Updated: Feb 3
Modern, or smart, toothbrushes make a lot of promises; they provide different modes that help tackle different oral health issues, help detect and remove plaque, and even offer various gamification interfaces to help with proper engagement while brushing.
But one thing they have in common is that they give feedback after each toothbrushing session regarding your performance. One of the main components of said feedback is a visual representation of areas that have been brushed properly and those that have been omitted. And here’s where CNNs (Convolutional Neural Networks) and HAR (Human Activity Recognition) principles come in handy.
Applying them to toothbrushing data, following the assumption that brushing teeth in one of the areas can be treated as a separate sub-activity, can help recognize the area that is subject to brushing actions, based on the data from sensors placed inside the toothbrush’s handle. Thanks to this approach, we are able to recreate, analyze, and learn from our own toothbrushing patterns and habits. What’s more, this kind of data can be correlated to other physiological parameters and provide valuable insights regarding not only the state of our oral health but even the general one. Applying proper rule-based engines and ML (Machine Learning) models to such data can help us notice any changes in brushing habits, which may result in the early detection of certain diseases, including dental caries or periodontitis, and even systemic conditions, like diabetes.
All in all, although the potential applications of AI in dentistry have been shown in multiple studies and real-life scenarios, these systems are far from being able to replace dental professionals. Instead, the usege of AI should be viewed as a complementary asset to dentists, providing faster and more accurate diagnosis and related decision making. It is crucial to ensure its implementation and integration in a controlled and safe manner so as it doesn’t lead to careless decisions and missing out on crucial information when it’s the patient’s health that is at stake. The successful integration of AI in oral health care would require proper training and education of dental caregivers as well as caretakers. Knowledge of both advantages and dangers that come with certain technology is necessary to ensure its safe and successful implementation.
About Aceso ACESO is a patient-centric solution for smart and sustainable healthcare, employing a co-creative approach to realize integrated health and oral-care platform in which intelligent devices use data analytics for adaptable health and well-being. ACESO will monitor parameters related to physical health (blood pressure, glucose, heart rate, oxygen saturation, etc.), activity, sleep, and oral hygiene in an integrative manner which will provide primary users with personalized and adaptive feedback extracted by the underlying artificial intelligence engine. A patient-centric approach that actively involves users in maintaining their health will bring clear benefits for the elderly and caregivers. Aceso is funded by AAL. More about Aceso... About AAL AAL- Ageing Well in the Digital World - is a funding program that aims to create a better quality of life for older people and to strengthen industrial opportunities in the field of healthy aging technology and innovation. More about AAL. Contact: www.aal-aceso.eu/contact