AI Wearable Neck Patch Enables Speech Without Vocal Cords

Author: University of California, Los Angeles
Published: 15 Mar 2024 - Updated: 10 Aug 2026
Publication Details: Peer-Reviewed | Experimental Study

Table of Contents:
Synopsis - Definition - Overview - FAQs - Insights, Updates - Related Content

Synopsis

This article, a peer-reviewed experimental study from a reputable university, details the development of a novel, adhesive neck patch designed to translate laryngeal muscle movements into audible speech through advanced machine-learning technology. By attaching a soft, thin, and lightweight device to the skin near the throat, the system converts subtle muscle signals into clear vocal expressions with nearly 95% accuracy. This innovative technology presents a promising, non-invasive option for individuals with voice disorders resulting from conditions like laryngeal cancer surgeries or other vocal cord dysfunctions, and it holds significant potential to improve communication for people with disabilities, including seniors and those recovering from voice impairments.*

At a Glance

1 - The device measures 1.2 inches per side, weighs about 7 grams, and is just 0.06 inch thick.
2 - It adheres to the throat with double-sided biocompatible tape and can be reused by reapplying fresh tape.
3 - Testing on eight healthy adults reached an overall prediction accuracy of 94.68% across five spoken and voiceless sentences.
4 - The patch uses a soft magnetoelastic sensing mechanism developed by Chen's team in 2021, with serpentine copper induction coils generating high-fidelity electrical signals from muscle movement.

Topic Definition

Wearable Speech-Assistive Device: A wearable speech-assistive device is a compact, body-worn system that helps a person produce or restore audible speech when their natural voice is impaired or absent. In the UCLA design, a soft, stretchy patch adheres to the skin over the throat and works in two stages: a self-powered sensing component detects the tiny movements of the laryngeal muscles and converts them into electrical signals, and a machine-learning algorithm then matches those signals to intended words so an actuation component can play them back as spoken output. Because it reads muscle activity from outside the skin rather than requiring surgery, an implant, or a handheld electro-larynx, it offers a non-invasive alternative for people whose vocal cords no longer function normally, including those recovering from laryngeal cancer surgery or living with other voice disorders. As part of the broader field of wearable bioelectronics, devices like this aim to give users a practical, comfortable way to communicate both before and during treatment.

Overview

People with voice disorders, including those with pathological vocal cord conditions or who are recovering from laryngeal cancer surgeries, can often find it difficult or impossible to speak. That may soon change.

A team of UCLA engineers has invented a soft, thin, stretchy device measuring just over 1 square inch that can be attached to the skin outside the throat to help people with dysfunctional vocal cords regain their voice function. Their advance is detailed this week in the journal Nature Communications.

The new bioelectric system, developed by Jun Chen, an assistant professor of bioengineering at the UCLA Samueli School of Engineering, and his colleagues, is able to detect movement in a person's larynx muscles and translate those signals into audible speech with the assistance of machine-learning technology - with nearly 95% accuracy.

The breakthrough is the latest in Chen's efforts to help those with disabilities. His team previously developed a wearable glove capable of translating American Sign Language into English speech in real time to help users of ASL communicate with those who don't know how to sign.

The tiny new patch-like device is made up of two components. One, a self-powered sensing component, detects and converts signals generated by muscle movements into high-fidelity, analyzable electrical signals; these electrical signals are then translated into speech signals using a machine-learning algorithm. The other, an actuation component, turns those speech signals into the desired voice expression.

The wearable technology is designed to be flexible enough to move with and capture the activity of laryngeal muscles beneath the skin. — The wearable technology is designed to be flexible enough to move with and capture the activity of laryngeal muscles beneath the skin - Image Credit: Jun Chen Lab/UCLA.

The two components each contain two layers: a layer of biocompatible silicone compound polydimethylsiloxane, or PDMS, with elastic properties, and a magnetic induction layer made of copper induction coils. Sandwiched between the two components is a fifth layer containing PDMS mixed with micromagnets, which generates a magnetic field.

Utilizing a soft magnetoelastic sensing mechanism developed by Chen's team in 2021, the device is capable of detecting changes in the magnetic field when it is altered as a result of mechanical forces - in this case, the movement of laryngeal muscles. The embedded serpentine induction coils in the magnetoelastic layers help generate high-fidelity electrical signals for sensing purposes.

Measuring 1.2 inches on each side, the device weighs about 7 grams and is just 0.06 inch thick. With double-sided biocompatible tape, it can easily adhere to an individual's throat near the location of the vocal cords and can be reused by reapplying tape as needed.

Photo of a human neck with the device, a black adhesive square, attached outside the throat. — Photo of a human neck with the device, a black adhesive square, attached outside the throat - Image Credit: Jun Chen Lab/UCLA.

Voice disorders are prevalent across all ages and demographic groups; research has shown that nearly 30% of people will experience at least one such disorder in their lifetime. Yet with therapeutic approaches, such as surgical interventions and voice therapy, voice recovery can stretch from three months to a year, with some invasive techniques requiring a significant period of mandatory postoperative voice rest.

"Existing solutions such as handheld electro-larynx devices and tracheoesophageal- puncture procedures can be inconvenient, invasive or uncomfortable," said Chen who leads the Wearable Bioelectronics Research Group at UCLA, and has been named one the world's most highly cited researchers five years in a row. "This new device presents a wearable, non-invasive option capable of assisting patients in communicating during the period before treatment and during the post-treatment recovery period for voice disorders."

The two components, and five layers, of the device allow it to turn muscle movement into electrical signals which, with the help of machine learning, are ultimtately converted into speech signals and audible vocal expression. — The two components, and five layers, of the device allow it to turn muscle movement into electrical signals which, with the help of machine learning, are ultimtately converted into speech signals and audible vocal expression - Image Credit: Jun Chen Lab/UCLA.

How Machine Learning Enables the Wearable Tech

In their experiments, the researchers tested the wearable technology on eight healthy adults. They collected data on laryngeal muscle movement and used a machine-learning algorithm to correlate the resulting signals to certain words. They then selected a corresponding output voice signal through the device's actuation component.

The research team demonstrated the system's accuracy by having the participants pronounce five sentences - both aloud and voicelessly - including "Hi, Rachel, how are you doing today?" and "I love you!"

The overall prediction accuracy of the model was 94.68%, with the participants' voice signal amplified by the actuation component, demonstrating that the sensing mechanism recognized their laryngeal movement signal and matched the corresponding sentence the participants wished to say.

Going forward, the research team plans to continue enlarging the vocabulary of the device through machine learning and to test it in people with speech disorders.

About the Study

Other authors of the paper are UCLA Samueli graduate students Ziyuan Che, Chrystal Duan, Xiao Wan, Jing Xu and Tianqi Zheng - all members of Chen's lab.

The research was funded by the National Institutes of Health, the U.S. Office of Naval Research, the American Heart Association, Brain & Behavior Research Foundation, the UCLA Clinical and Translational Science Institute, and the UCLA Samueli School of Engineering.

A patent has been filed related to this work from the University of California, Los Angeles with US provisional patent application No. 63/176,651.

Frequently Asked Questions

NOTE: Researched FAQs by Disabled World (DW)

Can the device be used by people who have had their voice box removed

The study tested healthy adults and targets people with dysfunctional vocal cords, but because it reads laryngeal muscle movement, its usefulness after a full laryngectomy would need to be confirmed through further research.

How many words can the wearable patch currently recognize

The published work demonstrated a limited set of test sentences, and the team states it plans to enlarge the vocabulary over time through continued machine-learning training.

Does the device need an internet connection to work

The article does not specify connectivity requirements, describing instead an on-body sensing and actuation system paired with a machine-learning algorithm that interprets muscle signals.

Is the speech output in the user's own voice

The actuation component produces an audible voice signal matched to the intended words, but the article does not state that the output replicates the individual user's original voice.

Is the UCLA neck patch available to buy

No, it is described as a peer-reviewed experimental study with a filed patent, so it remains a research prototype rather than a commercial product at this stage.

What languages does the speech device support

The published experiments used English sentences, and the article does not mention support for additional languages, which would likely require further training data.

How is this patch different from a handheld electro-larynx

Unlike a handheld electro-larynx that a person holds against the neck, this is a lightweight adhesive patch worn on the skin that senses muscle movement and uses machine learning, offering a hands-free and non-invasive approach.

Insights, Analysis, and Developments

Editorial Note:

The development of this wearable speech-assistive device represents a major step forward in bridging the gap for individuals with vocal impairments. While still in its early stages, its high accuracy and non-invasive nature offer real hope for those who struggle with communication. Continued research and testing will be crucial in expanding its vocabulary and refining its capabilities, but this innovation could soon become an essential tool for people with voice disorders, providing them with a practical and effective way to express themselves

Attribution/Source(s): This peer reviewed publication was selected for publishing by the editors of Disabled World (DW) due to its relevance to the disability community. Originally authored by University of California, Los Angeles and published on 15 Mar 2024, this content may have been edited for style, clarity, or brevity.

* Editorial additions by Ian C. Langtree.