Theoretical Smart Design and Control for an Atruamatic Grasper


  • Yazen H. Alnema
  • Mohammed Abdulmalek Ahmed
  • Simon Venn





Accurate knowledge of the grasping force is essential when avoiding tissue trauma during grasping and manipulation in abdominal surgery. The aim of this paper is to present a theoretical design of laparoscopic grasper complete with control system. Mechanically the design comprises of a load cell and actuator added to the traditional grasper. The original grasper was also modified slightly for example, the standard type of teeth were replaced with waveform teeth to maximise grip yet reducing the chance of tissue trauma.  Control wise the grasper works by the load cell measuring the applied force which then controls the actuator via the control system. The applied force on the tissue either increases or decreases so that the demand force and the output force applied to the tissue are the same. To simulate the force the load cell would experience the Generalised Maxwell model was used to simulate the viscoelastic characteristics of a biological tissue.


[1] Mack, M. J. Minimally invasive and robotic surgery. Jama. 2001, 285(5), pp. 568-572.

[2] Vitiello, S.-L. Lee, T. P. Cundy, and G.-Z. Yang, ‘Emerging Robotic Platforms for Minimally Invasive Surgery’, IEEE Reviews in Biomedical Engineering, vol. 6, pp. 111–126, Jan. 2013.

[3] Shakeel, P.M., Tolba, A., Al-Makhadmeh, Zafer Al-Makhadmeh, Mustafa Musa Jaber, “Automatic detection of lung cancer from biomedical data set using discrete AdaBoost optimized ensemble learning generalized neural networksâ€, Neural Computing and Applications,2019,pp1-14.

[4] Visser, H. et al. Forces and displacements in colon surgery. Surgical Endoscopy and Other Interventional Techniques.2002, 16(10), pp.14263-1430.

[5] Preeth, S.K.S.L., Dhanalakshmi, R., Kumar, R.,Shakeel PM.An adaptive fuzzy rule based energy efficient clustering and immune-inspired routing protocol for WSN-assisted IoT system.Journal of Ambient Intelligence and Humanized Computing.2018:1–13.

[6] J. J. Dobbelsteen, R. A. Lee, M. Noorden, and J. Dankelman, ‘Indirect measurement of pinch and pull forces at the shaft of laparoscopic graspers’, Medical & Biological Engineering & Computing, vol. 50, no. 3, pp. 215–221, Jan. 2012.

[7] D. D. Marucci, J. A. Cartmill, W. R. Walsh, and C. J. Martin, ‘Patterns of Failure at the Instrument–Tissue Interface’, Journal of Surgical Research, vol. 93, no. 1, pp. 16–20, Jan. 2000.

a. Tirella, G. Mattei and A. Ahluwalia, "Strain rate viscoelastic analysis of soft and highly hydrated biomaterials," Journal of Biomedical Materials Research Part A, vol. 102, no. 10, pp. 3352-3360, 2013.

[8] W. Platzer, H. W. Schreiber, and K. Kremer, Minimally Invasive Abdominal Surgery. United States: Thieme Medical Publishers, Incorporated, 2001.

[9] P. Mohamed Shakeel; Tarek E. El. Tobely; Haytham Al-Feel; Gunasekaran Manogaran; S. Baskar., “Neural Network Based Brain Tumor Detection Using Wireless Infrared Imaging Sensorâ€, IEEE Access, 2019, Page(s): 1

[10] Vakili, K. et al. Design and testing of a pressure sensing laparoscopic grasper. In: Proceedings of the 2011 Design of Medical Devices Conference, DMD2011. USA, 2011, pp.1-8.

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