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

Related Concept Videos

Strategies of Self-Presentation III: Self-Monitoring

Strategies of Self-Presentation III: Self-Monitoring

Self-monitoring is a central construct in understanding individual differences in self-presentation strategies across social contexts. It refers to how individuals observe, regulate, and control their expressive behavior and self-presentation following situational cues. Self-monitoring reflects a person's sensitivity to social appropriateness and willingness to adapt behavior to fit varying interpersonal demands.High vs. Low Self-Monitoring IndividualsIndividuals high in self-monitoring are...

Role-Based Identity

Role-Based Identity

Role-based identities are central to understanding how individuals navigate social environments by adopting distinct self-conceptions aligned with various societal roles. These identities are not fixed traits but are constructed through personal actions and the social feedback individuals receive in context-specific interactions. Each social role, such as student, teacher, or friend, carries a set of expectations and norms that influence how people think, feel, and behave within that...

Social Foundations of Self IV: Self in Digital Communication

Social Foundations of Self IV: Self in Digital Communication

Since the early 2000s, computer-mediated communication (CMC) has grown rapidly, playing a crucial role in self-development. A key distinction between CMC and real-life interactions is the lack of a physically present partner. This absence makes non-verbal cues such as facial expressions, body language, and paralinguistic signals unavailable in CMC platforms like email, instant messaging, or social media. The lack of these cues can create ambiguity and complicate how feedback is interpreted.The...

You might also read

Related Articles

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

Sort by

Same author

Early high-energy diet induces a systemic metabolic alteration in light weaning body weight piglets that persists after dietary normalization.

Archives of animal nutrition·2026

Same author

Histone methyltransferase KMT2D targets the SPOP-G3BP1 axis to enhance AR stability and drive castration-resistant prostate cancer progression.

Molecular biomedicine·2025

Same author

KMT2D deficiency potentiates antitumor immunity and sensitizes immune checkpoint blockade in urologic cancers.

The Journal of pathology·2025

Same author

Coherent emission of antimonide semiconductor laser arrays with a phase-locked Talbot cavity.

Optics express·2025

Same author

The RNA helicase DDX17 enhances androgen receptor stability by interacting with the E3 ubiquitin ligase SPOP in prostate cancer.

Translational andrology and urology·2025

Same author

High coupling efficiency wedge-shaped cylindrical lensed fiber for the 2 µm band.

Applied optics·2025

Search research articles

Related Experiment Video

Updated: Jan 13, 2026

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

WiMTI: A multitask learning model for WiFi-based identity and posture recognition.

Zhiyi Zhou¹, Xinxin Lu¹, Bingxian Lu¹

¹DUT School of Software Technology & DUT-RU International School of Information Science and Engineering, Dalian University of Technology, Dalian, Liaoning, China.

Neural Networks : the Official Journal of the International Neural Network Society

|October 29, 2025

Summary

This study introduces WiMTI, a novel multitask learning model for WiFi identity recognition. It simultaneously recognizes identity and posture, significantly improving accuracy despite posture changes.

Keywords:

Channel state information Identity and posture recognition Multitask learning WiFi-based sensing

More Related Videos

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

Related Experiment Videos

Last Updated: Jan 13, 2026

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

Published on: August 9, 2024

Area of Science:

Computer Science
Signal Processing
Machine Learning

Background:

WiFi-based identity recognition offers privacy-preserving, nonintrusive alternatives to camera or sensor systems.
Human posture variations critically degrade the accuracy and reliability of existing WiFi identity recognition methods.

Purpose of the Study:

To develop a robust WiFi-based identity recognition system resilient to posture variations.
To introduce a novel multitask learning (MTL) model for simultaneous identity and posture recognition.

Main Methods:

Proposed WiMTI, a multitask learning model for joint identity and posture recognition.
Employed dynamic cross-stitch units for adaptive feature fusion.
Integrated fractal dimension analysis for enhanced feature representation.

Main Results:

Achieved state-of-the-art average accuracies: 98.25% for identity recognition and 92.83% for posture recognition.
Demonstrated significant reduction in the negative impact of posture variations on identity recognition.

Conclusions:

WiMTI effectively addresses the challenge of posture variations in WiFi identity recognition.
The model's robustness and high accuracy make it suitable for practical applications like access control and caregiving.