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 Experiment Video

Updated: May 7, 2026

Home-Based Monitor for Gait and Activity Analysis
07:24

Home-Based Monitor for Gait and Activity Analysis

Published on: August 8, 2019

6.4K

Fall Warning Method Based on Multimodal Sensor Fusion and Gait Phase Detection.

Wenxuan Zhang, Qian Liang, Xiaohui Jia

    IEEE Journal of Biomedical and Health Informatics
    |March 3, 2026
    PubMed
    Summary
    This summary is machine-generated.

    Related Concept Videos

    You might also read

    Related Articles

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

    Sort by
    Same author

    Disruption of Histidine Biosynthesis Impairs Outer Membrane Stability and Intracellular Survival of <i>Brucella melitensis</i>, Resulting in Attenuated Virulence.

    Microorganisms·2026
    Same author

    Spatial architecture of autism pathogenesis reveals mosaic structural disarray during early development.

    Nature communications·2026
    Same author

    High-precision camera calibration via perspective distortion correction using a hybrid chessboard-circle target.

    Applied optics·2026
    Same author

    Structural and functional characterization of ZenX, a thermostable hydrolase involved in zearalenone detoxification.

    Enzyme and microbial technology·2026
    Same author

    Single-cell transcriptomics revealed molecular vulnerability in a human midbrain-like organoid model of Parkinson's disease.

    iScience·2026
    Same author

    Advances in understanding the Clostridial spore inner membrane.

    Archives of microbiology·2026
    Same journal

    Non-contact Heart Sound Measurement by Defocused Speckle Imaging.

    IEEE journal of biomedical and health informatics·2026
    Same journal

    TaxEL: Taxonomy-Enhanced Entity Representation Learning for Biomedical Entity Linking.

    IEEE journal of biomedical and health informatics·2026
    Same journal

    Multimodal Feature Prototype Learning for Interpretable and Discriminative Cancer Survival Prediction.

    IEEE journal of biomedical and health informatics·2026
    Same journal

    CrossSG-DTA: Synergizing Sequence Semantics and Graph Structures via Cross-Attention for Drug-Target Affinity Prediction.

    IEEE journal of biomedical and health informatics·2026
    Same journal

    FGCSA-Net: A Novel Framework for Medical Report Generation Via Fine-Grained Feature Preservation and Semantic Alignment.

    IEEE journal of biomedical and health informatics·2026
    Same journal

    Med-SORA: Symptom to Organ Reasoning in Abdomen CT Images.

    IEEE journal of biomedical and health informatics·2026
    See all related articles

    This study presents a novel fall warning system using fused sensor data for early imbalance detection in the elderly. The method enhances fall prevention by accurately identifying gait phases and overcoming data limitations.

    Area of Science:

    • Biomedical Engineering
    • Gerontology
    • Rehabilitation Science

    Background:

    • Falls pose significant risks to the elderly and those with mobility issues.
    • Early detection of imbalance during complex gait is vital for effective fall prevention.
    • Existing methods struggle with fall phase identification and real-world data scarcity.

    Purpose of the Study:

    • To develop an advanced fall warning system.
    • To improve early imbalance detection using multimodal sensor fusion and gait phase analysis.
    • To address the challenge of limited real-world fall data.

    Main Methods:

    • Utilized multimodal sensor fusion combining plantar pressure sensors and inertial measurement units.
    • Introduced a gait phase detection module for fine-grained gait cycle division.

    More Related Videos

    Design and Analysis for Fall Detection System Simplification
    08:05

    Design and Analysis for Fall Detection System Simplification

    Published on: April 6, 2020

    12.6K
    Author Spotlight: Innovations in iTUG Test for Enhanced Risk Assessment and Cognitive Insights
    05:26

    Author Spotlight: Innovations in iTUG Test for Enhanced Risk Assessment and Cognitive Insights

    Published on: October 25, 2024

    1.9K

    Related Experiment Videos

    Last Updated: May 7, 2026

    Home-Based Monitor for Gait and Activity Analysis
    07:24

    Home-Based Monitor for Gait and Activity Analysis

    Published on: August 8, 2019

    6.4K
    Design and Analysis for Fall Detection System Simplification
    08:05

    Design and Analysis for Fall Detection System Simplification

    Published on: April 6, 2020

    12.6K
    Author Spotlight: Innovations in iTUG Test for Enhanced Risk Assessment and Cognitive Insights
    05:26

    Author Spotlight: Innovations in iTUG Test for Enhanced Risk Assessment and Cognitive Insights

    Published on: October 25, 2024

    1.9K
  • Created a hybrid dataset of simulated and real fall data, using multiple linear regression for data mapping.

    • Main Results:

    • Achieved high performance metrics: 94.8% accuracy, 92.8% recall, and 94.2% precision.
    • Demonstrated stable performance in cross-subject and multi-scenario evaluations.
    • The proposed method effectively detects early imbalance features.

    Conclusions:

    • The multimodal sensor fusion approach offers a reliable and generalizable solution for fall prevention.
    • The hybrid dataset strategy effectively mitigates the problem of insufficient real-world data.
    • This system shows strong potential for enhancing the safety and independence of elderly individuals.