Accelerometer based motion noise analysis of ECG signal

Han, Dong-Kyoon; Hong, Ji-Heon; Shin, Jong-Il; Lee, T. S.

doi:10.1007/978-3-642-03904-1_56

Cited by 8 publications

(4 citation statements)

References 7 publications

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“…The SCG signal is affected by respiration in three ways: first, by shifting the SCG baseline due to the chest wall movement; second, by SCG amplitude variation caused by changes in pressure inside the chest; and third, through respiratory sinus arrhythmia in HRV [55]. Current research teams are either working on proposing extraction algorithms [56] or enhancing the quality through quantitative analysis of motion artifacts [57,58]. This involves utilizing an adaptive recursive least-squares filter [59] or time-frequency distribution analysis [60] or employing two cooperating accelerometers [54,61].…”

Section: Seismocardiography Ballistocardiography and Similar Methodsmentioning

confidence: 99%

Advances in Respiratory Monitoring: A Comprehensive Review of Wearable and Remote Technologies

Vitazkova,

Foltan,

Kosnacova

et al. 2024

Biosensors

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This article explores the importance of wearable and remote technologies in healthcare. The focus highlights its potential in continuous monitoring, examines the specificity of the issue, and offers a view of proactive healthcare. Our research describes a wide range of device types and scientific methodologies, starting from traditional chest belts to their modern alternatives and cutting-edge bioamplifiers that distinguish breathing from chest impedance variations. We also investigated innovative technologies such as the monitoring of thorax micromovements based on the principles of seismocardiography, ballistocardiography, remote camera recordings, deployment of integrated optical fibers, or extraction of respiration from cardiovascular variables. Our review is extended to include acoustic methods and breath and blood gas analysis, providing a comprehensive overview of different approaches to respiratory monitoring. The topic of monitoring respiration with wearable and remote electronics is currently the center of attention of researchers, which is also reflected by the growing number of publications. In our manuscript, we offer an overview of the most interesting ones.

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Section: Seismocardiography Ballistocardiography and Similar Methodsmentioning

confidence: 99%

Advances in Respiratory Monitoring: A Comprehensive Review of Wearable and Remote Technologies

Vitazkova,

Foltan,

Kosnacova

et al. 2024

Biosensors

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“…The thorax accelerometer signal contains a low-frequency component corresponding to the motion of the chest wall due to respiration and a higher-frequency component corresponding to the heartbeat. Actual research teams are either trying to develop extracting algorithms of these signals [73] or are focused on increasing the quality of daily-life ECG monitoring using quantitative analysis of motion artifacts [74,75]. In different studies, the quality of the obtained SCG is enhanced using a novel adaptive recursive least-squares filter [76], time-frequency distribution analysis [77], or even using two cooperating accelerometers [78].…”

Section: Inertial Measurement Units and Seismocardiographymentioning

confidence: 99%

Application of Modern Multi-Sensor Holter in Diagnosis and Treatment

Vavrinský

Subjak

Donoval

et al. 2020

Sensors

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Modern Holter devices are very trendy tools used in medicine, research, or sport. They monitor a variety of human physiological or pathophysiological signals. Nowadays, Holter devices have been developing very fast. New innovative products come to the market every day. They have become smaller, smarter, cheaper, have ultra-low power consumption, do not limit everyday life, and allow comfortable measurements of humans to be accomplished in a familiar and natural environment, without extreme fear from doctors. People can be informed about their health and 24/7 monitoring can sometimes easily detect specific diseases, which are normally passed during routine ambulance operation. However, there is a problem with the reliability, quality, and quantity of the collected data. In normal life, there may be a loss of signal recording, abnormal growth of artifacts, etc. At this point, there is a need for multiple sensors capturing single variables in parallel by different sensing methods to complement these methods and diminish the level of artifacts. We can also sense multiple different signals that are complementary and give us a coherent picture. In this article, we describe actual interesting multi-sensor principles on the grounds of our own long-year experiences and many experiments.

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“…Patient's physical activity such as walking, running, biking, etc. influence ECG data and often decrease its diagnostic quality due to motion artifacts [6]. In the current system, clinicians often have to guess certain patterns of motion artifacts based on their experience and expertise.…”

Section: Contextual Informationmentioning

confidence: 99%

Leveraging Multi-modal User-labeled Data for Improved Accuracy in Interpretation of ECG Recordings

Maharjan

Bækgaard

Bardram

2018

Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computi

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This paper presents our preliminary design of the Reaching the Frail Elderly Patient for Optimizing Diagnosis of Atrial Fibrillation (REAFEL) system that helps to improve accuracy in interpretation of Electrocardiography (ECG) recordings by leveraging multi-modal user-labeled data and other contextual information from mobile devices. We describe the methods to collect and visualize the data, discuss the challenges associated with the project and conclude the paper by outlining future work.

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Accelerometer based motion noise analysis of ECG signal

Cited by 8 publications

References 7 publications

Advances in Respiratory Monitoring: A Comprehensive Review of Wearable and Remote Technologies

Advances in Respiratory Monitoring: A Comprehensive Review of Wearable and Remote Technologies

Application of Modern Multi-Sensor Holter in Diagnosis and Treatment

Leveraging Multi-modal User-labeled Data for Improved Accuracy in Interpretation of ECG Recordings

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