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

Search research articles

Related Experiment Video

Updated: Jun 1, 2026

Memorization-Based Training and Testing Paradigm for Robust Vocal Identity Recognition in Expressive Speech Using Event-Related Potentials Analysis

Memorization-Based Training and Testing Paradigm for Robust Vocal Identity Recognition in Expressive Speech Using Event-Related Potentials Analysis

Published on: August 9, 2024

Enhanced Sign Language Recognition Using Weighted Intrinsic-Mode Entropy and Signer's Level of Deafness.

V E Kosmidou, P C Petrantonakis, L J Hadjileontiadis

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|June 11, 2011

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

Detecting fetal heart sounds by means of Fractal Dimension analysis in the Wavelet domain.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2017

Same author

Surface EMG analysis on normal subjects based on isometric voluntary contraction.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology·2007

Same author

Discrimination analysis of discontinuous breath sounds using higher-order crossings.

Medical & biological engineering & computing·2003

Same author

ECG data compression using wavelets and higher order statistics methods.

IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society·2001

Same author

An orthogonal least squares-based fuzzy filter for real-time analysis of lung sounds.

IEEE transactions on bio-medical engineering·2000

Same author

Enhancement of bowel sounds by wavelet-based filtering.

IEEE transactions on bio-medical engineering·2000

This study introduces a new method for sign language recognition by linking signing style to the signer's level of deafness (LoD). This approach enhances sign language classification accuracy, benefiting deaf communication systems.

Area of Science:

Biomedical Engineering
Signal Processing
Human-Computer Interaction

Background:

Sign language (SL) is crucial for deaf communication.
Accurate SL recognition systems are needed to bridge communication gaps.
Current systems may not fully account for individual signing variations.

Purpose of the Study:

To propose an enhanced sign language recognition method.
To incorporate the signer's level of deafness (LoD) into the recognition process.
To improve SL sign classification accuracy.

Main Methods:

A novel hybrid adaptive weighting (HAW) process was developed.
HAW utilized a LoD-driven genetic algorithm to weight signal intrinsic modes.
Surface electromyogram and 3-D accelerometer data were processed for feature extraction (wIMEn).

More Related Videos

Artificial Intelligence-Based System for Detecting Attention Levels in Students

Artificial Intelligence-Based System for Detecting Attention Levels in Students

Published on: December 15, 2023

Related Experiment Videos

Last Updated: Jun 1, 2026

Memorization-Based Training and Testing Paradigm for Robust Vocal Identity Recognition in Expressive Speech Using Event-Related Potentials Analysis

Memorization-Based Training and Testing Paradigm for Robust Vocal Identity Recognition in Expressive Speech Using Event-Related Potentials Analysis

Published on: August 9, 2024

Artificial Intelligence-Based System for Detecting Attention Levels in Students

Artificial Intelligence-Based System for Detecting Attention Levels in Students

Published on: December 15, 2023

Main Results:

The proposed weighted intrinsic-mode entropy (wIMEn) feature set showed superior performance.
wIMEn outperformed other feature sets in discriminating between signers and signs.
Enhanced accuracy was observed in signer identification, LoD-based group identification, and GSL sign classification.

Conclusions:

The novel wIMEn feature set significantly improves SL recognition.
Incorporating LoD into SL classification enhances system performance.
This approach can contribute to developing more effective, signer-independent SL recognition systems.