Comparative Study on Heart Rate Variability Analysis for Atrial Fibrillation Detection in Short Single-Lead ECG Recordings

Nguyen, An; Ansari, Sardar; Hooshmand, Mohsen; Lin, K.M.; Ghanbari, Hamid; Gryak, Jonathan; Najarian, Kayvan

doi:10.1109/embc.2018.8512345

Cited by 10 publications

(9 citation statements)

References 13 publications

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“…Cortisol levels also declined, therefore, showing a tenuous anti-stress effect. In addition, sympathetic activity decreased and parasympathetic was enhanced, which means that our volunteers felt more relaxed in the wood environment [11,35].…”

Section: Discussionmentioning

confidence: 99%

“…Heart and respiration are also adaptable, and their parameters react to various environments. Sympathetic and parasympathetic activity shows the activity or tranquility of the human body [10,11,12]. Additionally, facial expressions and emotions were analyzed utilizing 4 IP (internet protocol) cameras strategically placed to cover all angles within the wooden waiting room and also the faces of the volunteers.…”

Section: Methodsmentioning

confidence: 99%

“…It provides the conditions for relaxation and rest. Low values of the LF/HF ratio mean relaxation and energy saving; vice versa, high values represent higher performance and body effort [11].…”

Section: Methodsmentioning

confidence: 99%

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Wood and Its Impact on Humans and Environment Quality in Health Care Facilities

Kotradyová

Vavrinský

Kaliňáková

et al. 2019

IJERPH

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The paper presents the application of natural materials, especially wood, which are relevant for human well-being in built environments of health, social, and day care facilities. These properties were tested by a complex methodology in a case study in the wooden waiting room at National Oncology Institute in Bratislava. In this space, experimental tests of physiological responses were further executed on 50 volunteers moving in the waiting room for 20 min. In this article, the EEG (electroencephalograph) (four persons) and emotions from the faces of all our volunteers before entering and after a stay in a wooden waiting room were recorded. Specifically, the ECG (electrocardiograph), heart rate (HR), and respiration activity were measured by using our own designed ECG holter (40 persons), and also blood pressure and cortisol levels were observed. The usage of wooden materials verifies their regenerative and positive impact on the human nervous system, through the appealing aesthetics (color, texture, and structures), high contact comfort, pleasant smell, possibility to regulate air humidity, volatile organic compound emissions (VOC-emissions), and acoustic well-being in the space.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Wood and Its Impact on Humans and Environment Quality in Health Care Facilities

Kotradyová

Vavrinský

Kaliňáková

et al. 2019

IJERPH

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“…If RR interval is greater than 2 s, this study marks the waveforms as noisy. In the context of HRV feature-based analysis, paper [34] describes a QRS detection algorithm called "gqrs" to generate HRV signals. For noise processing, this work uses the "double median filter" and the "taut string linear approximation method".…”

Section: P Wave-based Noise Classification Methodsmentioning

confidence: 99%

Noisy ECG Signal Data Transformation to Augment Classification Accuracy

Afzal¹,

Majeed²,

Ali³

et al. 2022

Computers, Materials &Amp; Continua

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In this era of electronic health, healthcare data is very important because it contains information about human survival. In addition, the Internet of Things (IoT) revolution has redefined modern healthcare systems and management by providing continuous monitoring. In this case, the data related to the heart is more important and requires proper analysis. For the analysis of heart data, Electrocardiogram (ECG) is used. In this work, machine learning techniques, such as adaptive boosting (AdaBoost) is used for detecting normal sinus rhythm, atrial fibrillation (AF), and noise in ECG signals to improve the classification accuracy. The proposed model uses ECG signals as input and provides results in the form of the presence or absence of disease AF, and classifies other signals as normal, other, or noise. This article derives different features from the signal using Maximal Information Coefficient (MIC) and minimum Redundancy Maximum Relevance (mRMR) technique, and then classifies them based on their attributes. Since the ECG contains some kind of noise and irregular data streams so the purpose of this study is to remove artifacts from the ECG signal by deploying the method of Second-Order-Section (SOS) (filter) and correctly classify them. Several features were extracted to improve the detection of ECG data. Compared with existing methods, this work gives promising results and can help improve the classification accuracy of the ECG signals.

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“…The first Holters were large, uncomfortable, and required a chest lead unit, including a radio broadcasting unit with an antenna system [3]. Thanks to technical progress, nowadays, Holters are small portable devices [4] with wireless signal transmission, integrated memory for data recording, and modern electrodes. They are used for patient monitoring in the comfort of their own home where they are not scared by doctors.…”

Section: Introductionmentioning

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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Comparative Study on Heart Rate Variability Analysis for Atrial Fibrillation Detection in Short Single-Lead ECG Recordings

Cited by 10 publications

References 13 publications

Wood and Its Impact on Humans and Environment Quality in Health Care Facilities

Wood and Its Impact on Humans and Environment Quality in Health Care Facilities

Noisy ECG Signal Data Transformation to Augment Classification Accuracy

Application of Modern Multi-Sensor Holter in Diagnosis and Treatment

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