Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Pulse rhythm

Pulse rhythm

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 muscle...

Assessment of apical radial pulse

Assessment of apical radial pulse

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

Special considerations while measuring pulse

Special considerations while measuring pulse

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

Assessment of radial pulse

Assessment of radial pulse

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:

Pulse

Pulse

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 indicator...

Assessment of apical pulse

Assessment of apical pulse

Assessing the Apical Pulse
Assessing the apical pulse is a critical nursing procedure, particularly indicated for:

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Pulmonary fibrosis after COVID-19 is characterized by airway abnormalities and elevated club cell secretory protein-16.

JCI insight·2026

Same author

Signal in the Noise: Polygenic Scores and the Problem of Defining Idiopathic Pulmonary Fibrosis.

American journal of respiratory and critical care medicine·2026

Same author

Progressive Fusion of Multi-Scale Mamba Context and Local Detail Priors for Infrared Small Target Detection.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same author

Performance of Age-Adjusted Whole Genome Sequencing Telomere Length in Idiopathic Pulmonary Fibrosis.

American journal of respiratory and critical care medicine·2026

Same author

Carbapenem resistance mediated by <i>bla</i><sub>NDM-13</sub> in a highly drug-resistant <i>Salmonella</i> Stanley ST29 strain in China.

Microbiology spectrum·2026

Same author

Publisher Correction: Whole genome sequence analysis of pulmonary function and COPD in 44,287 multi-ancestry participants.

Genome biology·2026

Search research articles

Related Experiment Video

Updated: Jun 10, 2026

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver

Published on: June 27, 2025

Computerized wrist pulse signal diagnosis using modified auto-regressive models.

Yinghui Chen¹, Lei Zhang, David Zhang

¹Department of Computing, Biometrics Research Center, The Hong Kong Polytechnic University, Hong Kong, China.

Journal of Medical Systems

|August 13, 2010

Summary

This summary is machine-generated.

This study introduces a new time series analysis for wrist pulse signals to detect diseases. The method uses auto-regressive modeling and residual errors to accurately distinguish between healthy individuals and patients, showing high classification accuracy.

More Related Videos

Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression

Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression

Published on: December 10, 2014

Related Experiment Videos

Last Updated: Jun 10, 2026

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver

Published on: June 27, 2025

Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression

Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression

Published on: December 10, 2014

Area of Science:

Biomedical Engineering
Signal Processing
Health Informatics

Background:

Wrist pulse signals offer insights into physiological health status.
Pathological changes in the body manifest as alterations in pulse signals.
Existing methods may lack precision in disease detection from pulse waveforms.

Purpose of the Study:

To present a novel time series analysis approach for wrist pulse signal analysis.
To develop a method for distinguishing healthy individuals from patients using pulse signal characteristics.
To identify disease-sensitive features from wrist pulse data.

Main Methods:

A data normalization procedure using a 'closest' reference signal from healthy individuals.
Construction of an auto-regressive (AR) model based on the selected reference signal.
Definition of residual error (actual measurement vs. AR model prediction) as a disease-sensitive feature.

Main Results:

The proposed method achieved over 82% accuracy in distinguishing healthy individuals from patients with acute appendicitis.
Classification accuracy exceeded 90% for differentiating healthy individuals from patients with other diseases.
Demonstrated the effectiveness of the residual error as a disease-sensitive feature.

Conclusions:

The novel time series analysis approach shows significant promise for non-invasive disease detection.
Wrist pulse signal analysis using AR modeling can effectively identify pathological conditions.
The method provides a reliable tool for differentiating healthy subjects from patients based on pulse dynamics.