UCLA Bioengineers Develop Wearable Device for Voice Disorder Treatment Using Machine Learning
Bioengineers at UCLA have developed a thin, flexible device that can help people with voice disorders regain the ability to speak. The device attaches to the neck and translates the movements of the larynx muscles into audible speech using machine learning. This self-powered technology could serve as a non-invasive tool for people who have lost their voice due to vocal cord problems, such as those recovering from laryngeal cancer surgeries or with pathological vocal cord conditions.
The device consists of two main components: a sensing component and an actuation component. The sensing component detects and converts signals generated by laryngeal muscle movements into electrical signals using a soft magnetoelastic mechanism. These electrical signals are then translated into voice signals using a machine learning algorithm. The performance component takes these speech signals and converts them into the desired speech expression. The thin and lightweight device can be easily attached to the throat area using biocompatible tape.
The researchers tested the wearable technology on eight healthy adults and achieved an overall prediction accuracy of 94.68% by translating laryngeal movements into corresponding sentences. In the future, the team plans to expand the device’s vocabulary using machine learning and test it on people with speech disorders. This portable, non-invasive solution could provide a convenient option for people receiving treatment or recovering from voice disorders, which affect nearly 30% of the population at some point in their lives.
Fountain: UCLA
