People who don’t have much use of their hands will soon be able to control computers, smartphones, and wheelchairs with ease by wearing a smart mouthguard. This mouthguard translates complex bite patterns into instructions for controlling electronic devices quickly and accurately.
This bite-controlled optoelectronic system is the first of its kind. It was created by a team of scientists led by Professor Liu Xiaogang from the Department of Chemistry at the National University of Singapore (NUS) Faculty of Science and including researchers from Tsinghua University.
In the past few years, different assistive technologies like voice recognition, eye tracking, and brain-computer interfaces have been made to help people control electronic devices, especially those with limited dexterity or neurological disorders. But these technologies have problems with how they interact with the environment, how well they control, how much they cost, and how hard they are to keep up.
Prof Liu and his colleagues have successfully built and tested a smart mouthguard with integrated pressure sensors to detect occlusal patterns as an alternative to existing assistive technologies. These patterns are translated with 98 per cent precision into data inputs and can be utilised to control computers, smartphones, and wheelchairs.
The interactive mouthguard can be utilised for medical aid, healthcare equipment such as smart electronic skin, and dental diagnosis in addition to facilitating a human-computer connection. Moreover, assistive technologies increase the freedom and autonomy of disabled individuals. Unfortunately, such technologies have substantial disadvantages as well.
Voice recognition, for instance, demands a big operational memory and a low-noise environment, whereas eye tracking requires a camera to be put in front of the user and is susceptible to weariness. Although brain-computer interfaces have advanced significantly over the past decade, this technology is intrusive and requires heavily connected devices.
Bite force, which is frequently employed as a metric to evaluate masticatory (chewing) function, is a promising but poorly understood and capitalised topic. As dental occlusion allows high-precision control and requires minimal skill, Prof Liu and his team devised a novel concept for assistive technology by employing unique occlusal contact patterns.
First, the research team made a sensor with a series of contact pads that had different coloured phosphors on them. Phosphors are substances that light up when pressure is put on them. The contact pads are put inside a mouthguard that can bend.
When you bite the contact pads, they change shape and light up in different colours and intensities. This can be measured and analysed using algorithms for machine learning. The data that is collected is then used to control and operate electronic devices like a computer, smartphone, or wheelchair with a high level of accuracy using a remote control.
The new mouthguard weighs about 7 grammes and is easier to learn to use than other assistive technologies. Prof Liu noted that the bite-controlled optoelectronic system can accurately transform complex biting patterns into data inputs with a 98 per cent degree of precision.
The research team also showed that the new sensors can tell the difference between strain, compression, and bending. This means that they can be used for a wide range of mechanical sensing applications, such as miniaturised force sensing, flexible electronics, artificial skin, and dental diagnosis.
The cost to make each intelligent mouthguard in the lab is presently S$100, and the team anticipates a significant reduction in price during mass manufacturing. Although the current prototype is built for teeth that are properly aligned, a mouthguard with an irregular arrangement of phosphor-infused pads might be developed for users with various dental patterns or those who wear dentures.
The study team has submitted a patent application for this new technology, and they are investigating options to evaluate their gadget in a clinical setting, such as hospitals or nursing homes. Simultaneously, the researchers investigate methods to improve their technology, such as faster data processing and training.
