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

Sign Test for Matched Pairs

Sign Test for Matched Pairs

The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in...

You might also read

Related Articles

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

Sort by

Same author

CKD: Contrastive Knowledge Distillation for Cross-Dataset EEG Classification.

IEEE transactions on bio-medical engineering·2026

Same author

fastSeizureNet: Accurate and efficient knowledge-data fusion for semi-supervised seizure detection.

Neural networks : the official journal of the International Neural Network Society·2026

Same author

Mirror Descent Safe Policy Optimization for Reinforcement Learning Agents.

IEEE transactions on pattern analysis and machine intelligence·2026

Same author

Electroencephalography Enables Continuous Decoding of Hand Motion Angles in Polar Coordinates.

Cyborg and bionic systems (Washington, D.C.)·2026

Same author

Discovery of the reward function for embodied reinforcement learning agents.

Nature communications·2025

Same author

Magnetoencephalography (MEG) based non-invasive Chinese speech decoding.

Journal of neural engineering·2025

Same journal

Magnetic Resonance Spectroscopy Deep Learning with Magnetic Resonance Background Generator Enables In Vivo Metabolite Quantification of Hepatic Encephalopathy.

IEEE transactions on bio-medical engineering·2026

Same journal

Use of RPNIs and Implanted Electrodes for Prosthetic Wrist and Multi-Grip Hand Control during Functional Tasks: A Case Study.

IEEE transactions on bio-medical engineering·2026

Same journal

Healthy Limb Driven Prediction for Real Time Control of Unilateral Exoskeletons in Gait Rehabilitation.

IEEE transactions on bio-medical engineering·2026

Same journal

A Miniature Wearable Ultrasound System for Continuous Bladder Monitoring with Sleeping-Position-Robust Modeling Strategies.

IEEE transactions on bio-medical engineering·2026

Same journal

A Bi-objective Array Optimization Framework for Magnetocardiographic Source Imaging.

IEEE transactions on bio-medical engineering·2026

Same journal

A Dynamic Mutual Information Measure of Phase-Amplitude Coupling with Uncertainty Quantification.

IEEE transactions on bio-medical engineering·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Apr 2, 2026

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

SACM: SEEG-Audio Contrastive Matching for Chinese Speech Decoding.

Hongbin Wang, Zhihong Jia, Yuanzhong Shen

IEEE Transactions on Bio-Medical Engineering

|March 31, 2026

Summary

This summary is machine-generated.

This study introduces a new brain-computer interface (BCI) for decoding speech in Mandarin Chinese. The novel approach effectively translates speech intentions into spoken words, aiding communication for those with speech disorders.

More Related Videos

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

Published on: March 24, 2023

Sound Source Localization Testing in Single-sided Deafness Following Bone Conduction Intervention

Sound Source Localization Testing in Single-sided Deafness Following Bone Conduction Intervention

Published on: December 20, 2024

Related Experiment Videos

Last Updated: Apr 2, 2026

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

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

Published on: March 24, 2023

Sound Source Localization Testing in Single-sided Deafness Following Bone Conduction Intervention

Sound Source Localization Testing in Single-sided Deafness Following Bone Conduction Intervention

Published on: December 20, 2024

Area of Science:

Neuroscience
Biomedical Engineering
Speech Science

Background:

Speech disorders like dysarthria and anarthria significantly impact verbal communication.
Brain-computer interfaces (BCIs) offer a promising avenue for restoring speech through direct neural decoding.

Purpose of the Study:

To develop and evaluate a speech decoding BCI for Mandarin Chinese.
To propose a novel contrastive learning algorithm for enhanced speech decoding.

Main Methods:

Collected stereo-electroencephalography (SEEG) and audio data from ten epilepsy patients during a word-level reading task.
Developed the SEEG and Audio Contrastive Matching (SACM) algorithm, a contrastive learning approach.
Leveraged cross-modal correlations between neural activity and audio signals for speech segment decoding.

Main Results:

The SACM framework significantly surpassed random matching accuracy in both isolated and continuous speech decoding.
Outperformed SEEG-only baseline models across seven architectures in isolated-word decoding.
Demonstrated that a single ventral sensorimotor cortex electrode achieved performance comparable to a full electrode array.

Conclusions:

This work represents the first multimodal decoding approach for tonal speech BCIs.
The findings highlight the potential of SACM for developing effective speech neuroprostheses.