Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Factors Influencing Heart Rate01:30

Factors Influencing Heart Rate

7.5K
The heart rate, or pulse rate, is a vital indicator of cardiovascular health. It reflects the number of times the heart beats per minute. Various physiological and environmental factors influence heart rate, increasing or decreasing cardiac output. Understanding these factors is crucial for assessing heart function and identifying potential health issues.
Let us explore the significant factors affecting heart rate, including age, body temperature, posture, acute pain, chemical influences,...
7.5K
Special considerations while measuring pulse01:13

Special considerations while measuring pulse

1.1K
Assessing a patient's pulse is a fundamental skill in healthcare, but certain situations require special attention:
1.1K
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

17.1K
The electrical signals recorded on an electrocardiogram (ECG) occur before the mechanical processes of contraction and relaxation during the cardiac cycle.
A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...
17.1K
Pulse Oximetry01:24

Pulse Oximetry

1.7K
Pulse oximetry, or SpO2, is a non-invasive method for continuously monitoring arterial oxygen saturation (SaO2). This procedure involves attaching a probe or sensor to the patient's fingertip, forehead, earlobe, or nose bridge. The sensor works by detecting changes in oxygen saturation levels through light signals generated by the oximeter and reflected by the pulsing blood under the probe.
Purpose
Average SpO2 values are greater than 95%. If the readings fall below 90%, it indicates that...
1.7K

You might also read

Related Articles

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

Sort by
Same author

Exploring the feasibility of modeling next-day fatigue and sleepiness using digital sleep tracker data in neurodegenerative and immune-mediated inflammatory diseases.

Frontiers in digital health·2026
Same author

[Perioperative complications during transvenous pacemaker and defibrillator implantation].

Herzschrittmachertherapie & Elektrophysiologie·2026
Same author

IDEA-FAST clinical study protocol: Identifying digital end-points of fatigue, sleep quality and daytime sleepiness in N = 2000.

Digital health·2026
Same author

A multi-ancestry genome-wide study of tamoxifen metabolism and breast cancer recurrence.

NPJ breast cancer·2026
Same author

Drug targeting of the monocarboxylate transporter MCT4 is a novel treatment strategy for metastatic ccRCC.

Pharmacological research·2025
Same author

Trial-Based Hemolysis Modeling to Investigate Operating Modes of Continuous-Flow LVADs.

Artificial organs·2025

Related Experiment Video

Updated: Apr 19, 2026

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring
06:32

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring

Published on: July 14, 2023

2.0K

Improvement of force-sensor-based heart rate estimation using multichannel data fusion.

Christoph Bruser, Juha M Kortelainen, Stefan Winter

    IEEE Journal of Biomedical and Health Informatics
    |January 7, 2015
    PubMed
    Summary

    Multichannel force sensors in beds significantly improve heartbeat interval estimation accuracy compared to single sensors. This advancement offers better sleep disorder monitoring through enhanced cardiac vibration signal analysis.

    More Related Videos

    Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
    08:22

    Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis

    Published on: April 26, 2024

    3.6K
    Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels
    08:19

    Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels

    Published on: October 20, 2023

    1.9K

    Related Experiment Videos

    Last Updated: Apr 19, 2026

    Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring
    06:32

    Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring

    Published on: July 14, 2023

    2.0K
    Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
    08:22

    Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis

    Published on: April 26, 2024

    3.6K
    Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels
    08:19

    Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels

    Published on: October 20, 2023

    1.9K

    Area of Science:

    • Biomedical Engineering
    • Signal Processing
    • Sleep Medicine

    Background:

    • Accurate heartbeat interval estimation is crucial for diagnosing sleep disorders.
    • Existing methods often rely on single-point sensors, limiting data richness.
    • Leveraging multichannel sensor data for cardiac monitoring presents a significant challenge.

    Purpose of the Study:

    • To develop and evaluate algorithms for estimating heartbeat intervals using multichannel force sensors integrated into a bed.
    • To investigate the advantages of multichannel sensing systems over single-channel solutions for cardiac monitoring.
    • To compare the performance of two novel multichannel algorithms against a single-channel baseline.

    Main Methods:

    • Two algorithms were developed: one using cepstrum analysis on averaged spectra, and another employing Bayesian fusion with autocorrelation on individual channels.
    • Evaluation utilized 28 night-long sleep lab recordings from patients with various sleep disorders.
    • An eight-channel polyvinylidene fluoride-based sensor array captured cardiac vibration signals; a virtual single-channel signal was created by averaging.

    Main Results:

    • The single-channel approach yielded a beat-to-beat interval error of 2.2% and 68.7% coverage.
    • The best multichannel algorithm achieved a mean error of 1.0% and 81.0% coverage.
    • These improvements in error and coverage were statistically significant (p < 0.05).

    Conclusions:

    • Multichannel force sensor systems offer a statistically significant improvement in heartbeat interval estimation accuracy and data coverage compared to single-channel systems.
    • The developed algorithms effectively leverage multichannel data for enhanced cardiac monitoring during sleep.
    • This technology holds promise for more accurate and comprehensive sleep disorder assessment.