A new mouth guard could soon offer people with limited hand function a way to easily control devices such as computers, smartphones and wheelchairs.
The Mouth Guard, a one-of-a-kind opto-electronic bite control system, accurately and quickly translates complex bite patterns into instructions for controlling these types of electronic gadgets.
Various assistive technologies such as voice recognition, eye tracking, and brain-computer interfaces have been developed in recent years to help people, especially those with limited dexterity or neurological disabilities, control electronic devices. However, these technologies have limitations related to environmental interference, control accuracy, cost and maintenance.
To provide an alternative to existing assistive technologies, Liu Xiaogang, a professor in the Department of Chemistry, Faculty of Science, National University of Singapore, and his team successfully designed and demonstrated the smart mouthguard, which contains built-in pressure sensors to detect occlusal patterns. These models are translated into data inputs with 98% accuracy and can be used to control computers, smartphones and wheelchairs.
In addition to supporting human-computer interaction, the mouth guard can also be used for medical assistance, health care devices such as smart electronic skin and dental diagnosis.
Assistive technologies help promote the independence and autonomy of people with disabilities. Unfortunately, these technologies also have significant drawbacks.
For example, voice recognition requires a large operating memory and must operate in a low noise environment, while eye tracking requires a camera to be mounted in front of the user and is prone to fatigue. Although brain-computer interfaces have improved considerably in recent years, this technology is invasive and requires bulky wired instruments.
Bite force, often used as a parameter to assess masticatory (chewing) function, is a promising area that is not well understood or capitalized on. Because dental occlusion provides high-precision control and requires minimal skill, Liu and his team came up with a new concept of assistive technology using unique patterns of occlusal contacts.
Bite-based assistive technology
The research team first designed a sensor comprising a series of contact pads containing phosphors of different colors, substances that emit light in response to pressure. The network of contact pads is placed inside a flexible mouth guard.
Upon biting, the contact pads mechanically deform and emit light of 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 approximately 7 grams (about 0.01 pounds), the mouthguard requires less training experience compared to existing assistive technologies.
“Our bite-controlled optoelectronic system is able to translate complex bite patterns into data inputs with 98% accuracy. We have also demonstrated that our new sensors can distinguish between mechanical deformations, including strain, compression, and bending, making them applicable to multifunctional mechanical sensing applications, such as miniaturized force sensing, flexible electronics, artificial skin and dental diagnostics,” Liu said.
Each smart mouthguard currently costs 100 Singapore dollars (around US$70) to produce in the lab, and the team expects the cost to be significantly reduced in mass production. Although the current prototype is designed for well-aligned teeth, a mouthguard with an irregular arrangement of phosphorus-infused pads could be developed for users with different tooth patterns or for people who wear dentures.
The study appears in the journal Natural electronics.
The research team has filed a patent for this innovative technology and is exploring the possibilities of validating their device in a clinical setting, such as care centers or retirement homes. Meanwhile, the researchers are also looking at ways to improve their technology, such as faster data processing and training.
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