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Article

Internet of Things and Smart Technologies in Oral Health: Trends, Impacts, and Challenges

by
Susana J. Calderon
1,*,
Stephen Mujeye Sr
2 and
Melissa I. Calvillo
1
1
Mennonite College of Nursing, Illinois State University, Normal, IL 61790, USA
2
Department of Technology, Illinois State University, Normal, IL 61790, USA
*
Author to whom correspondence should be addressed.
Oral 2025, 5(1), 18; https://doi.org/10.3390/oral5010018
Submission received: 16 December 2024 / Revised: 6 February 2025 / Accepted: 26 February 2025 / Published: 12 March 2025
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Abstract

:
Objective: This study aims to discover the most current trends, impacts, and challenges of using IoT devices and smart technologies in oral health. Method: A modified systematic mapping method was used to generate and answer five research questions. Twelve databases were queried to identify published literature from 2017 to 2023. Abstract screening and full-text review were conducted to identify studies meeting inclusion criteria. The Pandas library in Python Version 3.9.19 and a Fibonacci series were used to identify keyword trends in abstracts. Full-text analysis was conducted to synthesize findings relevant to the impacts and challenges of IoDT. Results: A total of 958 unduplicated articles were identified from the literature databases. After review, 33 articles were included. Publications related to IoDT are rapidly increasing over the last 7 years and keywords relating to toothbrushing were the most common. The most common research strategy was design and creation, followed by experimental methods. Design and creation of smart technologies in oral health are in a phase of measurement optimization using IoT which is being used for prevention, early detection, monitoring, and treatment of dental disease as well as silent communication devices. Challenges in IoDT continue to include measurement accuracy and user acceptability. Conclusions: Research in IoDT is predicted to continue to advance rapidly. Dental providers and public health agencies can look to this research to develop best practices. However, more research on how IoDT can facilitate desirable outcomes in a cost-effective and user-friendly way is needed.

1. Introduction

The term Internet of Things (IoT) is used to describe a paradigm in which technology objects are combined with identifying, sensing, networking, and processing features that give them the capability to communicate with each other and other devices over the internet [1]. The convergence of the internet and sensor networks offers new possibilities, allowing machine-to-machine communication using the internet. IoT is also defined by the International Telecommunication Union as “a global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on, existing and evolving, interoperable information and communication technologies” [2]. Previous research described prominent areas of IoT application as smart industry (intelligent production systems), smart home or building area (intelligent thermostats), smart energy (smart electricity), smart transport (vehicle fleet tracking), and smart health (chronic disease management) [3].

1.1. Oral Health

Oral health is an integral part of overall health. It is critical to increase awareness and prevention of oral health diseases associated with systematic chronic conditions. The general population continues to be at risk for dental caries and poor oral hygiene due to multifactorial lack of access to dental care, poor oral hygiene practices, increased consumption of sugary drinks, and high carbohydrate nutrition [4]. A public health issue, lack of oral health, is preventable. It causes major oral disease, oral pain, and discomfort, which burdens most countries.

1.2. Internet of Dental Things

Salagare and Prasad [5] coined the term Internet of Dental Things (IoDT), building off the concept of the Internet of Things and the Internet of Medical Things. IoDT can assist with the diagnosis, prevention, monitoring, and management of a myriad of oral health problems. Prevention, risk assessment, and early detection of caries, oral cancers, and periodontal diseases are essential to preserving and protecting the health of populations [5]. IoT can improve critical data collection, transfer, and analysis processes, providing a bridge between providers and patients [5]. These technologies have the potential to improve quality and decrease the cost of oral healthcare [5].
The field of dental IoT technologies needs to advance further to catch up with other fields using IoT, but some limitations in software performance and synchronization with dental equipment prevent flawless incorporation of the technology. Some suggest that the integration of smart technology into dentistry is more complex [6]. The benefits of using IoT and smart technologies during COVID-19 allowed timely connections between patients and dentistry providers. For patients with both chronic conditions and periodontal disease, the integration of IoT and smart technology into their care can potentially monitor these co-morbidities simultaneously. Figure 1 shows how patient information collected by an IoT-based smart toothbrush can be sent to a dental provider over the cloud. Smart toothbrushes typically have sensors and wireless communication to provide feedback to the user and/or the dental provider about the brushing habits of the user.
Incorporating smart technology and IoT into dentistry can benefit younger generations. It has been used to improve teaching strategies for medical and dental students [7]. Moreover, adolescents in particular often spend hours on their cellphones, as many as 8 h daily [8]. Large amounts of data are collected from these devices (“big data”) presenting an opportunity to use smart technology to capture behavioral data and use it to improve oral health outcomes [9]. Innovative ways to incorporate IoT in dentistry can give dentistry providers the skills they will need to thrive in a technologically evolving world.

1.3. Purpose

The authors of this study aim to discover the most current trends, impacts, and challenges of using IoT devices and smart technologies in oral health. Five research questions (RQ) were generated in pursuit of this aim. The research questions and rationale for each question are provided in Table 1.

2. Materials and Methods

This study employed a modified systematic mapping method as described by Petersen and colleagues [10,11]. In a traditional systematic mapping study, outcomes include classification schemes and systematic maps of a concept in order to structure the research area [10]. Keywords in the literature are analyzed and graphically displayed to support an understanding of the current knowledge and identify gaps [12]. We adapted the mapping method to answer our five specific research questions. These research questions were generated based on a prior review of existing literature. The steps used in this study are provided in Figure 2.
The first steps used in this study were defining the research questions and reviewing the scope. The research questions are presented in Table 1. The scope was defined as the most current trends, impacts, and challenges of IoT and smart technologies in oral health. The scope was limited to the previous 6 years plus the current year to evaluate the most current state of the literature. The literature search was conducted in March of 2023. The following list of databases was used to identify articles on IoT devices and smart technologies in oral health, using the specified search terms. The keywords used for searching were acquired from our comprehensive background research. The search terms were tailored to each database to match the syntax and keywords specific to the databases to maximize potential articles for inclusion. Specific search terms by database are provided in Table 2.
Records were reviewed to remove duplicate articles and subsequently screened according to the inclusion and exclusion criteria in Table 3. The screening was performed by dividing this initial work among the researchers. Articles that did not clearly meet inclusion or exclusion criteria were reviewed by the full panel of researchers in this study and a consensus was reached. After the screening, data extraction included obtaining the full-text articles which were reviewed by two researchers to confirm the articles met inclusion criteria, and a consensus was reached on additional studies to exclude.
To answer research questions 1, 2, and 3, first, abstracts of included articles were analyzed using the computational tools of the Pandas library in Python Version 3.9.19 and a Fibonacci algorithm to map keyword frequency. The Pandas library was utilized to efficiently process and analyze large volumes of textual data from abstracts, allowing for keyword mapping and frequency analysis. This systematic approach enabled us to identify dominant themes in the literature. Subsequently, frequency tables and graphics were generated. A Fibonacci series was then used to understand the relative importance of each word. The Fibonacci series is a mathematical sequence in which each number is the sum of the two preceding ones [13]. Specifically, we applied the formula F_n = F_(n − 1) + F_(n − 2) and assigned a value from 1 to 10 that represented the relevance of each keyword based on its occurrence in the Fibonacci series. The Fibonacci series is an innovative method for evaluating data trends. The Fibonacci approach assigned scores to keywords based on their frequency distribution, offering a nuanced way to highlight significant terms.
The Pandas library in Python Version 3.9.19 and the Fibonacci algorithm tools were selected to enhance objectivity in trend identification and to introduce a mathematical structure to keyword relevance assessment, ultimately improving the rigor and reproducibility of their findings.
The final step was to review and synthesize relevant findings reported in the included articles. To the best of our knowledge, this study will be the first to answer these research questions about IoT devices and smart technologies in oral health.

3. Results

A total of 958 unduplicated articles were identified from the literature databases. After review, 33 articles were found to meet inclusion criteria and not excluded. Table 4 shows the results by database.

3.1. RQ1. What Are the Most Current Keyword Trends of IoT and Smart Technologies in Oral Health?

IoDT research identified 44 frequently occurring terms through content trend analysis. Table 5 provides the resulting frequency table and Figure 3 shows a bar graph of these keywords and their corresponding frequencies. An asterisk is used as an operator to denote any ending after a stem, for example, toothbrush * includes toothbrushing, toothbrushes, etc. “Toothbrush” emerged as the most prevalent word, occurring 30 times in the 33 selected abstracts, and “brushing” occurred an additional 14 times. Next, “accuracy” appeared 17 times with “data” and “oral” following closely behind, appearing 15 times each. Keywords such as “sensor”, “device”, “system”, “Bluetooth”, and “application” were more prevalent than “wearable”, “learning”, “hygiene”, “plaque”, “monitoring”, and “motion”. Meanwhile, “diseases”, “incentives”, “interaction”, “parents”, and “stress” were notably scarce, appearing only twice in the selected abstracts.
After the application of the Fibonacci series to evaluate the relative importance of keywords, “accuracy”, “data”, “oral”, and “brushing” remained towards the top, with a score of 8. Similarly, “sensor”, “dental”, “health”, “method”, and “teeth” also had a score of 8. Keywords including “device”, “system”, “Bluetooth”, “control”, “application”, “model”, and “mobile” each have a score of 7, while “incentives”, “parents”, and, notably, “wireless” were among the least prevalent key terms. These results are graphically displayed in a bar chart in Figure 4.

3.2. RQ2. What Are the Trends in Publication Frequency of Research in IoT and Smart Technologies in Oral Health?

We found a trend of increasing numbers of research articles related to IoT devices and smart technologies in oral health, over the last 7 years. Figure 5 displays results from 2017 to 2023, with 2023 being a partial year due to the timing of our literature search. Throughout the period examined, studies focused on improving oral hygiene and utilizing sensors.
Two included studies were published in 2017. They focused on using a wristwatch with sensors to monitor the effectiveness of toothbrushing [14] and using mobile devices for dental surgical consultation in remote areas [15]. In 2018, publications continued to reflect the study of wearable sensors to improve hygiene with smart toothbrushes and water flossers [16,17]. Additionally, one 2018 study focused on using teeth tapping for silent typing [18], and one examined masticatory muscle activity for use in treating cleft lip and palate [19]. In 2019, there were two studies related to using IoDT with retainers [20,21], one on silent communication using retainer-like equipment [22], and one on measuring oral hygiene behaviors using wrist-worn sensors [23]. In 2020, studies continued to test the use of wrist-worn sensors to track oral hygiene behaviors [24], to detect dental problems in the home setting [25], and to examine incentive-based oral hygiene programs for children and parents using smart toothbrushing [26,27].
By 2021, the number of studies continued to grow with three publications examining the use of sensors or Bluetooth technology in oral hygiene [28,29,30] and an additional study using an augmented reality system to coach children with autism spectrum disorders in oral hygiene [31]. One study continued the exploration of silent communication [32] and one study examined the use of smart technology to manage patient stress during dental procedures [33]. In 2022, three studies continued to examine sensor data to improve oral hygiene [34], with two focusing on pediatric populations [35,36]. Three additional studies reported efforts to improve silent speech [37,38,39], with two of those studying ear-worn devices that also measure jaw or mouth movements [38,39]. Also in 2022, one study described the use of IoDT in the context of the COVID-19 pandemic for remote dental examination, decreasing the risk of communicable disease for both patients and providers [40]. Finally, in 2023, more studies emerged that examined patient outcomes [41], the use of biosensors [42], and improved management of dental conditions such as xerostomia [43], root canal treatment [44], and mandibular fracture [45].

3.3. RQ3. What Are the Research Methods Used to Collect Data in the Published IoDT Literature?

The results of the different research methods used in the included articles are presented in Table 6. The studies are categorized into either experimental or focused on the design and creation of devices for use in IoDT. Additionally, the sample size is listed for each study with a total of 1896 participants reported in the 33 studies.
Among the included articles, the predominant research strategy was design and creation with 20 instances, indicating a strong emphasis on the development of novel solutions and improving the design of IoDT technologies. Experimental strategies were used in 13 articles with a significant focus on testing variables related to efficiency, performance, and security. None of the 33 selected abstracts used other methods such as surveys, case studies, participatory action research, or ethnography.

3.4. RQ4. What Impacts Have Internet of Things (IoT) Devices and Smart Technologies Had on Oral Health?

Twenty-three studies were included to answer this research question on the impacts of IoT devices and smart technologies on oral health. The majority of the studies were original research. We included studies that addressed oral health and oral structures, to facilitate breathing, eating, speaking, and communication. A number of articles addressed the impact of IoT when it is used with Bluetooth devices or sensors to improve oral health behavior or prevention of diseases.

3.4.1. Design, Creation, and Measurement Optimization

Many of the included studies examined the design, creation, and optimization of sensors to measure oral hygiene behaviors, including water flossing [17] and smart toothbrushing [14,23,24,28,30,34]. Other sensors measured the time orthodontic retainers were worn [20,21]. These studies typically involved smart technologies of wireless Bluetooth data linkages, mobile applications, and real-time feedback for the user. Grzegorz and colleagues [29] tested the acceptability of a smart toothbrush with real-time application feedback among older adults in an aged care facility with promising results. They plan a future study to measure the impact of the application feedback on oral health outcomes.

3.4.2. Prevention

Several studies measured outcome improvements for the prevention of dental disease including plaque reduction [16,35,41], decreased anxiety/stress during dental procedures [33], increased toothbrushing frequency [36], and less bleeding on brushing [41]. One study demonstrated increased masticatory muscle strength after using their device in children with cleft lip/palate [19]. Another study developed an augmented reality coaching system for oral hygiene behaviors among children with autism spectrum disorder and demonstrated reduced anxiety about toothbrushing in this population [31]. Other studies sought to maximize motivation for oral hygiene by examining varying incentive structures for families with children using Bluetooth-enabled toothbrushes to track behavior [26,27].

3.4.3. Detection, Monitoring, and Treatment

Remote monitoring and diagnostic efficiency are emerging topics in IoDT. Hashem and colleagues [42] developed a wearable biosensor to detect coughing, drinking, chewing, and smoking behaviors, as well as to analyze saliva for biomarkers, metal particles, glucose medications, and microorganisms. Similarly, Salagare and Prasad [5] describe a system to monitor microbial flora, biofilm pH, carbohydrate consumption, and oral hygiene. This technology was designed to assist in the early detection of risks for dental disease and facilitate targeted prevention efforts. One study developed tools for remote dental examination to reduce the risks of COVID-19 transmission during the height of the pandemic [40]. In addition, diagnostic devices have been tested to detect and classify dental diseases including tooth decay, plaque, and periodontal disease [34]. Meanwhile, Rane and colleagues [45] described technology to measure occlusion forces which are important in mandibular fracture assessment. Treatment of dental concerns can also be enhanced with IoDT. One study tested a wireless electronic apex locator to improve root canal treatment [44], while another designed and tested a device to treat xerostomia with a device to eject artificial saliva [43]. Furthermore, one study described how mobile consultation with dental surgeons can increase access to life-saving care in rural and other poorly-resourced areas [15].

3.4.4. Silent Communication

A surprisingly common application of smart technologies and IoT in oral health was to facilitate silent communication. Five studies developed and/or tested devices worn in the mouth that detected tongue gestures or tooth taps to represent letters, words, or sounds for use in a speech recognition application [18,22,32,37,39]. Similarly, one study tested an ear wearable device that detected jaw movement for silent communication [32].

3.5. RQ5. What Challenges Are Faced in the Implementation of IoT Devices and Smart Technologies in Oral Health?

3.5.1. Equipment Design and Accuracy

Throughout the literature, the most common challenge of implementing IoT technology in oral health was equipment design and use both by researchers and by the intended end user. A frequent concern was the ability of smart devices to obtain accurate measurements. First, interference was a major challenge. Many of the described IoT devices relied on measuring motion, sometimes small or subtle movements; therefore other movements interfered with sensor accuracy [18,22,24,34,35,36,37,38] or could cause device failure [20]. Some devices require users to maintain specified body positions [19], keep the head still during measurement [34], or limit what other activities the user can engage in [39]. One study highlighted the challenge of other oral hygiene IoT devices as being a cause of interference [30]. While several studies used magnets in their IoT devices, one specifically highlighted magnetic interference from different device components as a potential challenge [17]. One study reported that normal saliva levels and composition interfered with data measurement [25] and multiple studies mentioned the challenge of waterproofing devices due to the need for water or other liquid during oral hygiene activities [17,29,31]. In one study, the potential for their device to interfere with implanted pacemakers or defibrillators was a major concern and therefore it could not be used in certain patients [44].
An additional threat to accuracy was computational challenges including choosing the best algorithm to produce usable data or reliance on machine learning which requires varying sizes of training data sets, however, different algorithms were often compared and found to be acceptable [14,18,24,37,42]. Another challenge was limits on storage space [17,29,30] and the balance of power consumption with battery life for wireless devices [20,37,39]. One study mentioned a one-minute calibration period before the device can be used, which could influence user acceptability [34]. Furthermore, the accuracy of sensor data also varied for measurements in different areas of the mouth [22,25,34]. Finally, several researchers identified the challenge of having enough sensors to maximize accuracy while also minimizing the number of sensors with which the user must interact because additional sensors increase costs and can decrease user acceptability [23,38].

3.5.2. User Interface and End-User Acceptability

Ease of use for the intended audience and technological barriers were another common theme among reviewed articles. Many devices require familiarity with smartphones or tablets and applications [16,29,37,41]. The complexity of the user interface was a noted challenge in many studies [24,25,29,37,38,39]. Certain populations of device users had unique challenges in using IoT devices such as individuals with low manual dexterity [29], cognitive impairment [30], motor impairment [39], speech disorders [38], cleft lip/palate [19], and pediatric populations [26,31,36].
User acceptability, particularly social acceptability of using a novel device in public, was a challenge discussed in several studies [18,22,38,39]. Similarly, concordance between actual device usage by the patient and recommended use from the researcher/provider was not always reliably achieved [16,36]. Several study designs relied on participant self-report for measurement of some outcomes which can bias results [26,36,41]. Most interventions were examined only in the short-term and several studies explicitly recommended a longer-term study period of 6 months [16] to over a year [36] to examine long-term outcomes related to the use of dental IoT devices.

4. Discussion

Our study aimed to outline the trends, impacts, and challenges in research and literature on IoT and smart technologies in oral health. The field of IoDT has been growing over the last decade with an increasing number of publications from 2017 to 2023. The number of articles meeting inclusion criteria doubled from 2020 to 2022 and quadrupled since 2017. This is an area of research that we anticipate will continue to advance rapidly. Innovative interventions ready for the public are now emerging in the research. Dental providers and public health agencies can look to our synthesis and future work for promising practices and potential research opportunities. Increasing publishing trends show that industry experts and researchers are keenly aware of the potential of IoT devices and smart technologies to improve oral health. This trend could be attributed to the rapid development of IoT technologies and increasing access to smart devices around the globe. The “design and creation” strategy’s dominance highlights how proactive researchers are, in fostering innovation in the IoDT space for oral health. The fact that the selected papers lack survey, case study, action research, and ethnographic strategies presents an opportunity to apply these research techniques in this particular research area. Additionally, while some studies discussed the cost of equipment to create IoDT, there is a need for studies examining the cost-effectiveness of smart technology in comparison to the current standard of care in the prevention, diagnosis, and treatment of oral health problems.
The prevalence of research focused on the design and creation of IoDT equipment indicates a structured user-centered process in finding innovative solutions to problems in oral health. Overall, the publication trends reveal a growing interest and acceptance of IoDT which can result in effective and improved treatments. A large majority of studies focused on toothbrushing, while fewer focused on specific programs or interventions and evaluating outcomes. This suggests that it is timely for research to transition towards more experimental designs with the goal of creating best practice recommendations, based on outcomes evaluation, for the use of IoDT.
Big data presents opportunities in healthcare, including oral dentistry. Data mining tools and data analytics could also be used to analyze and evaluate collected data and provide solutions for oral health. IoDT technology and its creation of big data offer the opportunity to predict desirable and undesirable oral health outcomes. This can move us toward a world in which we can notify users not only about their risk for a disease but also empower them to take action toward their health before it is too late. This primary prevention approach is critical for public health and has the potential to advance the dental profession.
It is also worth noting that IoDT raises critical ethical considerations in data protection, informed consent, transparency, and ethical education. With IoDT devices collecting sensitive patient data, strong encryption and cybersecurity measures are essential to prevent breaches. Informed consent must be explicit, ensuring patients understand how their data is used and can withdraw consent at any time. Transparency in data management is crucial, requiring clear policies, audit trails, and patient access to their own information. Additionally, education and training in data privacy, AI ethics, and cybersecurity must be integrated into dental programs to prepare professionals for ethical IoDT use. By prioritizing security, consent, transparency, and education, IoDT can advance dental care while maintaining trust and compliance with ethical standards.
As the field of the Internet of Things and smart technologies continues to evolve, it can be leveraged to find solutions in oral health. Artificial intelligence and machine learning can also be applied in the use of IoT devices and smart technologies in healthcare in ways that can solve existing problems. Specifically, artificial intelligence can be used in oral health to help in areas including diagnostic assistance, personalized treatment plans, predictive analysis, patient monitoring, and research and development. There is a need for more research and collaboration including oral healthcare professionals and information security professionals.
Our study highlights how IoDT devices are transforming dental education by enhancing hands-on training, remote learning, and data-driven curriculum development. Smart toothbrushes, intraoral sensors, and AI-driven diagnostics provide real-time feedback, improving clinical skill acquisition. Teledentistry applications enable remote monitoring and interactive case studies, making education more accessible and immersive. The use of Python’s Version 3.9.19 Pandas library and Fibonacci ranking helps identify emerging trends, ensuring that curricula align with technological advancements. Additionally, IoDT-enabled motion tracking and biometric analysis allow for personalized student performance assessments, fostering data-driven learning and skill refinement. These advancements position IoDT as a critical tool for modernizing dental education and preparing students for a technology-driven future in dentistry.
Our findings build on the prior work of Salagare and Prasad [5] in identifying the challenges in IoDT application and research. We add specificity to their finding that easy data collection and application is a major challenge. Technologies that are robust to movement, liquid, and low magnetic or other interference are needed for IoDT. Storage and energy consumption while maintaining a small sensor size continues to be a critical challenge, which is consistent with prior work [5]. The use of IoDT in specific populations is an additional unique finding of our study. It was surprising that our results did not reveal data security and privacy as a major challenge, in contrast with Salagare and Prasad [5], rather, silent communication devices were proposed as a way to preserve privacy when communicating. We cannot infer that the lack of documented data privacy and security concerns in recent studies means that this challenge has been resolved. On the contrary, there are increased opportunities for data security breaches as IoT is expanded.

5. Limitations

Our study provides valuable insights into the trends, impacts, and challenges of IoT and smart technologies in oral health, but it has several limitations. The limited sample size of 33 articles from 2017 to 2023 may not fully capture all IoDT advancements, especially industry-led innovations not widely published in academic literature. Additionally, most reviewed studies were short-term, lacking longitudinal data to assess long-term effectiveness, user engagement, and device reliability. The focus on design and creation over clinical validation means that while many IoDT devices show potential, their real-world effectiveness and adoption remain uncertain.
Furthermore, while the study used Python’s Version 3.9.19 Pandas library and a Fibonacci ranking system to analyze trends, it did not incorporate AI-driven analytics that could enhance predictive modeling in IoDT research. Ethical and privacy concerns were not extensively explored, despite being critical for data security, regulatory acceptance, and patient trust. Additionally, the study does not address cost-effectiveness and accessibility issues, particularly in low-resource settings where IoT-powered dental care may be less viable. Future research should focus on long-term validation, clinical effectiveness, ethical concerns, and economic feasibility to fully understand IoDT’s practical applications in oral healthcare.

6. Conclusions

In the digital age, the increased presence of IoT devices and smart health technologies in oral health is promising for the improvement of public health outcomes. Smart technologies and IoT devices have the potential to decrease costs while improving diagnostics, treatment, and convenience for patients and providers. This potential must overcome challenges in designing products that are easy to use in diverse populations and are socially acceptable. Additionally, measurement accuracy should strive to be at least as good as other existing strategies. Despite these challenges, the research is trending toward increased work with IoT devices and smart technologies in oral health with an eye toward amplifying positive outcomes for the public.

Author Contributions

S.J.C. conceived the work, wrote, and revised the manuscript draft; S.M.S. wrote and revised the work, as well as revised the manuscript; M.I.C. wrote and revised the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

The authors did not receive support from any organization or funding agency for the submitted work.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Acknowledgments

We acknowledge the following individual for his assistance: Graduate Student Benjamin Panful.

Conflicts of Interest

The authors declare no conflicts of interest.

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  27. Ramos-Gomez, F.; White, J.S.; Lindau, H.E.; Lin, T.K.; Finlayson, T.L.; Liu, J.X.; Gansky, S.A. Family Monetary Incentives as a value-based Care Model for Oral Hygiene: Rationale and Design of the BEhavioral EConomics for Oral Health iNnovation (BEECON) Trial. J. Public Health Dent. 2020, 80, S17–S26. [Google Scholar] [CrossRef]
  28. Akther, S.; Saleheen, N.; Saha, M.; Shetty, V.; Kumar, S. mTeeth: Identifying Brushing Teeth Surfaces Using Wrist-Worn Inertial Sensors. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2021, 5, 1–25. [Google Scholar] [CrossRef]
  29. Grzegorz Broda, L.; Oseni, T.; Stranieri, A.; Marino, R.; Robinson, J.; Yates, M. The Design of a Smartbrush Oral Health Installation for Aged Care Centres in Australia. In Proceedings of the 2021 5th International Conference on Medical and Health Informatics, Kyoto, Japan, 14–16 May 2021; ACM: New York, NY, USA, 2021; pp. 176–180. [Google Scholar] [CrossRef]
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  31. Zheng, Z.K.; Sarkar, N.; Swanson, A.; Weitlauf, A.; Warren, Z.; Sarkar, N. CheerBrush: A Novel Interactive Augmented Reality Coaching System for Toothbrushing Skills in Children with Autism Spectrum Disorder. ACM Trans. Access. Comput. 2021, 14, 1–20. [Google Scholar] [CrossRef]
  32. Sun, W.; Li, F.M.; Steeper, B.; Xu, S.; Tian, F.; Zhang, C. TeethTap: Recognizing Discrete Teeth Gestures Using Motion and Acoustic Sensing on an Earpiece. In Proceedings of the 26th International Conference on Intelligent User Interfaces, Station, TX, USA, 14–17 April 2021; ACM: New York, NY, USA, 2021; pp. 161–169. [Google Scholar] [CrossRef]
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  34. Li, H.; Jing, L.; Liu, F. A Real-Time Lightweight Method to Detect the Sixteen Brushing Regions Based on a 9-Axis Inertial Sensor and Random Forest Classifier. In Proceedings of the 2021 The 9th International Conference on Information Technology: IoT and Smart City, Guangzhou, China, 22–25 December 2021; ACM: New York, NY, USA, 2022; pp. 24–29. [Google Scholar] [CrossRef]
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Figure 1. Patient transmitting real-time dental data from a smart device to a provider for remote monitoring.
Figure 1. Patient transmitting real-time dental data from a smart device to a provider for remote monitoring.
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Figure 2. Study process steps.
Figure 2. Study process steps.
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Figure 3. Most Frequent Word Chart. Asterisk (*) is an operator to denote any ending after a stem.
Figure 3. Most Frequent Word Chart. Asterisk (*) is an operator to denote any ending after a stem.
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Figure 4. Relative Importance of Keywords Based on Fibonacci Sequence.
Figure 4. Relative Importance of Keywords Based on Fibonacci Sequence.
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Figure 5. Number of included IoDT publications by year 2017–2023. Note: 2023 is a partial year.
Figure 5. Number of included IoDT publications by year 2017–2023. Note: 2023 is a partial year.
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Table 1. Research questions and rationales.
Table 1. Research questions and rationales.
Research QuestionRationale
RQ1What are the most current keyword trends of IoT and smart technologies in oral health?To identify promising areas for application of IoDT in practice and opportunities for future research
RQ2What are the most current trends in publication frequency of research in IoT and smart technologies in oral health?To determine if this is an area of research growth, decline, or stagnation
RQ3What are the most current research methods used to collect data in the published IoDT literature?To summarize research strategies commonly used in IoDT and suggest opportunities for needed strategies
RQ4How have IoT devices and smart technologies impacted oral health outcomes?To identify how IoT and smart technologies have the potential to impact oral health outcomes and identify opportunities for research and practice
RQ5What are the most current challenges in the implementation of IoT devices and smart technologies in oral health?To identify challenges that may be pertinent for research or industry to address for technology and research improvements
Table 2. Search terms by database.
Table 2. Search terms by database.
DatabaseSearch Terms
Computers & Applied Sciences Complete(Bluetooth or “wireless communication” or “internet of things” or “wearable” or “biosensor *” or “smart device” or “smart technolog *” or “smart watch” or “smart monitoring” or “smart toothbrush” or “smart electronic *” or “smart meter *”) AND (dental or dentist * or “oral health” or “dental thing *”)
Health databases * (Bluetooth or “wireless communication” or “internet of things” or “wearable” or “biosensor *” or “smart device” or “smart technolog *” or “smart watch” or “smart monitoring” or “smart toothbrush” or “smart electronic *” or “smart meter *”) AND (dental or dentist * or “oral health” or “dental thing *”)
IGI Global Ebooks CollectionMultiple searches were conducted to cover all combinations of smart device, smart technology, internet of things, Bluetooth, smart toothbrush, biosensor, wearable, smart monitoring AND dental or oral health
ACM Digital Library[[All: bluetooth] OR [All: “wireless communication”] OR [All: “internet of things”] OR [All: “wearable”] OR [All: “biosensor *”] OR [All: “smart device”] OR [All: “smart technolog *”] OR [All: “smart watch”] OR [All: “smart monitoring”] OR [All: “smart toothbrush”] OR [All: “smart electronic *”] OR [All: “smart meter *”]] AND [[All: dental] OR [All: dentist *] OR [All: “oral health”]] AND [E-Publication Date: (01/01/2017 TO 12/31/2023)]
PubMed(“internet of things” [All Fields] OR Bluetooth OR “smart device” OR “smart technology”) AND ((dental) OR (dentist *))
* Health databases include CINAHL Complete, ERIC, APA Psych Info, Academic Search Complete, Consumer Health Complete EBSCOHost, Consumer Health Reference eBook Collection, Health and Psychosocial Instruments, and Health Source: Nursing/Academic Edition.
Table 3. Inclusion and exclusion criteria.
Table 3. Inclusion and exclusion criteria.
Inclusion CriteriaExclusion Criteria
Articles that discuss trends and/or challenges of IoT and smart technologies in oral healthArticles that do not discuss trends and/or challenges of IoT and smart technologies in oral health
Published from 2017 to 2023Articles that are not in English
Articles with the main output of a systematic literature review or mapping study
Book chapters
Articles not accessible in full-text
Duplicate studies
Commentaries and editorials
Table 4. Search results by database.
Table 4. Search results by database.
DatabaseNumber of Unduplicated Articles ReviewedNumber of Articles Included
ACM Digital34716
Computers & Applied Science4185
Health databases394
IGI Global731
PubMed817
Total95833
Table 5. Keywords frequency table. Asterisk (*) is an operator to denote any ending after a stem.
Table 5. Keywords frequency table. Asterisk (*) is an operator to denote any ending after a stem.
RankWordFrequency RankWordFrequency RankWordFrequency
1 toothbrush * 30 16 model 10 31 plaque 5
2 accuracy 17 17 mobile 9 32 monitoring 4
3 data 15 18 sensors 9 33 surface 4
4 oral 15 19 smart 8 34 distance 3
5 brushing 14 20 detection 7 35 gesture 3
6 sensor 14 21 patients 7 36 gestures 3
7 dental 13 22 technology 7 37 muscle 3
8 health 13 23 children 6 38 tongue 3
9 method 13 24 dentist 6 39 wireless 3
10 teeth 13 25 learning 6 40 diseases 2
11 device 12 26 machine 6 41 incentives 2
12 system 12 27 wearable 6 42 interaction 2
13 Bluetooth 11 28 hygiene 5 43 parents 2
14 control 11 29 intervention 5 44 stress 2
15 application 10 30 motion 5
Table 6. Included articles by research method with sample size.
Table 6. Included articles by research method with sample size.
TypeAuthor, YearTitleSample Size
Design and Creation (Total = 20)Akther et al., 2019 [23]MTeeth: Identifying Brushing Teeth Surfaces Using Wrist-Worn Inertial Sensors25
Akther et al., 2021 [28]MORAL: An MHealth Model for Inferring Oral Hygiene Behaviors in-the-Wild Using Wrist-Worn Inertial Sensors25
Fan et al., 2018 [17]Smart Water Flosser: A Novel Smart Oral Cleaner with IMU Sensor8
Grzegorz et al., 2021 [29]The Design of a Smartbrush Oral Health Installation for Aged Care Centres in Australia2
Hashem et al., 2023 [42]Design and development of wireless wearable bio-tooth sensor for monitoring of tooth fracture and its bio metabolic components.10
Huang and Lin, 2017 [14]Tooth Brushing Recognition Using Neural Networks: Poster Abstract12
Karthikeyan et al., 2023 [43] A salivary sensor for the management of xerostomia in edentulous patients.n/a
Kimura et al., 2022 [37]SilentSpeller: Towards Mobile, Hands-Free, Silent Speech Text Entry Using Electropalatography6
Li et al., 2022 [34]A Real-Time Lightweight Method to Detect the Sixteen Brushing Regions Based on a 9-Axis Inertial Sensor and Random Forest Classifier743
Li et al., 2019 [22]TongueBoard: An Oral Interface for Subtle Input4
Liu et al., 2020 [25]A Smart Dental Health-IoT Platform Based on Intelligent Hardware, Deep Learning, and Mobile Terminal.100
Nguyen et al., 2018 [18]TYTH-Typing On Your Teeth: Tongue-Teeth Localization for Human-Computer Interface15
Omsri Kumar et al., 2021 [30]A Solution with Bluetooth Low Energy Technology to Support Oral HealthCare Decisions for Improving Oral Hygiene170
Salagare and Prasad, 2023 [5]Internet of Dental Things (IoDT), Intraoral Wireless Sensors, and Teledentistry: A Novel Model for Prevention of Dental Caries.n/a
Srivastava et al., 2022 [38]MuteIt: Jaw Motion Based Unvoiced Command Recognition Using Earable20
Sun et al., 2021 [32]TeethTap: Recognizing Discrete Teeth Gestures Using Motion and Acoustic Sensing on an Earpiece11
Wang et al., 2022 [39]ToothSonic: Earable Authentication via Acoustic Toothprint25
Wedyan et al., 2022 [40]A Smart Device for a Preliminary Dental Examination Based on the Internet of Thingsn/a
Witzke et al., 2017 [15]M-Health Telemedicine and Telepresence in Oral and Maxillofacial Surgery: An Innovative Prehospital Healthcare Concept in Structurally Weak Areasn/a
Zheng et al., 2021 [31]CheerBrush: A Novel Interactive Augmented Reality Coaching System for Toothbrushing Skills in Children with Autism Spectrum Disorder12
Experiment (Total = 13)Brand et al., 2023 [44]An in vitro evaluation of the WIRELE-x electronic apex locator31
Castle et al., 2019 [20]Compliance monitoring via a Bluetooth-enabled retainer: A prospective clinical pilot study5
Erbe et al., 2018 [16]A comparative assessment of plaque removal and toothbrushing compliance between a manual and an interactive power toothbrush among adolescents: a single-center, single-blind randomized controlled trial.60
Hussain et al., 2020 [24]Toothbrushing Data and Analysis of Its Potential Use in Human Activity Recognition Applications: Dataset17
Jeong et al., 2022 [35]Efficacy of tooth brushing via a three-dimensional motion tracking system for dental plaque control in school children: a randomized controlled clinical trial.42
Labus et al., 2021 [33]Enhancing smart healthcare in dentistry: an approach to managing patients’ stress.46
Ramos-Gomez et al., 2020 [27]Family monetary incentives as a value-based care model for oral hygiene: rationale and design of the BEhavioral EConomics for Oral health iNnovation (BEECON) trial244
Rane et al., 2023 [45]Development of computerized masticatory force measurement system.22
Szyszka-Sommerfeld et al., 2018 [19]The electrical activity of the masticatory muscles in children with cleft lip and palate.82
Tadakamadla et al., 2022 [36]Protocol of a cluster randomised controlled trial evaluating the effectiveness of an online parenting intervention for promoting oral health of 2–6 years old Australian children18
Tonetti et al., 2023 [41]Self-reported bleeding on brushing as a predictor of bleeding on probing: Early observations from the deployment of an internet of things network of intelligent power-driven toothbrushes in a supportive periodontal care population.100
White et al., 2020 [26]Monetary incentives for improving smartphone-measured oral hygiene behaviors in young children: A randomized pilot trial36
Williams, 2019 [21]What is the clinical efficacy and accuracy of a newly developed Bluetooth-enabled retainer when worn by orthodontic residents?5
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Calderon, S.J.; Mujeye Sr, S.; Calvillo, M.I. Internet of Things and Smart Technologies in Oral Health: Trends, Impacts, and Challenges. Oral 2025, 5, 18. https://doi.org/10.3390/oral5010018

AMA Style

Calderon SJ, Mujeye Sr S, Calvillo MI. Internet of Things and Smart Technologies in Oral Health: Trends, Impacts, and Challenges. Oral. 2025; 5(1):18. https://doi.org/10.3390/oral5010018

Chicago/Turabian Style

Calderon, Susana J., Stephen Mujeye Sr, and Melissa I. Calvillo. 2025. "Internet of Things and Smart Technologies in Oral Health: Trends, Impacts, and Challenges" Oral 5, no. 1: 18. https://doi.org/10.3390/oral5010018

APA Style

Calderon, S. J., Mujeye Sr, S., & Calvillo, M. I. (2025). Internet of Things and Smart Technologies in Oral Health: Trends, Impacts, and Challenges. Oral, 5(1), 18. https://doi.org/10.3390/oral5010018

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