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

You might also read

Related Articles

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

Sort by
Same author

Harnessing the art of balance: Examining the effects of Tai Chi on creativity among art and design students.

Acta psychologica·2026
Same author

Road infrastructure drives habitat fragmentation and connectivity loss for large mammals in central iranian protected area.

Scientific reports·2026
Same author

Epidemiology of eyelid disorders in an elderly population: Tehran Geriatric Eye Study.

BMC ophthalmology·2026
Same author

Measuring children's spatial accessibility to urban park green spaces.

Scientific reports·2026
Same author

Immune-Mediated IgA Nephropathy Induced by PD-1 Blockade in Extranodal NK/T-Cell Lymphoma.

International medical case reports journal·2026
Same author

Can a self-regulated flipped classroom improve creative performance? Evidence from a randomized controlled trial.

Frontiers in psychology·2026

Related Experiment Video

Updated: Aug 3, 2025

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
06:58

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Published on: November 6, 2015

9.5K

Sensor Selection With Composite Features in Identifying User-Intended Poses for Human-Prosthetic Interfaces.

Tianshi Yu, Alireza Mohammadi, Ying Tan

    IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
    |April 8, 2023
    PubMed
    Summary

    This study introduces a new algorithm for selecting sensors in Human-Prosthetic Interfaces (HPIs). The Sensor Selection with Composite Features (SS-CF) algorithm optimizes sensor choice for better accuracy and simpler prosthetic systems.

    More Related Videos

    Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
    08:15

    Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

    Published on: March 28, 2025

    675
    A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
    11:06

    A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

    Published on: April 12, 2016

    10.5K

    Related Experiment Videos

    Last Updated: Aug 3, 2025

    A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
    06:58

    A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

    Published on: November 6, 2015

    9.5K
    Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision
    08:15

    Capturing Dynamic Finger Gesturing with High-resolution Surface Electromyography and Computer Vision

    Published on: March 28, 2025

    675
    A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation
    11:06

    A Human-machine-interface Integrating Low-cost Sensors with a Neuromuscular Electrical Stimulation System for Post-stroke Balance Rehabilitation

    Published on: April 12, 2016

    10.5K

    Area of Science:

    • Biomedical Engineering
    • Robotics
    • Human-Computer Interaction

    Background:

    • Human-Prosthetic Interfaces (HPIs) interpret user's intended limb movements using sensor data.
    • Conventional HPIs map individual sensor inputs to prosthesis degrees of freedom, limiting coordinated movement capture.
    • Advanced HPIs map multi-joint limb poses, requiring systematic sensor selection for accuracy and reduced complexity.

    Purpose of the Study:

    • To systematically formulate a sensor selection process for HPIs that maximizes information content for a given number of sensors.
    • To develop a method that accounts for composite features, which rely on information from multiple sensors for coordinated limb movements.
    • To improve the accuracy and reduce the complexity of prosthetic systems by optimizing sensor selection.

    Main Methods:

    • Formulated a non-convex optimization problem to select sensors, considering constraints imposed by composite features.
    • Utilized a projection matrix as an optimization variable for feature selection.
    • Developed the Sensor Selection with Composite Features (SS-CF) algorithm, employing convex-relaxation techniques to solve the optimization problem.

    Main Results:

    • The SS-CF algorithm was benchmarked against HPIs with expert-selected sensors and a greedy heuristic method.
    • The SS-CF algorithm demonstrated superior performance in selecting informative sensors for HPIs.
    • The study confirmed the efficacy of the SS-CF algorithm in optimizing sensor selection for capturing coordinated limb movements.

    Conclusions:

    • The proposed SS-CF algorithm effectively addresses the challenge of sensor selection in HPIs, particularly for capturing complex, coordinated movements.
    • This systematic approach enhances prosthetic system accuracy and efficiency by optimizing the use of sensor information.
    • The SS-CF algorithm provides a valuable tool for developing more sophisticated and intuitive prosthetic devices.