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

Pulse rhythm01:30

Pulse rhythm

1.6K
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...
1.6K
Holter Monitor: 24-Hour Monitoring01:23

Holter Monitor: 24-Hour Monitoring

4.6K
Holter monitoring is a continuous electrocardiography (ECG) recording that tracks the heart's electrical activity over an extended period, generally 24 to 48 hours. This noninvasive diagnostic tool detects irregular heart rhythms that may not be captured during a standard ECG performed in a clinical setting.DeviceThe Holter monitor is a portable, small device connected to several electrodes on the patient's chest. These electrodes detect the heart's electrical signals and transmit them to the...
4.6K
Heart Failure VII: Nursing Interventions01:30

Heart Failure VII: Nursing Interventions

732
The first step in nursing management of a patient with heart failure involves thoroughly assessing the patient's medical history.Subjective Data: Obtain the patient's medical history of coronary artery disease, hypertension, myocardial infarction, and symptoms like dyspnea, orthopnea, and paroxysmal nocturnal dyspnea.Objective Data: Conduct a physical examination to identify findings such as jugular vein distention, pulmonary crackles, tachycardia, murmurs, peripheral edema, and vital signs,...
732
Heart Failure IV: Classification and Diagnostic Evaluation01:30

Heart Failure IV: Classification and Diagnostic Evaluation

603
Heart failure can be classified in various ways, with the most common classifications based on physical activity limitations, disease progression, severity, and treatment strategies.The Functional Classification of Heart Failure divides patients into four categories based on physical activity limitation due to symptom burden.Class I: Patients in this class have cardiac disease but no physical activity limitations. Ordinary activities like walking, climbing stairs, or routine tasks do not cause...
603
Heart Failure V: Medical Management01:30

Heart Failure V: Medical Management

545
Medical Management of Acute Decompensated Heart Failure (ADHF)The primary goals of therapy for patients hospitalized with acute decompensated heart failure (ADHF) include:Relieving symptomsOptimizing volume statusSupporting oxygenation and ventilationMaintaining cardiac output (CO) and end-organ perfusionIdentifying and addressing the cause of ADHFPreventing complicationsProviding patient education on factors precipitating HF exacerbationPlanning for dischargeOngoing monitoring and assessment...
545
Rheumatic Heart Disease IV: Nursing Management01:20

Rheumatic Heart Disease IV: Nursing Management

453
AssessmentA comprehensive assessment is essential in managing a patient with rheumatic heart disease (RHD). Begin with obtaining a detailed medical history, including recent streptococcal infections, a history of rheumatic fever, or previously diagnosed rheumatic heart disease. Assess the patient for symptoms such as fever, chest pain, widespread joint pain (arthralgia), tachycardia, pericardial friction rub, muffled heart sounds, heart murmurs, peripheral edema, subcutaneous nodules, and...
453

You might also read

Related Articles

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

Sort by
Same author

Distinct Spectral and Directional Thalamocortical Network Dynamics Define Focal Seizure Evolution.

medRxiv : the preprint server for health sciences·2026
Same author

Exploring Temporal Dynamics in No-Reflow Assessment.

medRxiv : the preprint server for health sciences·2025
Same author

Comparing P300 flashing paradigms in online typing with language models.

PloS one·2025
Same author

Enhancing Ultrasound Image Quality Across Disease Domains: Application of Cycle-Consistent Generative Adversarial Network and Perceptual Loss.

JMIR biomedical engineering·2024
Same author

A Deep Learning Approach to Predict Recanalization First-Pass Effect following Mechanical Thrombectomy in Patients with Acute Ischemic Stroke.

AJNR. American journal of neuroradiology·2024
Same author

From Bench-to-Bedside: How Artificial Intelligence is Changing Thyroid Nodule Diagnostics, a Systematic Review.

The Journal of clinical endocrinology and metabolism·2024
Same journal

Comparative Evaluation of Pretrained Large Language Models for Suicide Risk Prediction from Clinical Notes in U.S. Veterans.

medRxiv : the preprint server for health sciences·2026
Same journal

Nocturnal Respiratory Rate and Variability Predict Long-term Mortality in Stable Outpatients with Cardiovascular Disease.

medRxiv : the preprint server for health sciences·2026
Same journal

MOSAIC: Methylation-Oriented Site Analysis and Information Classifier for Robust Epigenomic Classification of Acute Leukemia in Clinical Cohorts with Variable Tumor Purity.

medRxiv : the preprint server for health sciences·2026
Same journal

Risk beliefs, intensive digital information and demand for a new preventative health product in public clinics: Evidence from an experiment in Zimbabwe.

medRxiv : the preprint server for health sciences·2026
Same journal

Development of an automated, imaging-based preoperative screening model for early identification of malnutrition in an abdominal surgery cohort.

medRxiv : the preprint server for health sciences·2026
Same journal

A Pilot Project Leveraging Large Language Models for Automated Screening and Variable Extraction in Observational Studies.

medRxiv : the preprint server for health sciences·2026
See all related articles

Related Experiment Video

Updated: Apr 4, 2026

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
04:24

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

Published on: April 19, 2019

12.9K

Early Identification of Hospital Visit Risk in Heart Failure Using Wearable-Derived Data.

Vedrana Ivezić1,2,3, Jack Dawson4, Rose Doherty2

  • 1Biomedical AI Research Lab, University of California, Los Angeles, Los Angeles, USA.

Medrxiv : the Preprint Server for Health Sciences
|April 3, 2026
PubMed
Summary
This summary is machine-generated.

Wearable Fitbit data can predict hospital visits for heart failure patients. Lower activity and increased resting heart rate indicate higher risk, enabling early intervention.

More Related Videos

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
05:03

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function

Published on: December 11, 2019

9.2K
Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health
05:51

Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health

Published on: February 21, 2025

1.6K

Related Experiment Videos

Last Updated: Apr 4, 2026

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
04:24

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

Published on: April 19, 2019

12.9K
Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
05:03

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function

Published on: December 11, 2019

9.2K
Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health
05:51

Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health

Published on: February 21, 2025

1.6K

Area of Science:

  • Cardiology
  • Digital Health
  • Biomedical Engineering

Background:

  • Heart failure is a major cause of death.
  • Early identification of high-risk patients is crucial for intervention.
  • Wearable technology offers potential for continuous physiological monitoring.

Purpose of the Study:

  • To investigate if Fitbit data can identify physiological trends associated with heart failure hospital visit risk.
  • To assess the utility of wearable devices in predicting exacerbations.

Main Methods:

  • 249 individuals with heart failure were monitored for 180 days.
  • Participants used a Fitbit and wireless weight scale.
  • Three monitoring arms included devices only, devices with a mobile app, or devices with an app and financial incentives.

Main Results:

  • 51 participants experienced hospital visits.
  • Hospital visits correlated with reduced daily steps (p=.002) and increased symptom severity (p=.044).
  • Resting heart rate increased three days before a visit (p=.022), and lower baseline steps predicted higher visit probability (p=.003).

Conclusions:

  • Passive physiological monitoring using wearable devices can effectively identify patients at risk of health exacerbation.
  • Wearable technology holds promise for timely clinical interventions in heart failure management.