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Related Concept Videos

Increased pulse rate01:17

Increased pulse rate

1.2K
Tachycardia is a condition marked by an abnormally fast or irregular heart rate, surpassing the typical resting rate. In adults, tachycardia is characterized by a pulse rate ranging from 100 to 180 beats per minute. The increased heart rate can result in inadequate blood flow to various body parts, ultimately diminishing the oxygen supply to organs and tissues.
Many factors can elevate the risk of developing tachycardia. These include advanced age, a family history of arrhythmias, and an...
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Decreased pulse rate01:14

Decreased pulse rate

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Bradycardia is a medical condition in which the heart rate is slower than normal. It occurs when the heart's natural pacemaker, the sinus node, generates slower electrical impulses than the standard rhythm. In adults, bradycardia is diagnosed when the pulse rate falls below 60 beats per minute, indicating a deviation from the normal heart rate range.
There are specific risk factors that can elevate the likelihood of developing bradycardia. Advanced age is a significant factor, with...
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Pulse01:16

Pulse

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When the heart pumps blood out, arterial elastic fibers play a crucial role in sustaining a high-pressure gradient. They expand to accommodate the received blood and then recoil - a process known as the pulse that can be either manually palpated or electronically quantified. Despite a reduction in its effect with increased distance from the heart, elements of the pulse's systolic and diastolic components persist, observable even at the arteriole level.
The pulse serves as a clinical...
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Pulse01:05

Pulse

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The pulse is one of the most fundamental physiological indicators of the body's cardiovascular health. It is the rhythmic expansion and contraction of the arterial walls in response to the pressure generated by the heart's pumping action.
Pulse Rate and its Significance
Pulse rate, often measured in beats per minute (bpm), reflects the heart rate (HR), which is influenced by numerous factors such as stress, physical activity, and hormonal changes. A normal resting adult pulse rate falls...
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What are Estimates?01:06

What are Estimates?

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It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. 
The estimate for the mean of a sample is denoted by ͞x, whereas the mean of the population is designated as μ. Further, parameters such...
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Variability: Analysis01:11

Variability: Analysis

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Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
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Estimating Sediment Denitrification Rates Using Cores and N2O Microsensors
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Spectral Estimation Methods for Evaluating iPPG Pulse Rate Variability.

Daniel McDuff, Ethan Blackford, Justin Estepp

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    |November 17, 2018
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    Summary
    This summary is machine-generated.

    We compared two methods for analyzing pulse rate variability (PRV) from non-contact measurements. Bayesian Spectral Estimation excels at tracking PRV changes, while Lomb-Scargle handles missing data effectively.

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    Area of Science:

    • Physiological monitoring
    • Biomedical signal processing
    • Autonomic nervous system research

    Background:

    • Non-contact measurement of physiological parameters, such as pulse rate variability (PRV), is crucial for medical and affective computing applications.
    • PRV provides insights into autonomic nervous system activity.
    • Frequency-domain analysis of PRV requires spectral estimation from non-stationary and unevenly sampled data.

    Purpose of the Study:

    • To compare the performance of the Lomb-Scargle method and Bayesian Spectral Estimation for PRV computation.
    • To evaluate the suitability of these methods for analyzing non-contact photoplethysmography (PPG) data.

    Main Methods:

    • Comparison of PRV computation using Lomb-Scargle and Bayesian Spectral Estimation.
    • Utilized synthetic data and real non-contact imaging photoplethysmography (PPG) measurements.
    • Focused on spectral estimation techniques for unevenly sampled, non-stationary data.

    Main Results:

    • The Lomb-Scargle method demonstrated robustness in the presence of missing beats.
    • Bayesian Spectral Estimation showed advantages in tracking dynamic changes in PRV amplitude and frequency.
    • Both methods were applied to synthetic and real-world non-contact PPG data.

    Conclusions:

    • Both Lomb-Scargle and Bayesian Spectral Estimation are viable for PRV analysis.
    • Bayesian Spectral Estimation is superior for capturing temporal variations in PRV.
    • The choice of method depends on the specific requirements of PRV analysis, particularly concerning data completeness and dynamic tracking.