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Review

Artificial-Intelligence-Based Smart Toothbrushes for Oral Health and Patient Education: A Review

by
Vanshika Maini
1,†,
Rupanjan Roy
1,
Gargi Gandhi
1,
Aditi Chopra
1,*,† and
Subraya G. Bhat
2
1
Department of Periodontology, Manipal College of Dental Sciences, Manipal, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India
2
Department of Preventive Dental Sciences, Division of Periodontology, College of Dental Surgery, Iman Abdulrahman Bin Faizal University, Dammam 34212, Saudi Arabia
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Hygiene 2025, 5(1), 5; https://doi.org/10.3390/hygiene5010005
Submission received: 26 November 2024 / Revised: 19 December 2024 / Accepted: 3 January 2025 / Published: 4 February 2025
(This article belongs to the Section Oral and Dental Hygiene)
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Abstract

:
Artificial intelligence (AI) is one of the most promising technological advancements that have revolutionized the healthcare sector (medicine and dentistry). AI and its subsets, such as machine learning (ML), artificial neural networks (ANNs), and deep learning (DL), are being used in dentistry for data recording and management, patient education, radiographic interpretation, diagnosis, and treatment plans. AI and ML tools are commonly employed to improve oral hygiene and patient compliance. This narrative review paper discusses the innovations in AI-based plaque control aids (toothbrushes and interdental aids) that have improved overall health and patients’ hygiene compliance. We performed a literature search using different databases using the following keywords: “Artificial intelligence or machine learning or robots or robotics” AND “Toothbrush OR Smart toothbrush”. We included all the studies evaluating the use of any smart toothbrush, AI, or robotics for oral hygiene, plaque control, and patient education. AI-based smart toothbrushes helped patients to brush effectively by indicating the amount of pressure and the time taken for brushing, along with providing feedback on their brushing performance. Many microrobots can even recognize and automatically remove biofilm. Some AI-based smart toothbrushes are beneficial for children, patients with disabilities lack of manual dexterity, and neurological disorders. However, dental professionals choose AI-based smart toothbrushes for patients with poor oral hygiene and poor compliance for more effective control of oral diseases and to provide better health.

1. Introduction

Regular and effective tooth brushing is fundamental to maintaining good oral hygiene. Effective tooth brushing disrupts the microbial biofilm formed on the hard and soft tissue surface and prevents the onset of gingival and periodontal diseases [1]. However, the efficacy of plaque control depends on the kinds of tools we use for brushing; patient compliance and motivation to perform a meticulous brushing regimen; dexterity to hold and brush; and alignment of teeth [2]. Effective removal of plaque is also challenging, especially on the posterior, palatal, and lingual surfaces of teeth [3,4,5]. Many patients use an inappropriate brush head size, brushing technique, and duration of brushing, leading to poor oral health and poor overall health and well-being [3,4]. Studies have also noted that people without any dental background clean only up to 30–40% of their teeth via manual toothbrushing [4,5,6,7,8,9,10]. Physically and mentally challenged patients, hospitalized or bedridden patients, and individuals who lack manual dexterity often find plaque control difficult with manual toothbrushes [6].
To overcome these limitations and to improve oral health, over the years, many technological advancements and innovations have taken place (Figure 1). Artificial intelligence and robotics are some of the most promising technological advancements used in dentistry for improving oral health. AI is a field of science and technology that deals with the creation of artifacts and models that simulate human-like behavior. AI-based toothbrushes, AI apps, and microrobots for plaque removal have been developed. AI-based modifications have improved interdental cleaning tools, music, and indicators for brushing pressure and app-based brushing, while sensors have made our toothbrushes smarter [8]. AI-based smart toothbrushes are used to remind patients to brush, interpret brushing efficiency, and indicate the tooth surface that has not been cleaned properly [11]. Even with so many advancements in AI-based technology for oral hygiene and plaque control, to the best of our knowledge, no review has discussed the recent advancements in AI- and robot-based smart toothbrushes for plaque control. Hence, the present review aims to comprehensively discuss the type of AI- and robot-based smart toothbrushes for oral care, plaque control, and patient education. This narrative review is important as it will help dental professionals choose the most appropriate tool for plaque control and oral hygiene for their patients.

2. Method

A comprehensive literature search was performed in different databases (PubMed/MEDLINE, Scopus, Web of Science, Google Scholar) to collect relevant articles using the following keywords: “Artificial intelligence or machine learning or robots or robotics” AND “Toothbrush OR Smart toothbrush”. All systematic and narrative review articles and human in vivo (observational studies, longitudinal study design, randomized clinical trial comprising of interventional trials, cohort study, case-control study, and cross-sectional study), in vitro, and animal studies evaluating the use of any smart toothbrush, AI- or robotic-based tool for biofilm control were included for this review. The results of the searches run in the above-mentioned databases were compiled in the Mendeley reference manager (version 1.19.4) and duplicates were removed. Two members of the team (A.C. and R.R.) independently screened the articles to exclude those that did not report the use of smart toothbrushes for oral care. Studies, where any form of AI, robotics, ML, DL, or smart toothbrush using computer-generated apps/tools were used for oral hygiene education, plaque control, patient motivation, and plaque removal, were included. Any studies of AI-based tools that reported the type and nature of the smart toothbrush used for plaque control, mechanism of action of the smart toothbrush, and indication of its use were noted. The details are presented as a narrative review.

3. Results

A total of 1153 articles were screened initially, and based on the title and abstract, 1059 papers were excluded. Thus, a total of 94 papers were then included in the full-text screening. Upon full screening, only 70 papers (all observational, interventional, and reviews) were included in this narrative review (Figure S1). The results of this review are described as a narrative review as follows.

3.1. What Are the Components of AI Used in Smart Toothbrushes?

AI has various sub-components: machine learning (ML); artificial neural networks (ANNs); convoluted neural networks (CNNs); deep learning (DL); recurrent neural networks (RNNs); and long short-term memory models (LSTMs) [12,13,14,15,16,17]. These components have been incorporated in various ways to develop smart toothbrushes [12,13]. An ANN acts like the neurons in the brain, which act like stacks of perceptrons to create a machine that can recognize patterns, mimic those patterns, and deliver a desired outcome. Using these AI technologies, various types of smart toothbrushes have been developed for various applications.

3.2. What Are the Various Smart Brushes for Checking Brushing Position, Brushing Technique, Plaque Removal Efficacy, and Patient Education?

ANN, CNN, and DL models are widely employed in smart toothbrushes for the recognition of images, speech, motion, and manner of brushing [13,14,15,16,17,18,19]. These toothbrushes, along with virtual reality (VR) and augmented reality (AR), can visualize the brushing performance. They also provide real-time immediate feedback in the form of a graph or speech output via a smartphone. This helps to enhance patient education and provide an interactive toothbrushing experience. This type of monitoring and feedback can be shared with the dentist, who can gauge the patient’s motivation and compliance [20,21,22,23,24,25,26,27,28,29,30,31,32,33]. The AR-based training incorporated in the toothbrush can identify the area where plaque is still present via an image delivered to a smartphone. Some of the AI-based smart toothbrushes for checking the brushing position, technique, and plaque removal efficacy include the Oral-B iO, Plaqless Pro smart toothbrush, and ‘Ara toothbrush’.
The Ara toothbrush is the first AI toothbrush manufactured by Kolibre in 2017 [24,25,26,27,28,29,30,31]. The Ara connects to the phone via Bluetooth and records the brushing frequency, duration, and sites that are cleaned properly [24]. Colgate’s new Plaqless Pro smart toothbrush provides feedback to the patients and collects data related to brushing performance using a sensor placed inside the toothbrush itself [25,26,27]. Oral-B’s NEW GENIUS X toothbrush tracks the areas of brushing and brushing force in the mouth to generate personalized feedback via the Oral-B app. Individuals who brush forcefully can be prescribed pressure-sensor-based toothbrushes to prevent unwanted damage to the teeth and soft tissues in the oral cavity [28,29,30,31]. Some common examples of smart toothbrushes with pressure sensors include the Philips Sonicare 4100 power toothbrush, Philips Sonicare Diamond Clean Smart 9700 Rechargeable electric toothbrush, Oral-B Genius X White electric toothbrush, Oral-B i-O, and Oral-B Triumph with SmartGuide [32,33,34,35,36,37,38,39,40,41,42,43].
The Oral-B i-O is a smart toothbrush with a bimodal pressure sensor and linear magnetic drive to determine the brushing pressure [28,29,30,31,32,33]. The linear magnetic drive with O-R technology produces oscillating and rotating micro-vibrations from a controlled energy source that are directed to the bristle tip [34]. The “Tuft-in-Tuft” technology and smart pressure sensor help to brush with an optimal pressure range of 0.8–2.5 N. The sensor changes light according to the force applied: a green light indicates ideal brushing pressure (0.8–2.5 N) and a red light indicates pressure (>2.5 N). The users can also interact with the AI for guidance via a 2-min brushing session by using a 3D-tracking Oral-B iO app. Studies have compared Oral-B i-O smart toothbrushes with manual and sonic toothbrushes [28,29,30,31]. The first clinical study was by Grender et al., who found that subjects who brushed unsupervised with the Oral-B iO electric toothbrush had statistically significantly greater relative plaque and gingivitis reductions at the end of 8 weeks versus those using the manual toothbrush [31]. There were three times more “healthy” patients in the Oral-B iO group at eight weeks compared to those who used a manual brush (82% vs. 24%, respectively). Individuals who used the oral-B iO removed more plaque and had lower gingivitis scores compared to those who used manual toothbrushes [31]. Adam et al. (2020) also found a significant improvement in plaque removal efficacy and gingival health with Oral-B iO toothbrushes versus manual and sonic toothbrushes. Over 80% of subjects who used the Oral-B iO transitioned from “gingivitis” (≥10% bleeding sites) at baseline to “generally healthy” (<10% bleeding sites) at the end of eight weeks [34]. A study by Goyal et al. also noted a significant difference in the plaque removal efficacy for the Oral-B iO brush compared to the sonic brush (p < 0.001) [28,29]. Janusz (2008) conducted a randomized controlled trial to evaluate the ability of a powered toothbrush (Oral-B Triumph with “Smart-Guide”) with a pressure sensor to improve the brushing force and effectiveness of oral cleaning. The study found an 88.5% reduction in the pressure sensor activation time for the Oral-B Triumph at the end of 30 days compared to 53.4% for the powered brush, indicating the benefits of smart toothbrushes in improving the brushing technique [33].
Recently, a recurrent probabilistic neural network (RPNN), computer-based learning (CBL), SVM regression model, and decision tree algorithms (DTAs) have been incorporated into toothbrushes. An RPNN with nine-axis motion sensors helps to visualize patients’ brushing technique and position with 99.08% efficacy compared to other forms of AI [12] (Figure 2). The RPNN-based brush was trained to brush with any brushing technique, but still, some differences in the method of brushing, spacing between teeth, and manual dexterity among patients were noted. To overcome these variations and customize to the individual’s brushing habits, a smart brush called “Colgate hum” was developed. This toothbrush incorporates sensors that transmit the speed and angulation data of the brush via a Colgate app to the user and provide suggestions on how they can improve upon their brushing and achieve better brush placement. This brush also allows you to accumulate points upon good brushing, which acts as an incentive for purchasing any replacement brush heads [12,13,14,15,16]. Toothbrushing performance can also be noted using a speech recognition and SVM regression model by collecting data using an audio data collector via a smartphone. These models use AI technology to detect the brushing location and type of brush stroke using audio recognition, with accuracy ranging from 49% to 68% [41]. A study by Thurzo (2021) also evaluated the effect of computer-based learning (CBL) and decision tree algorithms (DTAs) on patient education and found that AI models provide better patient education than manual methods. These brushes have been synchronized to a mobile app (StrojCHECK®) that can take photos and videos of patients with their orthodontic appliances, helping to improve plaque control and providing measurable benefits when monitoring patients at home [38]. Shen (2022) found that home-based AI monitoring and counseling have a positive effect on treatment outcomes for patients with periodontitis. Patients who received AI-assisted health counseling at home exhibited better treatment outcomes than patients who received AI monitoring alone. The AI combined with human counseling showed more improvement in pocket depth, clinical attachment level, and plaque index [39]. Similarly, a study by Tonetti et al. (2020) evaluated the efficacy of intelligent power-driven toothbrushes for supportive periodontal-driven care programs connected to the app (I-Brush) [40]. The brushing periods and occurrence of bleeding on brushing were recorded in the app two weeks before the recall visit. The results showed that individuals who used the app had lower plaque scores at the supportive periodontal care (p < 0.001). This proved that the use of intelligent power toothbrushes during supportive periodontal care can be beneficial for maintaining good oral health [40].
The AI-based toothbrushes can be tried for oral hygiene maintenance among individuals with intellectual disabilities. Jeon et al. (2021) evaluated the tooth-brushing training efficacy using AR and smart toothbrushes in individuals with intellectual disability and found that individuals who used AI- and AR-based toothbrushes have a lower debris index, calculus index, and total oral hygiene scores compared to those with trained with a visual material [42]. Smart toothbrushes with AI can also be used for patients admitted to the intensive care unit. AI-powered analysis can aid the ICU staff in providing optimal oral hygiene to their patients [43]. Novenine “SMASH”, another type of smart toothbrush, was used to assess the mental health of individuals during the COVID-19 pandemic [44,45,46]. Novenine “SMASH” has an ultra-compact gas sensor that measures breath odor from exhaled air, and determines the condition of your mouth’s odor on a scale of four different colors. By linking it to an original app, the measured data can be quantified as an “oral score” and users can receive appropriate advice from dentists and dental hygienists based on data from intraoral photographs taken by the camera in the user’s brush [47].

3.3. Smart Toothbrushes for Children

Some smart toothbrushes are developed especially to improve the brushing technique and ensure optimal plaque control in children. Some of the AI-based toothbrushes for kids include the Colgate Magik smart toothbrush for kids, chatbots, 21-Day FunDee, 30-Day FunDee, Hum Kids by Colgate, and Blu smart Bluetooth-enabled kids toothbrush. Many AI-based toothbrushes incorporate the “m-Teeth model” that can detect more amounts of plaque compared with an experienced pediatric dentist [47,48]. The “m-Teeth model” brush uses a wrist-worn sensor to detect the micro-events of the brush and evaluate the brushing strokes [35,37]. Smartwatches are also being synchronized with toothbrushes to capture the movement of the hand and detect the direction of brushing and the brushing posture through a magnetometer attached to the toothbrush handle and a magnetic sensor present in the watch and provide feedback to the patient [36,37]. Huang et al. monitored a manual toothbrush using a wristwatch and found that smartwatches have a recognition rate of only 85.6%. The authors modified the manual toothbrush by attaching small magnets to the handle so that its orientation and motion can be captured by the magnetic sensor in the wristwatch [37,38,39,40,41,42,43,44,45,46,47,48,49,50,51]. An intelligent toothbrush with a vision-based tracker that uses a color-based algorithm has also been tried in young children who may not brush their teeth and pretend to brush [24]. This toothbrush has three sub-trackers that detect and track the person’s face, locate the person’s mouth to know if the person is brushing the teeth, and follow the actual toothbrush [24,48,49,50,51,52,53]. Pithpornchaiyakul (2022) evaluated the effectiveness of “2 chatbots; 21-Day FunDee and 30-Day FunDee” to improving the toothbrushing behaviors of caregivers in oral hygiene care for children (6 to 36 months) without in-person training during the COVID-19 pandemic [49]. The results showed that these AI-based toothbrushes significantly increase toothbrushing for children by caregivers [49]. Marcon et al. (2016) also conducted a study to analyze the toothbrushing movements using a smartphone and found that the use of an AI toothbrush linked to a smartphone can help children learn the correct method of brushing [50]. The smartphone display can be used as a “virtual mirror”, where the image of the person using the toothbrush can be replaced by an avatar based on facial feature tracking. This can mimic gestures and expressions and point out incorrect hand movements while brushing [52,53,54]. The “Playful Toothbrush” is another toothbrush for training children in the correct technique for brushing. This toothbrush has a vision-based motion tracker that recognizes different brushing strokes along with a brushing game and projects the virtual image of a child’s uncleaned teeth on the LCD. When the kids start brushing, the uncleaned tooth, which initially appears as “1” on the screen, turns to “2”. Each proper brush stroke also produces a graphic representation of a removed plaque layer, accompanied by audio feedback composed of notes on the diatonic scale, starting with “Do”. An incorrect brushing technique elicits no response. After all the seven notes (Do, Re, Mi, Fa, So, La, and Ti) on the diatonic scale are heard, this helps the child to thoroughly clean the virtual uncleaned teeth using his/her physical tooth-brushing motions as input. Chang (2008) conducted a study to assess the efficacy of a “playful toothbrush” in improving the effectiveness of brushing in kids by measuring the number of brush strokes, duration of brushing, and thoroughness of cleaning [54]. The study found a significant difference (p < 0.1) in teeth-cleaning effectiveness between the pretest phase (without a playful toothbrush) and training/post-test phases (with a playful toothbrush) at the end of seven days [52,53,54,55,56,57]. The “Tooth Tunes” is another smart toothbrush that utilizes musical tunes to teach tooth brushing to children [53,54,55,56,57]. This toothbrush is also embedded with small pressure sensors that can recognize brushing activity. When the sensors are activated, a two-minute musical clip is played to encourage the user to brush for at least two minutes. The Mouth Band is another interesting toothbrush for children that turns your toothbrush into a musical instrument. Three minutes of music is played according to the user’s brushing style. It is also possible to brush to one of the user’s favorite tunes as well. Furthermore, one can also listen to the news using the Mouth News reads while brushing [53,54,55,56]. The “Mouth Monster” is an app-based brushing tool that works like a video game and allows the users to play with characters designed.
The “Smart-Guide” and “G.U.M Play” are examples of toothbrushes that work on similar principles and recognize brushing actions by counting brushing strokes on a display showing how much time a user has brushed for or still needs to brush in each quadrant [32]. The “G.U.M Play” has a sensor-based toothbrush that can measure the rotation, angle, and speed of the brush using two components, referred to as “mouth check” and “mouth log”. The “mouth check” assesses the brushing based on how similar the movement of the brush is to the model brushing of a professional dental hygienist. The “mouth log” records the style and duration of toothbrushing.

3.4. Microrobot-Based Smart Toothbrush for Biofilm Removal

Various forms of chemical microrobots are being tested and used in the form of mouthwash or paste for biofilm removal [55,56]. These small and tubular microrobots, which are composed of biocompatible materials like titanium dioxide and platinum (Pt) nanoparticles, work on the principle of “bubble propulsion” or diffusiophoresis. The microrobots are composed of iron oxide nanoparticles with catalytic and magnetic properties. They cause the catalytic decomposition of hydrogen peroxide (H2O2) into water (H2O) and oxygen (O2) by platinum (Pt). The catalytic reaction helps to release antimicrobials that eliminate harmful oral bacteria (Figure 3). Some microrobots that are composed of iron oxide nanoparticles utilize the “robotic swarm technology”, also known as “shapeshifting microrobots”, to alter the configuration under a magnetic field. These microrobots can mold to form bristle-like structures while brushing and change to a thread-like configuration to act like floss. These robots play an effective role in removing plaque biofilm from a wide area of the tooth surface, including the interdental area (Figure 4).
Oh et al. (2022) used a magnetic-field-directed assembly of nanoparticles to develop ‘surface topography-adaptive robotic superstructures (STARS)’. The “STARS” were tried for precision-guided biofilm removal and diagnostic sampling. The STARS could retract or extend to varying lengths, shapes, and stiffness, which could be used to remove biofilm from narrow angles fissures, pits, crevices, grooves, and interdental areas around teeth. These microrobots could also capture images of microorganisms, disrupt the matrix components of biofilm, collect plaque samples for microbial analysis, and help deliver antimicrobial agents [20]. Babeer et al. (2021) also analyzed three-dimensional micro-molded opacifier-infused aggregated nanoparticles, known as “micro-swarms”, to visualize the root canal, enter the gingival sulcus, and implant in a controlled manner. These “micro-swarms” also helped to remove the biofilm and recover the samples of the biofilm for microbial analysis [21]. These microrobots have been compared to manual methods of periodontal debridement [54,55].

3.5. Automatic Hands-Free Brushes and Self-Disinfecting Brushes

The Amabrush is the world’s first fully automatic toothbrush, a revolutionary hands-free brush that brushes all the teeth in a mere 30 s. The Amabrush uses a U-shaped single-piece to brush in a circular motion with several directions on the tooth surface for plaque removal [54,55]. Nieri et al. (2020) conducted a study to assess the efficacy of a U-shaped automatic electric toothbrush compared to a powered toothbrush and manual toothbrushing for biofilm removal [55]. The results were statistically different between the automatic brush and powered brush, favoring the powdered brush. However, automatic and manual brushing also favored the manual group. The differences between treatments in terms of the clean-mouth VAS were statistically significant (p < 0.0001), favoring powered and manual toothbrushing [55]. However, one should note that limited studies confirmed the efficacy and advantage of these smart toothbrushes over manual toothbrushes. This could be related to the difference in the Hasbro that also helps to improve the brushing habits and teach the right method and duration of brushing through playful experiences.
Some toothbrushes also come with inbuilt technology to indicate if there is any contamination of the bristles due to plaque build-up and have self-cleansing mechanisms using ultraviolet light [56,57,58]. A toothbrush named “Lumio” utilizes retractable head technology and a self-cleaning toothbrush utilizes UV radiation to kill around 99.9% of germs on its bristles [57]. Another smart brush, known as “Bristl”, works on the same principle, where it uses three types of light (blue, red, and purple) to kill bacteria on the teeth and gums. The “Bristl” comes with a dual-mode light therapy, which is near-UV blue light mode and infrared red-light mode, and dual mode, which combines both UV and infrared. The blue light can kill the bacteria in the mouth that would cause gum disease and whiten teeth. The red light stimulates collagen secretion and aids in tissue regeneration. Purple light is a combination of blue and red light and is used to kill germs and strengthen the gingival tissue. The LED light can reduce the bacterial count by up to 95% compared to mechanical/chemical treatment for cleaning the toothbrush [58,59,60].

3.6. Clinical Recommendations and Limitations of AI-Based Toothbrushes

AI is rapidly changing the way we can educate our patients and achieve good plaque control. Although these toothbrushes are found to be better than manual toothbrushes, one should note that these toothbrushes should not be the first choice for all patients. Toothbrushing training using AR and smart toothbrushes should be tried only for those who are not improving their oral hygiene care, even after repeated personal and professional efforts. Additionally, initial education should be provided using a manual toothbrush with a standard oral hygiene regime and brushing technique for all patients. If the patient is unable to follow the instructions due to any problems in compliance, motivation, or dexterity, switching to a smart toothbrush can be tried. AI-based toothbrushes should be tried for the pediatric population and in people with intellectual disabilities who are unable to maintain good oral hygiene due to a lack of manual dexterity and reduced mental acuity [26]. These toothbrushes would also make plaque control easier for the caregiver, and they would reduce the time required for effective oral hygiene maintenance. Integrating smart toothbrushes into an oral hygiene regime would help to improve oral care and, in turn, prevent complications in children compared to adults and mentally challenged, critically ill, and hospitalized patients. As these patients lack sufficient manual dexterity and intellect to maintain oral hygiene, the use of these smart toothbrushes should always be preferred over manual brushes to achieve good oral hygiene [43]. However, dentists should conduct in-office training and patient education for all their patients before prescribing these smart toothbrushes. Regular follow-up and assessment of patient satisfaction and patient-reported outcomes regarding the ease of use, satisfaction, and effect on oral health and hygiene should be recorded. AI-based toothbrushes are expensive and many patients may have financial constraints when buying them. These toothbrushes rely on technology, including batteries, sensors, and connectivity. If these components fail, the toothbrush’s effectiveness may be compromised. They can be complex to set up and use. Users may need to navigate through smartphone apps, connect via Bluetooth, and understand various settings. Additionally, patient occlusion, alignment of teeth, spacing or gaps between teeth, and nature of enamel (hardness and existing defect in enamel/dentin, i.e., amelogenesis of imperfect/brittle teeth, hypoplasia) should also be assessed before using any AI-based toothbrushes. Patients should also be trained and have the required technology (smartphones) to effectively understand how best they can benefit from these smart toothbrushes. One should also consider the environmental impact of producing and disposing of high-tech toothbrushes, which may have a shorter life cycle than traditional brushes. This aspect is crucial, considering the increasing global focus on sustainable practices. We would also like to highlight that the limitations of this review are as follows. Firstly, this review is narrative in nature, with the search limited to English papers, and this could lead to the presence of selection bias. The risk assessment of individual studies has not been performed. The main objective of this review was to spread awareness among the public and clinicians regarding the availability of and indications for newer technology for oral hygiene and plaque control.

4. Conclusions

AI and robotics have revolutionized the field of dentistry. AI, ML, and microrobots have changed the way we can educate our patients and achieve better plaque control. Adequate knowledge, awareness, and acceptance of these newer and rapidly changing technologies by both dentists and patients are important, as it would be a good step toward controlling the rapidly growing burden of oral disease.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/hygiene5010005/s1, Figure S1: Flowchart for the search selection process.

Author Contributions

Conceptualization and ideas: V.M., R.R., G.G., A.C. and S.G.B.; methodology development or design of methodology: V.M., R.R., G.G. and A.C.; software and programming: V.M., R.R. and A.C.; validation: A.C. and G.G.; formal analysis: V.M., R.R., G.G., A.C. and S.G.B.; investigation, performing the experiments, or data/evidence collection: V.M., R.R., G.G., A.C. and S.G.B.; data curation: A.C. and S.G.B.; writing—original draft: V.M., R.R., G.G. and A.C.; writing—review and editing and preparation: V.M., R.R., A.C. and S.G.B.; visualization (figures): V.M., G.G. and A.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data will be available upon request via email from the corresponding author.

Conflicts of Interest

The authors have no conflicts of interest.

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Figure 1. Schematic representation of different types of smart toothbrushes and their associated technologies.
Figure 1. Schematic representation of different types of smart toothbrushes and their associated technologies.
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Figure 2. A prototype of a smart toothbrush based on the recurrent probabilistic neural network (RPNN) model, nine-axis inertial sensor MPU -9255, and Bluetooth 4.2 for syncing to a smartphone. The basic working mechanism of a smart toothbrush with defined 3-dimensional coordinates wherein the toothbrush is facing upwards. A nine-axis inertial sensor is used to identify brushing motions and send this signal via Bluetooth to the user’s mobile phone. This concept of ANN/ML has been incorporated into toothbrushes. The toothbrush’s and the user’s movements are closely combined to train the toothbrush and mimic those movements. The data extracted by the sensor needs to be used to accurately identify the user. Different from traditional human motion recognition methods, deep learning does not need to extract features manually. It can input unmarked data as features. Since the data collected by sensor data are time series data, some studies have proposed using convolution. The convolutional neural network (CNN) and the long short-term memory (LSTM) model are used to identify sensor data.
Figure 2. A prototype of a smart toothbrush based on the recurrent probabilistic neural network (RPNN) model, nine-axis inertial sensor MPU -9255, and Bluetooth 4.2 for syncing to a smartphone. The basic working mechanism of a smart toothbrush with defined 3-dimensional coordinates wherein the toothbrush is facing upwards. A nine-axis inertial sensor is used to identify brushing motions and send this signal via Bluetooth to the user’s mobile phone. This concept of ANN/ML has been incorporated into toothbrushes. The toothbrush’s and the user’s movements are closely combined to train the toothbrush and mimic those movements. The data extracted by the sensor needs to be used to accurately identify the user. Different from traditional human motion recognition methods, deep learning does not need to extract features manually. It can input unmarked data as features. Since the data collected by sensor data are time series data, some studies have proposed using convolution. The convolutional neural network (CNN) and the long short-term memory (LSTM) model are used to identify sensor data.
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Figure 3. Mechanism of action of chemical microrobots and their role in plaque control. Chemical microrobots work by catalytic decomposition of hydrogen peroxide (H2O2) into oxygen (O2) and water (H2O) by platinum (Pt) nanoparticles on the inner surface.
Figure 3. Mechanism of action of chemical microrobots and their role in plaque control. Chemical microrobots work by catalytic decomposition of hydrogen peroxide (H2O2) into oxygen (O2) and water (H2O) by platinum (Pt) nanoparticles on the inner surface.
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Figure 4. Toothbrushing microrobots (shapeshifting microrobots) using swarm technology to change their shape.
Figure 4. Toothbrushing microrobots (shapeshifting microrobots) using swarm technology to change their shape.
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Maini, V.; Roy, R.; Gandhi, G.; Chopra, A.; Bhat, S.G. Artificial-Intelligence-Based Smart Toothbrushes for Oral Health and Patient Education: A Review. Hygiene 2025, 5, 5. https://doi.org/10.3390/hygiene5010005

AMA Style

Maini V, Roy R, Gandhi G, Chopra A, Bhat SG. Artificial-Intelligence-Based Smart Toothbrushes for Oral Health and Patient Education: A Review. Hygiene. 2025; 5(1):5. https://doi.org/10.3390/hygiene5010005

Chicago/Turabian Style

Maini, Vanshika, Rupanjan Roy, Gargi Gandhi, Aditi Chopra, and Subraya G. Bhat. 2025. "Artificial-Intelligence-Based Smart Toothbrushes for Oral Health and Patient Education: A Review" Hygiene 5, no. 1: 5. https://doi.org/10.3390/hygiene5010005

APA Style

Maini, V., Roy, R., Gandhi, G., Chopra, A., & Bhat, S. G. (2025). Artificial-Intelligence-Based Smart Toothbrushes for Oral Health and Patient Education: A Review. Hygiene, 5(1), 5. https://doi.org/10.3390/hygiene5010005

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