Page 217 - Control Theory in Biomedical Engineering
P. 217
198 Control theory in biomedical engineering
Hogan, N., 1985b. Impedance control: an approach to manipulation: part II—
implementation. J. Dyn. Syst. Meas. Control. 107 (1), 8–16. https://doi.org/10.1115/
1.3140713.
Hogan, N., 1985c. Impedance control: an approach to manipulation: part III—applications.
J. Dyn. Syst. Meas. Control. 107 (1), 17–24. https://doi.org/10.1115/1.3140701.
Howe, R.D., Matsuoka, Y., 1999. Robotics for surgery. Annu. Rev. Biomed. Eng. 1 (1),
211–240. https://doi.org/10.1146/annurev.bioeng.1.1.211.
Huo, W., et al., 2016. Lower limb wearable robots for assistance and rehabilitation: a state of
the art. IEEE Syst. J. 1068–1081. https://doi.org/10.1109/JSYST.2014.2351491.
Hussain, A., et al., 2014. The use of robotics in surgery: a review. Int. J. Clin. Pract. https://
doi.org/10.1111/ijcp.12492.
Jaikumar, S., Kim, D.H., Kam, A.C., 2002. History of minimally invasive spine surgery.
Neurosurgery 51 (Suppl_2), S2-1–S2-14. https://doi.org/10.1097/00006123-
200211002-00003.
Jobba ´gy, B., et al., 2014. Robotic exoskeleton for rehabilitation of the upper limb. Am. J.
Mech. Eng. 2 (7), 299–302. https://doi.org/10.12691/ajme-2-7-27.
Johnson, M.J., et al., 2008. Rehabilitation and assistive robotics [TC spotlight]. IEEE Robot.
Autom. Mag. 15 (3), 16–110. https://doi.org/10.1109/MRA.2008.928304.
Joubair, A., et al., 2016. Use of a force-torque sensor for self-calibration of a 6-DOF medical
robot. Sensors 16 (6), 798. https://doi.org/10.3390/s16060798.
Kalan, S., et al., 2010. History of robotic surgery. J. Robot. Surg. 4 (3), 141–147. https://doi.
org/10.1007/s11701-010-0202-2.
Katsura, S., Iida, W., Ohnishi, K., 2005. Medical mechatronics—an application to haptic
forceps. Annu. Rev. Control. 29 (2), 237–245. https://doi.org/10.1016/j.arcontrol.
2005.05.003.
Khanal, P., et al., 2014. Collaborative virtual reality based advanced cardiac life support train-
ing simulator using virtual reality principles. J. Biomed. Inform. 51, 49–59. https://doi.
org/10.1016/j.jbi.2014.04.005.
Kim, K.C., 2014. Kim, K.C. (Ed.), Robotics in General Surgery. Springer, New York, NY.
https://doi.org/10.1007/978-1-4614-8739-5.
Kim, E.J., et al., 2005. A biofidelic birthing simulator. IEEE Eng. Med. Biol. Mag. https://
doi.org/10.1109/memb.2005.1549728.
Kramme, R., Hoffmann, K.P., Pozos, R.S., 2011. Springer Handbook of Medical
Technology. In: Kramme, R., Hoffmann, K.-P., Pozos, R.S. (Eds.), Springer, Berlin,
Heidelberg. https://doi.org/10.1007/978-3-540-74658-4.
Krebs, H.I., Volpe, B.T., 2013. Rehabilitation robotics. In: Handbook of Clinical Neurol-
ogy. pp. 283–294. https://doi.org/10.1016/B978-0-444-52901-5.00023-X.
Krebs, H.I., et al., 1998. Robot-aided neurorehabilitation. IEEE Trans. Rehabil. Eng. 6 (1),
75–87. https://doi.org/10.1109/86.662623.
Kwoh, Y.S., et al., 1988. A robot with improved absolute positioning accuracy for CT
guided stereotactic brain surgery. IEEE Trans. Biomed. Eng. https://doi.org/
10.1109/10.1354.
Lane, T., 2018. A short history of robotic surgery. Ann. R. Coll. Surg. Engl. https://doi.org/
10.1308/rcsann.supp1.5.
Lanfranco, A.R., et al., 2004. Robotic surgery. Ann. Surg. 239 (1), 14–21. https://doi.org/
10.1097/01.sla.0000103020.19595.7d.
Le, H.M., Do, T.N., Phee, S.J., 2016. A survey on actuators-driven surgical robots. Sensors
Actuators A Phys. 247, 323–354. https://doi.org/10.1016/j.sna.2016.06.010.
Leal Ghezzi, T., Campos Corleta, O., 2016. 30 years of robotic surgery. World J. Surg.
40 (10), 2550–2557. https://doi.org/10.1007/s00268-016-3543-9.
Lee, C., et al., 2017. Soft robot review. Int. J. Control. Autom. Syst. https://doi.org/
10.1007/s12555-016-0462-3.