Design, implementation and evaluation of an independent real-time safety layer for medical robotic systems using a force–torque–acceleration (FTA) sensor

  • Lars Richter
  • Ralf Bruder
Original Article


Purpose Most medical robotic systems require direct interaction or contact with the robot. Force–Torque (FT) sensors can easily be mounted to the robot to control the contact pressure. However, evaluation is often done in software, which leads to latencies.

Methods To overcome that, we developed an independent safety system, named FTA sensor, which is based on an FT sensor and an accelerometer. An embedded system (ES) runs a real-time monitoring system for continuously checking of the readings. In case of a collision or error, it instantaneously stops the robot via the robot’s external emergency stop.

Results We found that the ES implementing the FTA sensor has a maximum latency of \(1\pm 0.03\) ms to trigger the robot’s emergency stop. For the standard settings in the application of robotized transcranial magnetic stimulation, the robot will stop after at most 4 mm.

Conclusion Therefore, it works as an independent safety layer preventing patient and/or operator from serious harm.


Safety Medical robotics Real-time system Force–torque sensor Acceleration sensor Robotized transcranial magnetic stimulation 



This work was partially supported by the Graduate School for Computing in Medicine and Life Sciences funded by Germany’s Excellence Initiative [DFG GSC 235/1]. Conflict of interest   None.


  1. 1.
    Adler JR Jr, Chang SD, Murphy MJ, Doty J, Geis P, Hancock SL (1997) The CyberKnife: a frameless robotic system for radiosurgery. Stereotact Funct Neurosurg 69:124–128. doi: 10.1159/000099863 PubMedCrossRefGoogle Scholar
  2. 2.
    Baik SH (ed) (2010) Robot surgery. InTech, Vukovar, CroatiaGoogle Scholar
  3. 3.
    Benabid A, Cinquin P, Lavalle S, Le Bas J, Demongeot J, De Rougemont J (1987) Computer-driven robot for stereotactic surgery connected to ct scan and magnetic resonance imaging. Stereotact Funct Neurosurg 50(1-6):153–154CrossRefGoogle Scholar
  4. 4.
    Bozovik V (ed) (2008) Medical robotics. InTech, Vienna, AustriaGoogle Scholar
  5. 5.
    Craig JJ (2005) Introduction to robotics: mechanics and control, 3rd edn. Prentice Hall, Englewood CliffsGoogle Scholar
  6. 6.
    Dombre E, Duchemin G, Poignet P, Pierron F (2003) Dermarob: a safe robot for reconstructive surgery. IEEE Trans Robotics Autom 19(5):876–884. doi: 10.1109/tra.2003.817067 CrossRefGoogle Scholar
  7. 7.
    Drake JM, Joy M, Goldenberg A, Kreindler D (1991) Computer-and robot-assisted resection of thalamic astrocytomas in children. Neurosurgery 29(1):27PubMedCrossRefGoogle Scholar
  8. 8.
    Kwoh YS, Hou J, Jonckheere E, Hayati S (1988) A robot with improved absolute positioning accuracy for ct guided stereotactic brain surgery. IEEE Trans Biomed Eng 35(2):153–160PubMedCrossRefGoogle Scholar
  9. 9.
    Lancaster JL, Narayana S, Wenzel D, Luckemeyer J, Roby J, Fox P (2004) Evaluation of an image-guided, robotically positioned transcranial magnetic stimulation system. Hum Brain Mapp 22(4):329–340. doi: 10.1002/hbm.20041 PubMedCrossRefGoogle Scholar
  10. 10.
    Lanfranco AR, Castellanos AE, Desai JP, Meyers WC (2004) Robotic surgery: a current perspective. Ann Surg 239(1):14PubMedCrossRefGoogle Scholar
  11. 11.
    Lebossé C, Renaud P, Bayle B, de Mathelin M, Piccin O, Foucher J (2007) A robotic system for automated image-guided transcranial magnetic stimulation. In: Life science systems and applications workshop, 2007, LISA 2007, IEEE/NIH, pp 55–58. doi: 10.1109/lssa.2007.4400883
  12. 12.
    Li QH, Zamorano L, Pandya A, Perez R, Gong J, Diaz F (2002) The application accuracy of the NeuroMate robot–a quantitative comparison with frameless and frame-based surgical localization systems. Comput Aided Surg 7(2):90–98PubMedGoogle Scholar
  13. 13.
    Matthäus L (2002) A robotic assistance system for transcranial magnetic stimulation and its application to motor cortex mapping. Ph.D. thesis, Universität zu LübeckGoogle Scholar
  14. 14.
    Matthäus L, Giese A, Wertheimer D, Schweikard A (2006) Planning and analyzing robotized tms using virtual reality. Stud Health Technol Inform 119:373–378 PubMedGoogle Scholar
  15. 15.
    Matthäus L, Trillenberg P, Bodensteiner C, Giese A, Schweikard A (2006) Robotized TMS for motion compensated navigated brain stimulation. In: Computer assisted radiology and surgery (CARS), 20th international congress. Osaka, JapanGoogle Scholar
  16. 16.
    Medtech: Rosa neurosurgery robot. Tech. rep., Medtech SAS, Montepllier, France (2011)
  17. 17.
    Morgan PS, Carter T, Davis S, Sepehri A, Punt J, Byrne P, Moody A, Finlay P (2003) The application accuracy of the pathfinder neurosurgical robot. International congress series CARS 2003. Computer Assisted Radiology and Surgery. Proceedings of the 17th international congress and Exhibition, pp 561–567Google Scholar
  18. 18.
    Renaud P, Piccin O, Lebossé C, Laroche E, de Mathelin M, Bayle B, Foucher J (2006) Robotic image-guided transcranial magnetic stimulation. In: Computer assisted radiology and surgery (CARS), 20th international congress. Osaka, JapanGoogle Scholar
  19. 19.
    Richter L, Bruder R, Schweikard A (2012) Calibration of force/torque and acceleration for an independent safety layer in medical robotic systems. Cureus 4(9):e59. doi: 10.7759/cureus.59
  20. 20.
    Richter L, Bruder R, Schweikard A (2012) Hand-assisted positioning and contact pressure control for motion compensated robotized transcranial magnetic stimulation. Int J Comput Assist Radiol Surg 1–8 [Epub ahead of print]. doi: 10.1007/s11548-012-0677-6
  21. 21.
    Schweikard A, Bodduluri M, Adler JR Jr (1998) Planning for camera-guided robotic radiosurgery. IEEE Trans Rob Autom 14(6):951–962. doi: 10.1109/70.736778 CrossRefGoogle Scholar
  22. 22.
    Taylor RH (2006) A perspective on medical robotics. Proc IEEE 94(9):1652–1664. doi: 10.1109/jproc.2006.880669 CrossRefGoogle Scholar
  23. 23.
    Yi X, Bicker R (2010) Design of a robotic transcranial magnetic stimulation system. In: IEEE conference on robotics, automation and mechatronics, SingaporeGoogle Scholar
  24. 24.
    Zorn L, Renaud P, Bayle B, Goffin L, Lebossé C, de Mathelin M (2012) Design and evaluation of a robotic system for transcranial magnetic stimulation. IEEE Trans Biomed Eng 59(3):805–815. doi: 10.1109/tbme.2011.2179938 Google Scholar

Copyright information

© CARS 2012

Authors and Affiliations

  1. 1.Institute for Robotics and Cognitive SystemsUniversity of LübeckLüebeckGermany
  2. 2.Graduate School for Computing in Medicine and Life SciencesUniversity of LübeckLübeckGermany

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