Abstract
In precision computer and robotic assisted minimally invasive surgical procedures, such as retinal microsurgery or cardiac bypass surgery, physiological motion can hamper the surgeon’s ability to effectively visualize and approach the target site. Current day stabilizers used for minimally invasive cardiac surgery often stretch or pull at the tissue, causing subsequent tissue damage. In this study, we investigated novel means of modeling Z-axis physiological motion and demonstrate how these models could be used to compensate for this motion in order to provide a more stable surgical field. The Z-axis motion compensation is achieved by using a fiber-optic laser sensor to obtain precise displacement measurements. Using a weighted time series modeling technique, modeling of rodent chest wall motion and heart wall motion was accomplished. Our computational methods for modeling physiological motion open the door for applications using high speed, high precision actuators to filter motion out and provide for a stable surgical field.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Ko, W. Advances in Cardiovascular Surgery–Minimally Invasive Cardiac Surgery. in 1997 CAMS Semiannual Scientific meeting. 1997. New York.
Matsuda, H., et al., Minimally Invasive Cardiac Surgery: Current Status and Perpective. Artificial Organs, 1998. 22(9): p. 759–64.
Mayer, P.W., Relative Motion Cancelling, in Patent No. 5871017. 1999: US.
Rousou, J.A., et al., Fenestrated felt facilitates anastomotic stability and safety in & “off-pump” coronary bypass. Ann Thorac Surg, 1999. 68(1): p. 272–3.
Jansen, E.W.L., et al., Coronary Artery Bypass Grafting Without Cardiopulmonary Bypass Using the Octopus Method: Results in the First One Hundred Patients. The Journal of Thoracic and Cardiovascular Surgery, 1998. 116(1): p. 60–67.
Trejos, A.L., et al. On the Feasibility of a Moving Support for Surgery on the Beating Heart. in Medical Image Computing and Computer-Assisted Intervention–MICCAI’99: Second International Conference. 1999. Cambridge, UK.
Widrow, B. and S.D. Stearns, Adaptive signal processing. Prentice-Hall signal processing series. 1985, Englewood Cliffs: Prentice-Hall. xviii, 474.
Walter, D.O., A posteriori Wiener Filtering of average evoked responses. Electroencephalogr Clin Neurophysiol, 1968.:Suppl(27): p. 61+.
Widrow, B. and J.M.E. Hoff. Adaptive switching circuites. in IRE WESCON Conv. Rec. 1960.
Metz, S., An Intraoperative Monitoring System for the analysis of Evoked Potentials, in Biomedical Engineering. 1999, Johns Hopkins University: Baltimore. p. 159.
Vaz, C.A. and N.V. Thakor, Adaptive Fourier estimation of time-varying evoked potentials. IEEE Trans Biomed Eng, 1989. 36(4): p. 448–55.
Riviere, C.N., Adaptive suppression of tremor for improved human-machine control., in Biomedical Engineering. 1995, Johns Hopkins Univesity: Baltimore, Md.
Vaz, C., X. Kong, and N.V. Thakor, An adaptive estimation of periodic signals using a Fourier linear combiner. IEEE Transactions in Signal Processing, 1994. 42: p. 1–10.
Riviere, C.N., R.S. Rader, and N.V. Thakor, Adaptive canceling of physiological tremor for improved precision in microsurgery. IEEE Trans Biomed Eng, 1998. 45(7): p. 839–46.
Gresty, M. and D. Buckwell, Spectral analysis of tremor: understanding the results. J Neurol Neurosurg Psychiatry, 1990. 53(11): p. 976–81.
Kwong, R. and E. Johnston, A Variable Step Size LMS Algorithm. IEEE Transactions in Signal Processing, 1992. 40(7): p. 1633–1642.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Thakral, A., Wallace, J., Tomlin, D., Seth, N., Thakor, N.V. (2001). Surgical Motion Adaptive Robotic Technology (S.M.A.R.T): Taking the Motion out of Physiological Motion. In: Niessen, W.J., Viergever, M.A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001. MICCAI 2001. Lecture Notes in Computer Science, vol 2208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45468-3_38
Download citation
DOI: https://doi.org/10.1007/3-540-45468-3_38
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42697-4
Online ISBN: 978-3-540-45468-7
eBook Packages: Springer Book Archive