Related papers: Spectral Statistics of RR Intervals in ECG
An arrhythmia, also known as a dysrhythmia, refers to an irregular heartbeat. There are various types of arrhythmias that can originate from different areas of the heart, resulting in either a rapid, slow, or irregular heartbeat. An…
In this paper, we propose an algorithm denoted as HeartBEAT that tracks heart rate from wrist-type photoplethysmography (PPG) signals and simultaneously recorded three-axis acceleration data. HeartBEAT contains three major parts: spectrum…
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Arrhythmia, an abnormal cardiac rhythm, is one of the most common types of cardiac disease. Automatic detection and classification of arrhythmia can be significant in reducing deaths due to cardiac diseases. This work proposes a multi-class…
Heart Rate Variability (HRV) measures the variation of the time between consecutive heartbeats and is a major indicator of physical and mental health. Recent research has demonstrated that photoplethysmography (PPG) sensors can be used to…
A reliable spectral analysis requires sampling rate at least twice as large as the frequency bound, otherwise the analysis will be unreliable and plagued with aliasing distortions. The RR samplings do not satisfy the above requirements and…
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Electrocardiogram signals are omnipresent in medicine. A vital aspect in the analysis of this data is the identification and classification of heart beat types which is often done through automated algorithms. Advancements in neural…
Except for a few specific types, cardiac arrhythmias are not immediately life-threatening. However, if not treated appropriately, they can cause serious complications. In particular, atrial fibrillation, which is characterized by fast and…
The HeartBert model is introduced with three primary objectives: reducing the need for labeled data, minimizing computational resources, and simultaneously improving performance in machine learning systems that analyze Electrocardiogram…
Any reliable biomarker has to be specific, generalizable, and reproducible across individuals and contexts. The exact values of such a biomarker must represent similar health states in different individuals and at different times within the…
We describe a method for analyzing the stochasticity in the non-stationary data for the beat-to-beat fluctuations in the heart rates of healthy subjects, as well as those with congestive heart failure. The method analyzes the returns time…
Respiration rate (RR) is an important vital sign for clinical monitoring of hospitalized patients, with changes in RR being strongly tied to changes in clinical status leading to adverse events. Human labels for RR, based on counting…
The classification of the electrocardiogram (ECG) signal has a vital impact on identifying heart-related diseases. This can ensure the premature finding of heart disease and the proper selection of the patient's customized treatment.…
A deformed dielectric microcavity is used as an experimental platform for the analysis of the statistics of chaotic resonances, in the perspective of testing fractal Weyl laws at optical frequencies. In order to surmount the difficulties…
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We test whether the complexity of cardiac interbeat interval time series is simply a consequence of the wide range of scales characterizing human behavior, especially physical activity, by analyzing data taken from healthy adult subjects…
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A famous result going back to Eric Kostlan states that the moduli of the eigenvalues of random normal matrices with radial potential are independent yet non identically distributed. This phenomenon is at the heart of the asymptotic analysis…
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