The smart mouthguard uses the bite to control all types of devices

A new mouthguard device may soon offer people with limited hand functionality a way to easily control devices such as computers, smartphones and wheelchairs.

The mouthguard, a first-of-its-kind optoelectronic bite control system, accurately and quickly translates complex bite patterns into instructions for controlling this type of electronic gadget.

In recent years, various assistive technologies such as speech recognition, eye detection and brain-computer interfaces have been developed to help people, especially those with limited dexterity or neurological disorders, to control electronic devices. However, these technologies have limitations associated with environmental interference, control accuracy, cost and maintenance.

To offer an alternative to existing assistive technologies, Liu Xiaogang, professor in the chemistry department of the National University of Singapore Faculty of Science, and his team successfully designed and demonstrated the smart mouthguard, which contains integrated pressure sensors for detect occlusal patterns. These models are translated into data input with 98% accuracy and can be used to control computers, smartphones and wheelchairs.

In addition to supporting human-computer interaction, the mouthguard can also be used for medical care, health devices such as smart electronic skin and dental diagnosis.

Less invasive

Assistive technologies help promote the independence and autonomy of people with disabilities. Unfortunately, such technologies also have significant disadvantages.

For example, speech recognition requires large operating memory and must work in a low noise environment, while eye detection requires a camera to be mounted in front of the user and is subject to fatigue. Although brain-computer interfaces have greatly improved in recent years, this technology is invasive and requires cumbersome wired tools.

Bite strength, often used as a parameter for assessing chewing (chewing) function, is a promising area that is not well understood or capitalized on. Since dental occlusion provides high-precision control and requires minimal skills, Liu and his team have come up with a new concept in assistive technology using unique patterns of occlusal contacts.

Bite-based assistive technology

The research team initially designed a sensor comprising a series of contact pads containing different colored phosphors, substances that emit light in response to pressure. The contact pad set is placed inside a flexible mouthguard.

The bite causes the contact pads to deform mechanically and emit light in different colors and intensities, which can be measured and processed using machine learning algorithms. The collected data is then used for high-precision remote control and operation of various electronic devices.

Weighing around 7 grams (around 0.01 lbs), the mouthguard requires less training experience than existing assistive technologies.

“Our bite control optoelectronic system is capable of translating complex bite patterns into data input with 98% accuracy. We have also shown that our new sensors can distinguish mechanical deformations, including deformation, compression and bending, making them applicable to multifunctional mechanical sensing applications, such as miniaturized force sensing, flexible electronics, artificial skin and dental diagnosis. “says Liu.

Each smart mouthguard currently costs S $ 100 (about $ 70 US) for lab production, and the team expects the cost to be substantially reduced in mass production. Although the current prototype is designed for well-aligned teeth, it is possible to develop a mouthguard with an irregular arrangement of phosphorus-infused pads for users with different tooth models or for people who wear dentures.

The study appears in the diary Nature electronics.

The research team has filed a patent for this innovative technology and is exploring opportunities to validate their device in a clinical setting, such as nursing centers or nursing homes. At the same time, researchers are also looking for ways to improve their technology, such as faster data processing and training.

Source: NUS

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