Innovation of Digital Periodontal Probe Based on Camera Sensor as Automation for Identification of Gingival Discoloration and Anterior Gingival Recession

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Published: Jun 4, 2026
DOI: https://doi.org/10.55885/jchp.v6i1.974
Keywords:
Digital Periodontal Probe, Camera Sensor, Gingival Color, Gingival Recession, Innovation

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Rike Widayanti
Applied Dental and Oral Therapist Master's Study Program, Poltekkes Kemenkes Semarang, Indonesia
Supriyana
Applied Dental and Oral Therapist Master's Study Program, Poltekkes Kemenkes Semarang, Indonesia
Diyah Fatmasari
Applied Dental and Oral Therapist Master's Study Program, Poltekkes Kemenkes Semarang, Indonesia

Abstract

Periodontal disease remains a major oral health problem. This study aimed to develop and conduct a preliminary evaluation of a camera sensor-based digital periodontal probe for detecting gingival discoloration and gingival recession. The study employed a Research and Development (R&D) approach followed by a paired comparative assessment between manual and digital examination methods on the same subjects. The study involved 30 patients and 30 dental health professionals. Product feasibility was evaluated through expert validation using Aiken’s V, while reliability was assessed using the Intraclass Correlation Coefficient (ICC). Differences between manual and digital examination methods were analyzed using the Wilcoxon Signed Rank Test. The results showed no statistically significant difference in gingival discoloration detection between manual and digital methods (p=0.251). In contrast, a statistically significant difference was observed in gingival recession classification outcomes (p=0.011). The digital method identified more moderate and severe recession cases; however, this finding reflects differences in classification outcomes and does not necessarily indicate superior diagnostic performance. Expert validation indicated high content validity (Aiken’s V=0.897) and acceptable reliability (ICC=0.796). This study suggests that the developed tool has potential for use in periodontal screening and digital documentation. Further studies with larger sample sizes, reference standards, and agreement analysis are required to confirm the diagnostic accuracy and broader clinical applicability of the device.

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Widayanti, R., Supriyana, S., & Fatmasari, D. . (2026). Innovation of Digital Periodontal Probe Based on Camera Sensor as Automation for Identification of Gingival Discoloration and Anterior Gingival Recession. Journal of Community Health Provision, 6(1), 276-286. https://doi.org/10.55885/jchp.v6i1.974
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Vol. 6 No. 1 (2026): Journal of Community Health Provision
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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

References

Al-Yaseen, W., Haghi Ashtiani, G., Pattinson, R., Pritchard, M. F., Pickles, T., Galloway, J., & Innes, N. (2025). Picture perfect: study protocol for assessing the accuracy, feasibility and acceptability of intraoral photographs captured by parents for remote dental screening in children–an observational mixed-methods study. BMJ open, 15(9), e104769. https://doi.org/10.1136/bmjopen-2025-104769

Angelino, K., Shah, P., Edlund, D. A., Mohit, M., & Yauney, G. (2017). Clinical validation and assessment of a modular fluorescent imaging system and algorithm for rapid detection and quantification of dental plaque. BMC oral health, 17(1), 162. https://doi.org/10.1186/s12903-017-0472-4

Asan, O., Ye, Z., & Acharya, A. (2013). Dental care providers' and patients' perceptions of the effect of health information technology in the dental care setting. The Journal of the American Dental Association, 144(9), 1022-1029. https://doi.org/10.14219/jada.archive.2013.0229

Atri, F., Rahmani, F., Memarian, M., & Pirooz, P. (2026). Comparative Evaluation of Shade Selection Reliability: Visual Assessment, Intraoral Scanning, and Photographic Techniques. International Journal of Dentistry, 2026(1), 5516548. https://doi.org/10.1155/ijod/5516548

Azam, A. S., Miligy, I. M., Kimani, P. K., Maqbool, H., Hewitt, K., Rajpoot, N. M., & Snead, D. R. (2021). Diagnostic concordance and discordance in digital pathology: a systematic review and meta-analysis. Journal of Clinical Pathology, 74(7), 448-455. https://doi.org/10.1136/jclinpath-2020-206764

Braeken, J., & van Laar, S. (2026). Assessing the Measurement Equivalence of a set of Items: Item-specific Diagnostics on an Interpretable Metric. Practical Assessment, Research, and Evaluation, 31(1). https://doi.org/10.7275/pare.3048

Cairo, F., Nieri, M., Cincinelli, S., Mervelt, J., & Pagliaro, U. (2011). The interproximal clinical attachment level to classify gingival recessions and predict root coverage outcomes: an explorative and reliability study. Journal of clinical periodontology, 38(7), 661-666. https://doi.org/10.1111/j.1600-051X.2011.01732.x

Chau, R. C. W., Li, G. H., Tew, I. M., Thu, K. M., McGrath, C., Lo, W. L., ... & Lam, W. Y. H. (2023). Accuracy of artificial intelligence-based photographic detection of gingivitis. International dental journal, 73(5), 724-730. https://doi.org/10.1016/j.identj.2023.03.007

Chung, H. M., Park, J. Y., Ko, K. A., Kim, C. S., Choi, S. H., & Lee, J. S. (2022). Periodontal probing on digital images compared to clinical measurements in periodontitis patients. Scientific reports, 12(1), 1616. https://doi.org/10.1038/s41598-021-04695-6

Dahlen, G., Basic, A., & Bylund, J. (2019). Importance of virulence factors for the persistence of oral bacteria in the inflamed gingival crevice and in the pathogenesis of periodontal disease. Journal of clinical medicine, 8(9), 1339. https://doi.org/10.3390/jcm8091339

Ehrensperger, C., Körner, P., Svellenti, L., Attin, T., & Sahrmann, P. (2025). Evaluation of an Intraoral Camera with an AI-Based Application for the Detection of Gingivitis. Journal of Clinical Medicine, 14(15), 5580. https://doi.org/10.3390/jcm14155580

Elashiry, M., Meghil, M. M., Arce, R. M., & Cutler, C. W. (2019). From manual periodontal probing to digital 3‐D imaging to endoscopic capillaroscopy: Recent advances in periodontal disease diagnosis. Journal of periodontal research, 54(1), 1-9. https://doi.org/10.1111/jre.12585

Farina, R., Simonelli, A., Trombelli, L., Ettmayer, J. B., Schmid, J. L., & Ramseier, C. A. (2025). Emerging applications of digital technologies for periodontal screening, diagnosis and prognosis in the dental setting. Journal of Clinical Periodontology, 52, 211-245. https://doi.org/10.1111/jcpe.14156

Gkantidis, N., Dritsas, K., Ghamri, M., Halazonetis, D., & Sculean, A. (2024). Methods for 3D evaluation and quantification of gingival recessions and gingival margin changes: Advancements from conventional techniques. Periodontology 2000. https://doi.org/10.1111/prd.12615

Goldstein, R. E., Siranli, S., Haywood, V. B., & Caughman, W. F. (2018). Management of stained and discolored teeth. Ronald E. Goldstein's Esthetics in Dentistry, 667-691. https://doi.org/10.1002/9781119272946.ch21

Hausmann, E. (2000). Radiographic and digital imaging in periodontal practice. Journal of periodontology, 71(3), 497-503. https://doi.org/10.1902/jop.2000.71.3.497

Hegde, R., & Hegde, V. (2016). Magnification-enhanced contemporary dentistry: Getting started. Journal of Interdisciplinary Dentistry, 6(2), 91-100.

Heitz‐Mayfield, L. J. (2024). Conventional diagnostic criteria for periodontal diseases (plaque‐induced gingivitis and periodontitis). Periodontology 2000, 95(1), 10-19. https://doi.org/10.1111/prd.12579

Hyde, S., Dupuis, V., Mariri, B. P., & Dartevelle, S. (2017). Prevention of tooth loss and dental pain for reducing the global burden of oral diseases. International Dental Journal, 67, 19-25. https://doi.org/10.1111/idj.12328

Iacomussi, P., Carcieri, P., Rossi, G., & Migliario, M. (2017). The factors affecting visual discomfort of dental hygienist. Measurement, 98, 92-102. https://doi.org/10.1016/j.measurement.2016.11.022

Jansen, P., Krause, F., Braun, A., & Jansen, E. E. (2026). Agreement in Subjective Periodontal Findings in Undergraduate Dental Training: A Retrospective Observational Study of Bleeding on Probing and Tooth Mobility. Dentistry Journal, 14(4), 235. https://doi.org/10.3390/dj14040235

Jati, A. S., Furquim, L. Z., & Consolaro, A. (2016). Gingival recession: its causes and types, and the importance of orthodontic treatment. Dental press journal of orthodontics, 21, 18-29.

Kassab, M. M., & Cohen, R. E. (2003). The etiology and prevalence of gingival recession. The journal of the American dental association, 134(2), 220-225. https://doi.org/10.14219/jada.archive.2003.0137

Kennedy, V. L., Flavell, C. A., & Doma, K. (2019). Intra-rater reliability of transversus abdominis measurement by a novice examiner: Comparison of “freehand” to “probe force device” method of real-time ultrasound imaging. Ultrasound, 27(3), 156-166. https://doi.org/10.1177/1742271X19831720

Ko, T. J., Byrd, K. M., & Kim, S. A. (2021). The chairside periodontal diagnostic toolkit: past, present, and future. Diagnostics, 11(6), 932. https://doi.org/10.3390/diagnostics11060932

Lang, N. P., Schätzle, M. A., & Löe, H. (2009). Gingivitis as a risk factor in periodontal disease. Journal of clinical periodontology, 36, 3-8. https://doi.org/10.1111/j.1600-051X.2009.01415.x

Laugisch, O., Auschill, T. M., Heumann, C., Sculean, A., & Arweiler, N. B. (2021). Clinical evaluation of a new electronic periodontal probe: a randomized controlled clinical trial. Diagnostics, 12(1), 42. https://doi.org/10.3390/diagnostics12010042

Lynch, J. E., Hinders, M. K., & McCombs, G. B. (2006). Clinical comparison of an ultrasonographic periodontal probe to manual and controlled-force probing. Measurement, 39(5), 429-439. https://doi.org/10.1016/j.measurement.2005.12.001

Mariotti, A. (1999). Dental plaque‐induced gingival diseases. Annals of periodontology, 4(1), 7-17. https://doi.org/10.1902/annals.1999.4.1.7

Moharrami, M., Vahab, E., Bagherianlemraski, M., Hemmati, G., Singhal, S., Quinonez, C., ... & Glogauer, M. (2025). Deep Learning for Detecting Dental Plaque and Gingivitis From Oral Photographs: A Systematic Review. Community Dentistry and Oral Epidemiology, 53(6), 617-632. https://doi.org/10.1111/cdoe.70001

Mostafa, D., & Fatima, N. (2022). Gingival recession and root coverage up to date, a literature review. Dentistry review, 2(1), 100008. https://doi.org/10.1016/j.dentre.2021.100008

Mutawa, A. M., Altarakemah, Y. Y., & Thirupathy, K. (2026). Deep learning applications for dental-disease classification using intraoral photographic images: Current status and future perspectives. AI, 7(3), 85. https://doi.org/10.3390/ai7030085

Nazir, M., Al-Ansari, A., Al-Khalifa, K., Alhareky, M., Gaffar, B., & Almas, K. (2020). Global prevalence of periodontal disease and lack of its surveillance. The Scientific World Journal, 2020(1), 2146160. https://doi.org/10.1155/2020/2146160

Niemczyk, W., Niemczyk, S., Prokurat, M., Grudnik, K. E., Migas, M., Wągrowska, K., ... & Kasperczyk, J. (2024). Etiology of gingival recession-a literature review. Wiadomości Lekarskie, 77(5), 1080-1085. https://doi.org/10.36740/WLek202405131

Ohashi, Y., Shimizu, T., Koyano, H., Nakamura, Y., Takahashi, D., Yamada, K., & Iwasaki, N. (2025). Evaluation of Operator Variability and Validation of an AI-Assisted α-Angle Measurement System for DDH Using a Phantom Model. Bioengineering, 12(9), 1004. https://doi.org/10.3390/bioengineering12091004

Pachiou, A., Lirgg, N., Jung, R. E., Zitzmann, N. U., & Joda, T. (2025). Sensors and wearables as key to monitor oral health: A scoping review. Digital Dentistry Journal, 100045. https://doi.org/10.1016/j.ddj.2025.100045

Panagakos, F., & Scannapieco, F. (2011). Periodontal inflammation: from gingivitis to systemic disease. Gingival diseases: Their aetiology, prevention and treatment, 155-168.

Pasupuleti, M. K., Sirisha, G., Pujitha, G., Penmetsa, G. S., Salwaji, S., & Gurindapalli, N. (2025). Assessment of gingival characteristics by professional versus smartphone imaging. Journal of Advanced Periodontology & Implant Dentistry, 18(1), 11-19. https://doi.org/10.34172/japid.026.3806

Patel, J. S., Kumar, K., Zai, A., Shin, D., Willis, L., & Thyvalikakath, T. P. (2023). Developing automated computer algorithms to track periodontal disease change from longitudinal electronic dental records. Diagnostics, 13(6), 1028. https://doi.org/10.3390/diagnostics13061028

Peikert, S. A., Mittelhamm, F., Frisch, E., Vach, K., Ratka-Krüger, P., & Woelber, J. P. (2020). Use of digital periodontal data to compare periodontal treatment outcomes in a practice-based research network (PBRN): a proof of concept. BMC Oral Health, 20(1), 297. https://doi.org/10.1186/s12903-020-01284-3

Petersen, P. E., & Ogawa, H. (2005). Strengthening the prevention of periodontal disease: the WHO approach. Journal of periodontology, 76(12), 2187-2193. https://doi.org/10.1902/jop.2005.76.12.2187

Pini‐Prato, G., Franceschi, D., Cairo, F., Nieri, M., & Rotundo, R. (2010). Classification of dental surface defects in areas of gingival recession. Journal of periodontology, 81(6), 885-890. https://doi.org/10.1902/jop.2010.090631

Pradeep, K., Rajababu, P., Satyanarayana, D., & Sagar, V. (2012). Gingival recession: review and strategies in treatment of recession. Case reports in dentistry, 2012(1), 563421. https://doi.org/10.1155/2012/563421

Rajendran, H., Balu, H. M., & Palanisamy, H. (2026). Personalized Dentistry Using Digital Technologies: Integrating Artificial Intelligence, 3D Design, and Precision Treatment Planning. Indian Journal of Computer Science and Technology, 133-143.

Ravipudi, S., Appukuttan, D., Prakash, P. S. G., & Victor, D. J. (2017). Gingival recession: Short literature review on etiology, classifications and various treatment options. Journal of Pharmaceutical Sciences and Research, 9(2), 215.

Rigo-Bonnin, R., Durán-Espín, S., Valbuena-Asensio, M., Mas-Bosch, V., & Blanco-Font, A. (2026). Comparability, compatibility, equivalence and interchangeability: metrological concepts widely misunderstood in laboratory medicine. Clinical Chemistry and Laboratory Medicine (CCLM), (0). https://doi.org/10.1515/cclm-2025-1644

Ristic, L., Dakovic, D., Postic, S., Lazic, Z., Bacevic, M., & Vucevic, D. (2019). Clinical characteristics of abutment teeth with gingival discoloration. Journal of Prosthodontics, 28(1), e45-e50. https://doi.org/10.1111/jopr.12612

Romandini, M., Soldini, M. C., Montero, E., & Sanz, M. (2020). Epidemiology of mid‐buccal gingival recessions in NHANES according to the 2018 World Workshop Classification System. Journal of Clinical Periodontology, 47(10), 1180-1190. https://doi.org/10.1111/jcpe.13353

Schnitzer, S., Türp, J. C., & Heydecke, G. (2004). Color distribution and visual color assessment of human gingiva and mucosa: a systematic review of the literature. International Journal of Prosthodontics, 17(3).

Sirintawat, N., Leelaratrungruang, T., Poovarodom, P., Kiattavorncharoen, S., & Amornsettachai, P. (2021). The accuracy and reliability of tooth shade selection using different instrumental techniques: An in vitro study. Sensors, 21(22), 7490. https://doi.org/10.3390/s21227490

Smith, R. N., Rawlinson, A., Lath, D. L., & Brook, A. H. (2006). A digital SLR or intra‐oral camera: preference for acquisition within an image analysis system for measurement of disclosed dental plaque area within clinical trials. Journal of periodontal research, 41(1), 55-61. https://doi.org/10.1111/j.1600-0765.2005.00841.x

Stambaugh, R. V., Myers, G., Ebling, W., Beckman, B., & Stambaugh, K. (2002). Endoscopic visualization of the submarginal gingiva dental sulcus and tooth root surfaces. Journal of periodontology, 73(4), 374-382. https://doi.org/10.1902/jop.2002.73.4.374

Stochkendahl, M. J., Christensen, H. W., Hartvigsen, J., Vach, W., Haas, M., Hestbaek, L., ... & Bronfort, G. (2006). Manual examination of the spine: a systematic critical literature review of reproducibility. Journal of manipulative and physiological therapeutics, 29(6), 475-485. https://doi.org/10.3390/s25113415

Stødle, I. H., Imber, J. C., Shanbhag, S. V., Salvi, G. E., Verket, A., & Stähli, A. (2025). Methods for clinical assessment in periodontal diagnostics: A systematic review. Journal of Clinical Periodontology, 52, 58-73. https://doi.org/10.1111/jcpe.14145

Strauss, F. J., Gil, A., Smirani, R., Rodriguez, A., Jung, R., & Thoma, D. (2024). The use of digital technologies in peri‐implant soft tissue augmentation–a narrative review on planning, measurements, monitoring and aesthetics. Clinical Oral Implants Research, 35(8), 922-938. https://doi.org/10.1111/clr.14238

Suchoń, S., Burkacki, M., Chrzan, M., & Winder, M. (2025). What ranges of probe pressure are applied during ultrasound examinations? a systematic review. Sensors, 25(11), 3415. https://doi.org/10.3390/s25113415

Surdu, A., Foia, C. I., Luchian, I., Trifan, D., Budala, D. G., Scutariu, M. M., ... & Tatarciuc, D. (2025). Telemedicine and digital tools in dentistry: enhancing diagnosis and remote patient care. Medicina, 61(5), 826. https://doi.org/10.3390/medicina61050826

Tang, L. H., Gonen, M., Hedvat, C., Modlin, I. M., & Klimstra, D. S. (2012). Objective quantification of the Ki67 proliferative index in neuroendocrine tumors of the gastroenteropancreatic system: a comparison of digital image analysis with manual methods. The American journal of surgical pathology, 36(12), 1761-1770.

Tobias, G., & Spanier, A. B. (2020). Developing a mobile app (iGAM) to promote gingival health by professional monitoring of dental selfies: user-centered design approach. JMIR mHealth and uHealth, 8(8), e19433. https://doi.org/10.2196/19433

Tugnait, A., & Clerehugh, V. (2001). Gingival recession—its significance and management. Journal of dentistry, 29(6), 381-394. https://doi.org/10.1016/S0300-5712(01)00035-5.