Scholarly record
THE ADAPTIVE BIOMECHANICAL MODEL OF THE SPINE OF HUMAN
Abstract
In this paper, the principle of constructing an adaptive biomechanical model of the spine is described, which allows modeling damage to the spinal segments, spinal cord and nerve roots, as well as taking into account the perception and tolerability of pain. Adaptability of this model is achieved due to the possibility of introducing individual parameters of a particular segment (geometric dimensions and spatial coordinates of the elements (vertebra, intervertebral disc, nerve roots, spinal canal); modulus of elasticity of bone, cartilaginous and nerve tissues; structural parameters of tissues), while forming the entire vertebrae from the set of segments obtained on the basis of the adaptive model. The developed model of the vertebral segment will make it possible to analyze the spine, by the varying of the parameters (individual properties) of the segments under study, and will predict the development of various diseases and pathologies (osteoporosis, osteochondrosis, neuropathy, neuralgia, spondylosis, etc.). Based on the developed model, it is possible to evaluate the stress-strain state of the spinal segment in various states under functional loads.
Publication Impact Profile
Publication details
References15
Avdeeva K. Yu., Sivets Yu. V., Gladkov A. V. New approach in the use of the mathematical apparatus in the construction of the three-dimensional model of the spine / Spinal surgery. 2005. № 1.
Latyshev K.S., Orlov S.V., Bobarykin N.D., Ivanov A.A., Kozhurov I.M., Mathematical model of spine instability in angular deformity of the vertebra / Bulletin of the Baltic Federal University. I. Kant. Series: Physics and mathematics and engineering. 2006. №10.
Orlov S.V., Sedov R.L., Bobarykin N.D., Apollinariev V..I, Mathematical modeling of spinal instability and stabilization methods / Russian Journal of Biomechanics. 2010. № 3.
Kirilova I. A., Podorozhnaya V.T., Legostaeva E.V., Sharkeev Yu. P. and all Kostnoplastic biomaterials and their physical and mechanical properties / Spinal surgery. 2010. №1.
Gonzalez R., Woods R. Digital image processing. M .: Technosphere, 2005. 1072 p
Pratt W. Digital imaging: Trans. with English. Moscow: Mir, 1982. Book 2. 480 p.
Masalitina N.N., Kurochka K.S. Application of the automated classifier of the results of computed tomography for constructing the geometric model of the human vertebra / Reports of BSUIR. 2017. № 3 (105).
Leskov A.G., Seliverstova E.Calculation of the areas of intersection of the surfaces of gripping devices of manipulators and deformable objects in the planning and modeling of capture / Vestnik MSTU them. N.E. Bauman. Series "Instrument-Making". 2016. №6 (111).
Yury Lifshits Algorithms for Nearest Neighbors: Theoretical Aspects Steklov Institute of Mathematics at St.Petersburg Kolmogorov Seminar, April 2007 URL: http://www.gproxx.com/https://logic.pdmi.ras.ru/~yura/en/nn-kolmogorov-talk.pdf
P.N. Yianilos Data structures and algorithms for nearest neighbor search in general metric spaces URL: http://www.pnylab.com/pny/papers/vptree/vptree.ps
Preparata F.P., Shamos M.I. Computational geometry: an introduction. New York, Spinger-Verlag. 412 p. (Russ. ed.: Vychislitelnaya geometriya. Moscow, Mir Publ., 1989. 478 p.).
Panigrahy R. An improved algorithm finding nearest neighbor using Kd-trees. Proc. 8th Latin American Symposium, Bzios, Brazil, 2008, vol. 26, no. 4, pp. 387–398.
Maneewongvatana S., Mount D.M. An empirical study of a new approach to nearest neighbor searching. Proc. third international workshop on algorithm engineering and experimentation, Washington, DC, USA, 2001, pp. 172–187.
Yianilos P.N. Data structures and algorithms for nearest neighbor search in general metric spaces. Proc. fourth annual ACM-SIAM Symposium on Discrete algorithms, Austin, TX, USA, 1993, pp. 311–321.
Grecheneva, A., Kuzichkin, O., Dorofeev, N. The algorithm for express-analysis of human functional systems considering of the goniometric control data // International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM Volume 17, Issue 61, 2017, Pages 1081-1088.
View or Download full articleAccess options
SWS access login
Login as SWS Scientific CommitteeLogin as SWS Scientific PartnerLogin as SWS AuthorAuthors and approved SWS contributors will read and export their own linked papers after identity matching by SWS profile, email and SGEM GlobalID.
For librarian assistance: [email protected]
Purchase Instant Access
- Article can be downloaded after successful payment.
- Article may be used according to SWS library access terms.
- Article cannot be redistributed.
