Jorge Torres Gómez
Regine Wendt
Falko Dressler
ABSTRACT
Recent advances in nanotechnology show possible applications of nano-devices within the human body. For example, technical solutions are under development to make use of nanobots to carry and release drugs via the circulatory system. In this scenario, it is important to study the location and the location distribution of nanobots in the human circulatory system (HCS). However, due to bifurcations and the variety of structures in the human vessels, this problem is rather challenging. In this paper, we address a new methodology based on a Markov chain model to study the distribution of nanobots in the HCS. The transition probabilities are assessed through analogies of their representation with an electric circuit representation of the HCS. Additionally, we conducted simulations in the simulation framework BloodVoyagerS to compare results with the provided Markov model. Our evaluation shows that the new model accounts well for the location of the nano-devices as well as their trajectories.
- Ian F. Akyildiz, Massimiliano Pierobon, S. Balasubramaniam, and Y. Koucheryavy. 2015. The Internet of Bio-Nano Things. IEEE Communications Magazine (COMMAG) 53, 3 (March 2015), 32--40. https://doi.org/10.1109/MCOM.2015.7060516Google Scholar
Digital Library
- David J Brayden. 2003. Controlled release technologies for drug delivery. Drug Discovery Today 8, 21 (Nov. 2003), 976--978. https://doi.org/10.1016/s1359-6446(03)02874-5Google ScholarCross Ref
- Youssef Chahibi, Massimiliano Pierobon, Sang Ok Song, and Ian F. Akyildiz. 2013. A Molecular Communication System Model for Particulate Drug Delivery Systems. IEEE Transactions on Biomedical Engineering 60, 12 (Dec. 2013), 3468--3483. https://doi.org/10.1109/tbme.2013.2271503Google ScholarCross Ref
- Yifan Chen, Panagiotis Kosmas, Putri Santi Anwar, and Limin Huang. 2015. A Touch-Communication Framework for Drug Delivery Based on a Transient Microbot System. IEEE Transactions on NanoBioscience 14, 4 (June 2015), 397--408. https://doi.org/10.1109/tnb.2015.2395539Google ScholarCross Ref
- Falko Dressler and Stefan Fischer. 2015. Connecting In-Body Nano Communication with Body Area Networks: Challenges and Opportunities of the Internet of Nano Things. Elsevier Nano Communication Networks 6 (June 2015), 29--38. https://doi.org/10.1016/j.nancom.2015.01.006Google Scholar
- Constantine Gatsonis, James S. Hodges, Robert E. Kaas, and Nozer D. Singpur-walla. 2012. Case Studies in Bayesian Statistics. Vol. II. Springer Science & Business Media.Google Scholar
- Regine Geyer, Marc Stelzner, Florian Büther, and Sebastian Ebers. 2018. BloodVoyagerS: Simulation of the Work Environment of Medical Nanobots. In 5th ACM International Conference on Nanoscale Computing and Communication (NANOCOM 2018). ACM, Reykjavík, Iceland, 5:1-5:6. https://doi.org/10.1145/3233188.3233196Google ScholarDigital Library
- Arthur C. Guyton and Michael. E. Hall. 2015. Guyton and Hall Textbook of Medical Physiology (14 ed.). Elsevier.Google Scholar
- William Hayt, Jack Kemmerly, Jamie Phillips, and Steven Durbin. 2019. Engineering Circuit Analysis (9 ed.). McGraw-Hill Education, New York City, NY.Google Scholar
- Zhe Hu. 2001. HSP. https://de.mathworks.com/matlabcentral/fileexchange/818-hspGoogle Scholar
- Sophia L. Kalpazidou. 2006. Cycle Representations of Markov Processes. Springer. https://doi.org/10.1007/0-387-36081-6Google Scholar
- Otilia M. Koo, Israel Rubinstein, and Hayat Onyuksel. 2005. Role of nanotechnology in targeted drug delivery and imaging: a concise review. Nanomedicine: Nanotechnology Biology and Medicine 1, 3 (Sept. 2005), 193--212. https://doi.org/10.1016/j.nano.2005.06.004Google Scholar
- Anke Kuestner, Lukas Stratmann, Regine Wendt, Stefan Fischer, and Falko Dressler. 2020. A Simulation Framework for Connecting In-Body Nano Communication with Out-of-Body Devices. In 7th ACM International Conference on Nanoscale Computing and Communication (NANOCOM 2020). ACM, Virtual Conference. https://doi.org/10.1145/3411295.3411308Google ScholarDigital Library
- J. MacQueen. 1981. Circuit Processes. The Annals of Probability 9, 4 (Aug. 1981). https://doi.org/10.1214/aop/1176994365Google ScholarCross Ref
- Tadashi Nakano, Tatsuya Suda, Y. Okaie, M. J. Moore, and A. V. Vasilakos. 2014. Molecular Communication Among Biological Nanomachines: A Layered Architecture and Research Issues. IEEE Transactions on NanoBioscience 13, 3 (Sept. 2014), 169--197. https://doi.org/10.1109/TNB.2014.2316674Google ScholarCross Ref
- Paul K. Newton, Jeremy Mason, Kelly Bethel, Lyudmila A. Bazhenova, Jorge Nieva, and Peter Kuhn. 2012. A Stochastic Markov Chain Model to Describe Lung Cancer Growth and Metastasis. PLOS ONE 7, 4 (April 2012), e34637. https://doi.org/10.1371/journal.pone.0034637Google ScholarCross Ref
- Vincent C. Rideout. 1991. Mathematical and Computer Modeling of Physiological Systems. Prentice Hall, Upper Saddle River, NJ.Google Scholar
- Yubing Shi, Patricia Lawford, and Rodney Hose. 2011. Review of Zero-D and 1-D Models of Blood Flow in the Cardiovascular System. BioMedical Engineering OnLine 10, 1 (2011), 33. https://doi.org/10.1186/1475-925x-10-33Google ScholarCross Ref
- M. F. Snyder and V. C. Rideout. 1969. Computer Simulation Studies of the Venous Circulation. IEEE Transactions on Biomedical Engineering BME-16, 4 (Oct. 1969), 325--334. https://doi.org/10.1109/tbme.1969.4502663Google ScholarCross Ref
Recommendations
Nanosensor location in the human circulatory system based on electric circuit representation of vessels
NANOCOM '22: Proceedings of the 9th ACM International Conference on Nanoscale Computing and CommunicationNanotechnologies are advancing precision medicine applications, enhancing the detection and treatment of diseases. Traveling through the human vessels, nanosensors are envisioned to locally detect and actuate on targets very efficiently. In this area, ...
1D-model of the human liver circulatory system
Highlights- A novel integrated 1D model of the entire liver circulatory system is proposed.
Graphical abstract▪
Abstract Background and objectiveBlood flow rate and pressure can be measured in vivo by invasive and non-invasive techniques in the large vessels of the hepatic vasculature, but it is not possible to do so along the entire liver ...
Fine-tuned Circuit Representation of Human Vessels through Reinforcement Learning: A Novel Digital Twin Approach for Hemodynamics
NANOCOM '23: Proceedings of the 10th ACM International Conference on Nanoscale Computing and CommunicationThe modeling of human vessel hemodynamics targets various benefits in health care applications. Subject-specific models of vessels allow the accurate prediction of pressure and flow, thus, enabling the study of individuals' responses to medical ...
Comments