globally. Early detection and treatment of CVDs significantly contribute to the prevention or delay of cardiovascular death. Electrocardiogram (ECG) records the electrical impulses generated by heart muscles, which reflect regular or irregular beating activity. Computer-aided techniques provide fast and accurate tools to identify CVDs using a patient’s ECG signal, which have achieved great success in recent years. Latest computational diagnostic techniques based on ECG signals for estimating CVDs conditions are summarized here. The procedure of ECG signals analysis is discussed in several subsections, including data preprocessing, feature engineering, classification, and application. In particular, the End-to-End models integrate feature extraction and classification into learning algorithms, which not only greatly simplifies the process of data analysis, but also shows excellent accuracy and robustness. Portable devices enable users to monitor their cardiovascular status at any time, bringing new scenarios as well as challenges to the application of ECG algorithms. Computational diagnostic techniques for ECG signal analysis show great potential for helping health care professionals, and their application in daily life benefits both patients and sub-healthy people.

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Section: The Trend Of Portability and The Eise Of Photoplethysmographmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Computational Diagnostic Techniques for Electrocardiogram Signal Analysis

Xie

Zhou

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…At present, traditional approaches of visual method, sound method and oscillometric method are mainly used for body motion sensing and pulse monitoring, which exist many deficiencies of complex structure, complicated fabrication process, required external power, trained technicians, poor portability and compatibility, etc. (Yang et al 2019;Regev and Wulich 2019). Therefore, it is urgent to develop simple, dynamic, timely, sensitive, breathable, wearable and energy-sustainable pressure sensors for monitoring body motion and pulse wave.…”

Section: Physical Sensorsmentioning

confidence: 99%

Recent advances in cellulose-based membranes for their sensing applications

Fan

Zhang

Li³

et al. 2020

Cellulose

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In recent years, sensing applications have played a very important role in various fields. As a novel natural material, cellulose-based membranes with many merits can be served as all kinds of sensors. This review summarizes the recent progress of cellulose membranes as sensors, mainly focusing on their preparation processes and sensing properties. In addition, the opportunities and challenges of cellulose membrane-based sensors are also prospected. This review provides some references for the design of cellulose membrane materials for sensing applications in the future.

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“…Most of the studies include fewer than 100 volunteers. [19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34] Six studies had a study population of more than 100 subjects [35][36][37][38][39][40] ; the largest monitored 1617 volunteers in an ambulatory setting. 36 Rhythm characteristics in the study populations varied among studies.…”

Section: Study Populationsmentioning

confidence: 99%

Atrial fibrillation monitoring with wrist-worn photoplethysmography-based wearables: State-of-the-art review

Eerikäinen

Bonomi

Dekker

et al. 2020

Cardiovascular Digital Health Journal

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Early detection and diagnosis of atrial fibrillation (AF) is essential in order to prevent stroke and other severe health consequences. The challenges in diagnosing AF arise from its intermittent and asymptomatic nature. Wrist-worn devices that use monitoring based on photoplethysmography have been proposed recently as a possible solution because of their ability to monitor heart rate and rhythm for long periods of time at low cost. Long-term continuous monitoring with implantable devices has been shown to increase the percentage of detected AF episodes, but the additional value of wrist-worn devices has yet to be determined. In this review, we present the state of the art in AF detection with wrist-worn devices, discuss the potential of the technology and current knowledge gaps, and propose directions for future research. The state-ofthe-art methods show excellent accuracy for AF detection. However, most of the studies were conducted in hospital settings, and more studies showing the accuracy of the technology for ambulatory long-term monitoring are needed. Objective comparison of results and methodologies among different studies currently is difficult due to the lack of adequate public datasets.

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Using PPG Signals and Wearable Devices for Atrial Fibrillation Screening

Cited by 60 publications

References 21 publications

Computational Diagnostic Techniques for Electrocardiogram Signal Analysis

Computational Diagnostic Techniques for Electrocardiogram Signal Analysis

Recent advances in cellulose-based membranes for their sensing applications

Atrial fibrillation monitoring with wrist-worn photoplethysmography-based wearables: State-of-the-art review

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