Current Approaches to Bone-Drilling Procedures with Orthopedic Drills

In order to minimize complications during orthopedic surgery, the important of research in this field is gaining importance and more studies are being conducted. The use of robotics and autonomous systems is gaining importance to achieve the aims reducing complications, lowering operation times, and increasing the surgical reliability and effectiveness in bone drilling operations that constitute a sub-set of the Computer-Aided Orthopedic Surgery (CAOS) issue. In this study, signal processing-based approaches for breakthrough detection during bone drilling operations, robotic autonomous systems that optimize optimal plunge and drilling speed while drilling, most effective drilling parameters that affect bone perforation, and studies conducted to improve the safety and efficiency of surgical operations, such as radiological imaging, were investigated. A systematic review of recent studies on bone drilling was performed and potential research topics were proposed for possible future studies.


1. Bertollo N, Robert W. Drilling of Bone: Practicality, Limitations and Complications Associated with Surgical Drill-Bits. In: Biomechanics in Applications. 2012. [CrossRef]

2. Gönen E. Minimally invasive surgical techniques for the treatment of the shaft fractures of the long bones. Türk Ortop ve Travmatoloji Birliği Derneği Derg. 2012; 11(1): 78–88. [CrossRef]

3. Farouk O, Krettek C, Miclau T, Schandelmaier P, Guy P, Tscherne H. Minimally invasive plate osteosynthesis: Does percutaneous plating disrupt femoral blood supply less than the traditional technique? J Orthop Trauma. 1999; 13(6): 401-6. [CrossRef]

4. Augustin G, Zigman T, Davila S, Udilljak T, Staroveski T, Brezak D, et al. Cortical bone drilling and thermal osteonecrosis. Clin Biomech Elsevier 2012; 27(4): 313-25. [CrossRef]

5. Praamsma M, Carnahan H, Backstein D, Veillette CJH, Gonzalez D, Dubrowski A. Drilling sounds are used by surgeons and intermediate residents, but not novice orthopedic trainees, to guide drilling motions. Can J Surg 2008; 51(6): 442-6.

6. Phadnis VA, Makhdum F, Roy A, Silberschmidt V V. Drilling in carbon/epoxy composites: Experimental investigations and finite element implementation. Compos Part A Appl Sci Manuf 2013; 47(1): 41-51. [CrossRef]

7. Modi RA, Nayak RP. Detection of breakthrough during bone-drilling in orthopaedic surgery. IJTRE 2014; 1(9): 794-8.

8. Wang S, Zhen Z, Zheng F, Wang X. Design of autonomous flight control system for small-scale UAV. 2014 IEEE Chinese Guid Navig Control Conf CGNCC 2014. 2015; 1885-8. [CrossRef]

9. Torun Y, Ozturk A, Hatipoglu N, Oztemur Z. Breakthrough detection for orthopedic bone drilling via power spectral density estimation of acoustic emission. 2018 Electr Electron Comput Sci Biomed Eng Meet EBBT 2018. 2018;1–5. [CrossRef]

10. Torun Y, Ozturk A, Hatipoglu N, Oztemur Z. Detection of Bone Excretion with Current Sensor in Robotic Surgery. In: UBMK 2018 - 3rd International Conference on Computer Science and Engineering. 2018. [CrossRef]

11. Brett PN, Baker DA, Naghdy F. Automatic Detection of Normal Drill Breakthrough Through Planar Bone Tissues of Unknown Thickness. IFAC Proc Vol 1997; 30(7): 609-12. [CrossRef]

12. Lee W-Y, Shih C-L. Control and breakthrough detection of a three-axis robotic bone drilling system. Mechatronics. Pergamon 2006; 16(2): 73-84. [CrossRef]

13. Kotev V, Boiadjiev G, Kawasaki H, Mouri T, Delchev K, Boiadjiev T. Design of a hand-held robotized module for bone drilling and cutting in orthopedic surgery. 2012 IEEE/SICE Int Symp Syst Integr SII 2012. 2012; 504-9. [CrossRef]

14. Boiadjiev G, Zagurski K, Boiadjiev T, Delchev K, Kastelov R, Kotev V. Robot application in orthopedic surgery: drilling control. GSTF J Eng Technol 2014; 1(1): 125-30. [CrossRef]

15. Qi L, Meng MQH. Real-time break-through detection of bone drilling based on wavelet transform for robot assisted orthopaedic surgery. 2014 IEEE Int Conf Robot Biomimetics, IEEE ROBIO 2014. 2014; 601-6. [CrossRef]

16. Zhang J, Zhang L, Jin H, Hu Y, Zhang P. State Recognition of Pedicle Drilling With Force Sensing in a Robotic Spinal Surgical System. IEEE/ASME Trans Mechatronics 2013; 19(1): 357-65. [CrossRef]

17. Wang Y, Deng Z, Sun Y, Yu B, Zhang P, Hu Y, et al. State detection of bone milling with multi-sensor information fusion. 2015 IEEE Int Conf Robot Biomimetics, IEEE-ROBIO 2015 2015; 1643-8. [CrossRef]

18. Li Y, Li X, Feng GU, Gao Z, Shen P. New method for identifying abnormal milling states of an otological drill. Med Devices 2015; 8: 207–18. [CrossRef]

19. Mallapragada V, Erol D, Sarkar N. A new method of force control for unknown environments. Int J Adv Robot Syst 2007; 4(3): 313- 22. [CrossRef]

20. Feio J, Martins J, Costa J da. Variable Impedance Control of Manipulator Robots Applied to Orthopedic Surgery. Proc Work Adv Control Diagnosis, 2009.

21. Kawasaki H, Kotev V, Delchev K, Boiadjiev T, Mouri T, Boiadjiev G. A Design Concept of an Orthopedic Bone Drilling Mechatronics System. Appl Mech Mater 2013; 302: 248-51. [CrossRef]

22. Kasi V, Mekhilef S, Ghazilla RAR, Ahmad N. Robotic system development for cooperative orthopedic drilling assistance. Adv Mech Eng 2014; 2014. [CrossRef]

23. Jin H, Hu Y, Tian W, Zhang P, Zhang J, Li B. Safety analysis and control of a robotic spinal surgical system. Mechatronics. Elsevier Ltd 2014; 24(1): 55-65. [CrossRef]

24. Taha Z, Salah AM, Lee J V. Bone Breakthrough Detection for Orthopedic Robot - Assisted Surgery. APIEMS 2008 Proc 9th Asia Pasific Ind Eng Manag Syst Conf 2008; 2742–6.

25. Kinsheel A. Hybrid Force / Position Control of Robotic Drilling System. International Conference on Control, Decision and Information Technologies 2014; (CoDIT): 3704 [CrossRef]

26. Hessinger M, Pingsmann M, Perry JC, Werthschutzky R, Kupnik M. Hybrid position/force control of an upper-limb exoskeleton for assisted drilling. IEEE Int Conf Intell Robot Syst 2017; 2017: 18249. [CrossRef]

27. Boiadjiev G, Chavdarov I, Delchev K, Boiadjiev T, Kastelov R, Zagurki K. Development of Hand-Held Surgical Robot ODRO-2 for Automatic Bone Drilling. J Theor Appl Mech 2017; 47(4): 12–22. [CrossRef]

28. Lee J, Gozen BA, Ozdoganlar OB. Modeling and experimentation of bone drilling forces. J Biomech 2012; 45(6): 1076-83. [CrossRef]

29. Jin H, Hu Y, Luo H, Zheng T, Zhang P. Intraoperative state recognition of a bone-drilling system with image-force fusion. IEEE Int Conf Multisens Fusion Integr Intell Syst 2012; 275–80. [CrossRef]

30. Aziz MH, Ayub MA, Jaafar R. Real-time algorithm for detection of breakthrough bone drilling Procedia Eng 2012; 41: 352-9. [CrossRef]

31. Lee W-YLW-Y, Shih C-LSC-L. Force control and breakthrough detection of a bone drilling system. 2003 IEEE Int Conf Robot Autom (Cat No03CH37422). 2003; 2(1): 1787-92.

32. Hessinger M, Hielscher J, Pott PP, Werthschutzky R. Handheld surgical drill with integrated thrust force recognition. 2013 E-Health Bioeng Conf EHB 2013. 2013; 1-4. [CrossRef]

33. Singh AP, Sharma M. Modeling and PID control of thrust force during drilling in composite laminates. 2014 Recent Adv Eng Comput Sci RAECS 2014. 2014; 6-8. [CrossRef]

34. Tian W, Han X, Liu B, Liu Y, Hu Y, Han X, et al. A robot-assisted surgical system using a force-image control method for pedicle screw insertion. PLoS One 2014; 9(1): 1-9. [CrossRef]

35. Zhang P, Tian W, Zhang J, Hu Y, Deng Z, Jin H, et al. Fuzzy force control and state detection in vertebral lamina milling. Mechatronics 2016; 35: 1-10. [CrossRef]

36. Xi–sheng L, Guo–dong F, Zhi–qiang G, Shen P, Tian–yang C. An Intelligent Otologic Drill. J Otol [Internet]. Elsevier Masson SAS; 2014; 5(2): 104–10. [CrossRef]

37. Yu K, Iwata S, Ohnishi K, Kawana H, Usuda S. Real-time CT value estimation method for robotic drilling system based on thrust force and torque. IECON Proc (Industrial Electron Conf). 2013; 3717- 22. [CrossRef]

38. Accini F, Diaz I, Gil JJ. Bone recognition during the drilling process. Proc IEEE RAS EMBS Int Conf Biomed Robot Biomechatronics. 2016: 305–10. [CrossRef]

39. Jin H, Hu Y, Deng Z, Zhang P, Song Z, Zhang J. Model-based state recognition of bone drilling with robotic orthopedic surgery system. Proc - IEEE Int Conf Robot Autom. 2014; 3538–43. [CrossRef]

40. Al-Abdullah KIA lateef, Abdi H, Lim CP, Yassin W. Force and temperature modelling of bone milling using artificial neural networks. Meas J Int Meas Confed 2018; 116: 25-37. [CrossRef]


Cyprus Journal of Medical Sciences
  • ISSN: 2149-7893
  • Yayın Aralığı: Yılda 4 Sayı
  • Başlangıç: 2016
  • Yayıncı: AVES Yayıncılık


Sayıdaki Diğer Makaleler

Effects of Acute and Chronic Exercises on Plasma Nesfatin-1 Levels in Young Adults


Demographic and Clinical Analysis and Outcome of Critically Ill Patients in a Northern Cyprus Hospital

Atalay ARKAN, Nedim ÇAKIR, Kaya SÜER, İlker GELİŞEN, Selin ÖZCEM, İlker ETİKAN

Knowledge and View of Mothers Whose Babies in Newborn Intensive Care Units About Breast Milk Banking in Turkey

Reyyan GÜREL, Ayten Şentürk ERENEL

Evaluation of the Psychosocial Effects of Long-Term Genital HPV Infection


Comparison of Transhiatal and Transthoracic Approaches in Esophageal Cancer Surgery

Orçun YALAV, Uğur TOPAL, Burak YAVUZ, Kubilay DALCI

Childhood and Adolescence Vitiligo: Clinicoepidemiological Profile and Its Impact on Quality of Life


Determining the Effects of the Monitoring and Counseling in Addition to Standard Monitoring on the Abstinence after Quit Smoking: A Randomized Controlled Study


A Comparative Study on the Effect of Using Three Maternal Positions on Postpartum Bleeding, Perineum Status and Some of the Birth Outcomes During Lathent and Active phase of the Second Stage of Labor


Delirium Awareness and Treatment Approach in Orthopedics Clinic


Top 100-Cited Articles in Tinnitus: A Bibliometric Analysis

Seyit Mehmet CEYLAN