Automation and Robotics in Biosensing for Early Diagnosis and Monitoring of Peri-Implantitis – A Systematic Review.

Authors

  • Ramyaa D PhD Scholar (BIHER), Associate Professor, Department of Prosthodontics and Crown & Bridge, Sree Balaji Dental College and Hospital, Chennai, Tamil Nadu, India
  • S Bhuminathan Professor, Department of Prosthodontics and Crown & Bridge, Sree Balaji Dental College and Hospital,Chennai, Tamil Nadu, India
  • Nithan S Postgraduate Student, Department of Prosthodontics and Crown & Bridge, Sree Balaji Dental College and Hospital, Chennai, Tamil Nadu, India
  • Nandini M S Associate Professor, Department of Microbiology, Sree Balaji Medical College and Hospital, BIHER, Chennai, Tamil Nadu, India
  • L Keerthi Sasanka Associate Professor, Department of Microbiology, Sree Balaji Medical College and Hospital, BIHER, Chennai, Tamil Nadu, India
  • Prabhu Manickam Natarajan Department of Clinical Sciences, Centre of Medical and Bio-Allied Health Sciences and Research, College of Dentistry, Ajman University, Ajman 346, United Arab Emirates

DOI:

https://doi.org/10.3329/bjms.v25i10.86619

Keywords:

Peri-implantitis, Biosensors, Automation, Robotics, Early Diagnosis, Systematic Review.

Abstract

Background Peri-implantitis is a progressive inflammatory illness that affects implant longevity. Early detection and continuous monitoring are crucial for efficient management. Recent breakthroughs in biosensing, automation, and robotics offer exciting prospects. The purpose of this systematic review is to assess the effectiveness of automation and robotic-assisted biosensing technologies in the early detection and real-time monitoring of peri-implantitis. Methods A complete search of PubMed, Scopus, Cochrane Library, IEEE Xplore, and Web of Science (2013- 2024) was carried out. Studies that used biosensors with automated or robotic systems to diagnose periimplantitis were considered. Methodological quality was evaluated using the PRISMA and ROBIS methods. Results 34 out of 562 articles met the requirements. Biosensing platforms (optical, electrochemical, piezoelectric) with AI integration demonstrated great sensitivity (80-95%) and specificity (85-98%) in detecting early biomarkers such as IL-1β, TNF-α, and MMPs. Robotic systems improved reproducibility and patient comfort. Conclusion While promising, more clinical validation and standardization are required for general implementation.

Bangladesh Journal of Medical Science Vol. 25. Supplementary Issue 2026, Page : S18-S25

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Author Biographies

Ramyaa D, PhD Scholar (BIHER), Associate Professor, Department of Prosthodontics and Crown & Bridge, Sree Balaji Dental College and Hospital, Chennai, Tamil Nadu, India

 

 

S Bhuminathan, Professor, Department of Prosthodontics and Crown & Bridge, Sree Balaji Dental College and Hospital,Chennai, Tamil Nadu, India

 

 

Nithan S, Postgraduate Student, Department of Prosthodontics and Crown & Bridge, Sree Balaji Dental College and Hospital, Chennai, Tamil Nadu, India

 

 

Nandini M S, Associate Professor, Department of Microbiology, Sree Balaji Medical College and Hospital, BIHER, Chennai, Tamil Nadu, India

 

 

L Keerthi Sasanka, Associate Professor, Department of Microbiology, Sree Balaji Medical College and Hospital, BIHER, Chennai, Tamil Nadu, India

 

 

Prabhu Manickam Natarajan, Department of Clinical Sciences, Centre of Medical and Bio-Allied Health Sciences and Research, College of Dentistry, Ajman University, Ajman 346, United Arab Emirates

 

 

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Published

2026-01-06

How to Cite

D, R., Bhuminathan, S., S, N., M S, N., Sasanka, L. K., & Natarajan, P. M. (2026). Automation and Robotics in Biosensing for Early Diagnosis and Monitoring of Peri-Implantitis – A Systematic Review. Bangladesh Journal of Medical Science, 25(10), S18-S25. https://doi.org/10.3329/bjms.v25i10.86619

Issue

Vol: 25. Supplementary issue 2026

Section

Review Article

License

Copyright (c) 2026 Ramyaa D, S Bhuminathan, Nithan S, Nandini M S, L. Keerthi Sasanka, Prabhu Manickam Natarajan

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