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Related Concept Videos

Special considerations while measuring pulse01:13

Special considerations while measuring pulse

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Assessing a patient's pulse is a fundamental skill in healthcare, but certain situations require special attention:
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Pulse rhythm01:30

Pulse rhythm

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Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac...
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Assessment of radial pulse01:11

Assessment of radial pulse

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Assessment of Radial Pulse
The radial pulse, located at the wrist, is often the preferred site for assessing peripheral pulse because of its accessibility and dependability. The process of determining the radial pulse involves several steps:
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Assessment of apical radial pulse01:25

Assessment of apical radial pulse

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Apical-Radial (A-R) Pulse Assessment
The A-R pulse assessment involves simultaneous evaluation of the apical and radial pulses. When the apical and radial pulse rates vary, this assessment helps identify a pulse deficit.
Pre-Procedural Preparation
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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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Assessment of apical pulse01:17

Assessment of apical pulse

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Assessing the Apical Pulse
Assessing the apical pulse is a critical nursing procedure, particularly indicated for:
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Evaluating the Pulse Rate Estimation Performance of the DS-EWMA Algorithm.

Rawan S Abdulsadig, Esther Rodriguez-Villegas

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    |December 3, 2025
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    Summary

    The dominance-scoring based and exponentially-weighted-moving-average driven (DS-EWMA) algorithm shows robust performance in estimating pulse rates from challenging photoplethysmography (PPG) signals, outperforming other methods during motion or with neck-based sensors.

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    Area of Science:

    • Biomedical Engineering
    • Signal Processing
    • Health Informatics

    Background:

    • Reliable vital signs monitoring, particularly heart rate estimation, is crucial for healthcare.
    • Photoplethysmography (PPG) signals are widely used for vital signs monitoring, especially in home settings.
    • The performance of PPG-based vital signs estimation heavily relies on the chosen algorithm and sensor placement.

    Purpose of the Study:

    • To evaluate the robustness and performance of the DS-EWMA pulse rate estimation algorithm.
    • To compare DS-EWMA against six state-of-the-art algorithms using diverse PPG datasets.
    • To assess algorithm performance under varying conditions, including stationary and motion-induced artifacts.

    Main Methods:

    • The dominance-scoring based and exponentially-weighted-moving-average driven (DS-EWMA) algorithm was evaluated.
    • Comparison involved six established algorithms: HeartPy, BioSPPy, Msptd, Qppg, Ampd, and Erma.
    • Performance was assessed using metrics like RMSE, MAE, STD, PCC, MAPE, and percentage accuracy across four PPG datasets.

    Main Results:

    • Under stationary conditions with finger PPG, HeartPy and Msptd generally showed superior performance.
    • DS-EWMA, Ampd, and Erma demonstrated moderate performance in stationary conditions.
    • DS-EWMA outperformed other algorithms significantly when analyzing noisy PPG signals (neck PPG, motion-affected finger PPG).

    Conclusions:

    • The DS-EWMA algorithm exhibits notable robustness, particularly in challenging PPG signal scenarios.
    • Existing algorithms like HeartPy, Qppg, and BioSPPy showed limitations with motion artifacts or non-ideal sensor locations.
    • Further refinement of the DS-EWMA method holds promise for improved vital signs monitoring accuracy.