Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
162 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Magnetic Localization for In-body Nano-communication Medical Systems (2403.02497v1)

Published 4 Mar 2024 in cs.IR and cs.NI

Abstract: Nano-machines circulating inside the human body, collecting data on tissue conditions, represent a vital part of next-generation medical diagnostic systems. However, for these devices to operate effectively, they need to relay not only their medical measurements but also their positions. This paper introduces a novel localization method for in-body nano-machines based on the magnetic field, leveraging the advantageous magnetic permeability of all human tissues. The entire proposed localization system is described, starting from 10x10 ${\mu}m2$ magnetometers to be integrated into the nano-machines, to a set of external wires generating the magnetic field. Mathematical equations for the localization algorithm are also provided, assuming the nano-machines do not execute the computations themselves, but transmit their magnetic field measurements together with medical data outside of the body. The whole system is validated with computer simulations that capture the measurement error of the magnetometers, the error induced by the Earth magnetic field, and a human body model assuming different possible positions of nano-machines. The results show a very high system accuracy with localization errors even below 1 cm.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (44)
  1. I. F. Akyildiz and J. M. Jornet, “The internet of nano-things,” IEEE Wireless Communications, vol. 17, no. 6, pp. 58–63, 2010.
  2. I. F. Akyildiz, M. Pierobon, S. Balasubramaniam, and Y. Koucheryavy, “The internet of bio-nano things,” IEEE Communications Magazine, vol. 53, no. 3, pp. 32–40, 2015.
  3. A. Sangwan and J. M. Jornet, “Joint communication and bio-sensing with plasmonic nano-systems to prevent the spread of infectious diseases in the internet of nano-bio things,” IEEE Journal on Selected Areas in Communications, vol. 40, no. 11, pp. 3271–3284, 2022.
  4. K. Aghababaiyan, H. Kebriaei, V. Shah-Mansouri, B. Maham, and D. Niyato, “Enhanced modulation for multiuser molecular communication in internet of nano things,” IEEE Internet of Things Journal, vol. 9, no. 20, pp. 19 787–19 802, 2022.
  5. M. Ali, Y. Chen, and M. J. Cree, “Semi-autonomous in vivo computation in internet of bio-nano things,” IEEE Internet of Things Journal, pp. 1–1, 2023.
  6. P. Kulakowski, K. Turbic, and L. M. Correia, “From nano-communications to body area networks: A perspective on truly personal communications,” IEEE Access, vol. 8, pp. 159 839–159 853, 2020.
  7. I. F. Akyildiz and J. M. Jornet, “Electromagnetic wireless nanosensor networks,” Nano Communication Networks, vol. 1, no. 1, pp. 3–19, 2010.
  8. M. Tamagnone, J. S. Gómez-Díaz, J. R. Mosig, and J. Perruisseau-Carrier, “Reconfigurable terahertz plasmonic antenna concept using a graphene stack,” Applied Physics Letters, vol. 101, no. 21, 11 2012.
  9. J. M. Jornet and I. F. Akyildiz, “Graphene-based plasmonic nano-antenna for terahertz band communication in nanonetworks,” IEEE Journal on Selected Areas in Communications, vol. 31, no. 12, pp. 685–694, 2013.
  10. M. S. Ukhtary and R. Saito, “Surface plasmons in graphene and carbon nanotubes,” Carbon, vol. 167, pp. 455–474, 2020.
  11. I. F. Akyildiz, F. Brunetti, and C. Blázquez, “Nanonetworks: A new communication paradigm,” Computer Networks, vol. 52, no. 12, pp. 2260–2279, 2008.
  12. N. Farsad, H. B. Yilmaz, A. Eckford, C.-B. Chae, and W. Guo, “A comprehensive survey of recent advancements in molecular communication,” IEEE Communications Surveys & Tutorials, vol. 18, no. 3, pp. 1887–1919, 2016.
  13. U. A. K. Chude-Okonkwo, R. Malekian, B. T. Maharaj, and A. V. Vasilakos, “Molecular communication and nanonetwork for targeted drug delivery: A survey,” IEEE Communications Surveys & Tutorials, vol. 19, no. 4, pp. 3046–3096, 2017.
  14. M. Kuscu, A. Kiraz, and O. B. Akan, “Fluorescent molecules as transceiver nanoantennas: The first practical and high-rate information transfer over a nanoscale communication channel based on fret,” Scientific reports, vol. 5, no. 1, p. 7831, 2015.
  15. K. Solarczyk, K. Wojcik, and P. Kulakowski, “Nanocommunication via fret with dylight dyes using multiple donors and acceptors,” IEEE Transactions on NanoBioscience, vol. 15, no. 3, pp. 275–283, 2016.
  16. P. Kulakowski, K. Solarczyk, and K. Wojcik, “Routing in fret-based nanonetworks,” IEEE Communications Magazine, vol. 55, no. 9, pp. 218–224, 2017.
  17. T. Hogg and R. A. Freitas Jr, “Acoustic communication for medical nanorobots,” Nano Communication Networks, vol. 3, no. 2, pp. 83–102, 2012.
  18. G. E. Santagati and T. Melodia, “Opto-ultrasonic communications for wireless intra-body nanonetworks,” Nano Communication Networks, vol. 5, no. 1-2, pp. 3–14, 2014.
  19. S. Canovas-Carrasco, A.-J. Garcia-Sanchez, and J. Garcia-Haro, “A nanoscale communication network scheme and energy model for a human hand scenario,” Nano Communication Networks, vol. 15, pp. 17–27, Mar. 2018.
  20. J. Simonjan, B. D. Unluturk, and I. F. Akyildiz, “In-body bionanosensor localization for anomaly detection via inertial positioning and thz backscattering communication,” IEEE Transactions on NanoBioscience, vol. 21, no. 2, pp. 216–225, 2022.
  21. F. Lemic, S. Abadal, and J. Famaey, “Toward localization in terahertz-operating energy harvesting software-defined metamaterials: Context analysis,” in Proceedings of the 7th ACM International Conference on Nanoscale Computing and Communication, ser. NanoCom ’20, 2020.
  22. F. Lemic, S. Abadal, A. Stevanovic, E. Alarcón, and J. Famaey, “Toward location-aware in-body terahertz nanonetworks with energy harvesting,” in Proceedings of the 9th ACM International Conference on Nanoscale Computing and Communication, ser. NANOCOM ’22, 2022.
  23. H. Tran-Dang, N. Krommenacker, and P. Charpentier, “Localization algorithms based on hop counting for wireless nano-sensor networks,” in 2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2014, pp. 300–306.
  24. L. Zhou, G. Han, and L. Liu, “Pulse-based distance accumulation localization algorithm for wireless nanosensor networks,” IEEE Access, vol. 5, pp. 14 380–14 390, 2017.
  25. C. M. Collins, B. Yang, Q. X. Yang, and M. B. Smith, “Numerical calculations of the static magnetic field in three-dimensional multi-tissue models of the human head,” Magnetic Resonance Imaging, vol. 20, no. 5, pp. 413–424, 2002.
  26. A. Emami and M. Monge, “Mri-inspired high-resolution localization for biomedical applications: Artificial nuclear spins on a chip,” IEEE Solid-State Circuits Magazine, vol. 10, no. 4, pp. 34–42, 2018.
  27. T. young Choi, W. F. Loke, T. Maleki, B. Ziaie, L. Papiez, and B. Jung, “Wireless magnetic tracking system for radiation therapy,” in 2009 IEEE/NIH Life Science Systems and Applications Workshop, 2009, pp. 148–151.
  28. W.-F. Loke, T.-Y. Choi, T. Maleki, L. Papiez, B. Ziaie, and B. Jung, “Magnetic tracking system for radiation therapy,” IEEE Transactions on Biomedical Circuits and Systems, vol. 4, no. 4, pp. 223–231, 2010.
  29. W.-F. Loke, W.-H. Chen, T. Maleki, M. Abu Khater, B. Ziaie, L. Papiez, and B. Jung, “A 0.5-v sub-mw wireless magnetic tracking transponder for radiation therapy,” in 2011 Symposium on VLSI Circuits - Digest of Technical Papers, 2011, pp. 172–173.
  30. V. Cavlu and P. Brennan, “Determining the position and orientation of in-body medical instruments using near-field magnetic field mapping,” IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology, vol. 4, no. 1, pp. 10–16, 2020.
  31. T. Wen and H. Wang, “Identification of workspace of the soft-magnet based position tracking system for medical robots using parallel experiments,” IEEE Journal of Radio Frequency Identification, vol. 6, pp. 987–992, 2022.
  32. M. Suveren and M. Kanaan, “5d magnetic localization for wireless capsule endoscopy using the levenberg-marquardt method and artificial bee colony algorithm,” in 2019 IEEE 30th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC Workshops), 2019, pp. 1–6.
  33. V. Pasku, A. De Angelis, G. De Angelis, D. D. Arumugam, M. Dionigi, P. Carbone, A. Moschitta, and D. S. Ricketts, “Magnetic field-based positioning systems,” IEEE Communications Surveys & Tutorials, vol. 19, no. 3, pp. 2003–2017, 2017.
  34. J. Sa, J. Park, E. Jung, N. Kim, D. Lee, S. Bae, Y. Lee, and G. Jang, “Separable and recombinable magnetic robot for robotic endovascular intervention,” IEEE Robotics and Automation Letters, vol. 8, no. 4, pp. 1881–1888, 2023.
  35. J. L. Marzo, J. M. Jornet, and M. Pierobon, “Nanonetworks in biomedical applications,” Current drug targets, vol. 20, no. 8, pp. 800–807, 2019.
  36. J. M. Jornet and A. Sangwan, “Nanonetworking in the terahertz band and beyond,” IEEE Nanotechnology Magazine, 2023.
  37. D. Izci, C. Dale, N. Keegan, and J. Hedley, “The construction of a graphene hall effect magnetometer,” IEEE Sensors Journal, vol. 18, no. 23, pp. 9534–9541, 2018.
  38. R. Asorey-Cacheda, S. Canovas-Carrasco, A.-J. Garcia-Sanchez, and J. Garcia-Haro, “An analytical approach to flow-guided nanocommunication networks,” Sensors, vol. 20, no. 5, 2020.
  39. R. Asorey-Cacheda, L. M. Correia, C. Garcia-Pardo, K. Wojcik, K. Turbic, and P. Kulakowski, “Bridging nano and body area networks: A full architecture for cardiovascular health applications,” IEEE Internet of Things Journal, vol. 10, no. 5, pp. 4307–4323, 2023.
  40. S. Canovas-Carrasco, R. Asorey-Cacheda, A.-J. Garcia-Sanchez, J. Garcia-Haro, K. Wojcik, and P. Kulakowski, “Understanding the applicability of terahertz flow-guided nano-networks for medical applications,” IEEE Access, vol. 8, pp. 214 224–214 239, 2020.
  41. A.-J. Garcia-Sanchez, R. Asorey-Cacheda, J. Garcia-Haro, and J.-L. Gomez-Tornero, “Dynamic multihop routing in terahertz flow-guided nanosensor networks: A reinforcement learning approach,” IEEE Sensors Journal, vol. 23, no. 4, pp. 3408–3422, 2023.
  42. K. Langendoen and N. Reijers, “Distributed localization in wireless sensor networks: a quantitative comparison,” Computer Networks, vol. 43, no. 4, pp. 499–518, 2003.
  43. A. Chulliat, W. Brown, P. Alken, C. Beggan, M. Nair, G. Cox, A. Woods, S. Macmillan, B. Meyer, and M. Paniccia, “The us/uk world magnetic model for 2020-2025 : Technical report,” 2020, technical Report. [Online]. Available: https://repository.library.noaa.gov/view/noaa/24390
  44. P. Blümler, “Magnetic guiding with permanent magnets: Concept, realization and applications to nanoparticles and cells,” Cells, vol. 10, no. 10, 2021.

Summary

  • The paper introduces a magnetic field-based system that localizes nano-machines with errors below 1 cm as demonstrated in simulations.
  • The paper develops and validates an algorithm using 10x10 μm² magnetometers and external magnetic fields to determine in-body positions.
  • The paper highlights potential applications in precision diagnostics and targeted drug delivery by leveraging near-uniform magnetic permeability in human tissues.

An Expert Overview of "Magnetic Localization for In-body Nano-communication Medical Systems"

In the field of advanced medical diagnostics, the paper "Magnetic Localization for In-body Nano-communication Medical Systems" by Skos et al. presents a sophisticated localization solution leveraging magnetic fields for in-body nano-machines. These nano-machines, acting as diagnostic agents, necessitate precise localization to effectively correlate medical measurements with spatial positions inside the human body, an endeavor that bears significant implications for the future of medical diagnostics.

The paper introduces a novel magnetic field-based localization system, highlighting the advantageous magnetic permeability near unity across various human tissues. This novel approach allows the magnetic field to serve as an effective medium for distance and position determination within the body. The proposed system outline initiates with the integration of 10x10 μm2 magnetometers in nano-machines. The localization involves external wires generating a magnetic field, the measurements of which enable the determination of the positions of the nano-machines.

Central to the paper is the establishment and validation of a localization algorithm, which, through computer simulations, demonstrates notable accuracy with localization errors reported to be below 1 cm. The simulations account for potential errors due to magnetometer precision and the Earth's magnetic field interference, modeled using the World Magnetic Model. This high level of accuracy bodes well for detailed diagnostic processes that necessitate pinpoint spatial resolution.

The paper distinguishes itself from previously existing localization methodologies, particularly relevant in the domain of nano-networks, where classical approaches such as RSSI are rendered ineffectual due to severe attenuation of electromagnetic signals in body tissues. By exploiting the near-uniform permeability of human tissues to magnetic fields, the authors propose a system that circumvents these traditional pitfalls.

From a practical standpoint, the implications are manifold. Reliable in-body localization opens adroit avenues for targeted drug delivery, precision diagnostics, and minimally invasive procedures. The system's independence from in-body computational resources further heightens its applicability, easing the energy and processing burdens typically faced by in-body devices.

Theoretically, the paper sets a precedent in employing static magnetic fields for precise in-vivo positioning, encouraging further exploration of magnetic phenomena for various medical applications. It raises compelling questions about the integration of in-body magnetism-based solutions, bridging gaps between nanotechnology and biomedicine.

Future research, as suggested, may explore substituting external magnetic sources with in-body magnets to enhance autonomy and precision. Additionally, examining dynamic characteristics of magnetic fields may refine measurements further, offering enhanced temporal resolution crucial for applications in real-time diagnostics.

In conclusion, this paper lays a robust, technical foundation for continuing advancements in the integration of magnetic localization in the ever-evolving field of in-body medical nano-systems, pushing the boundaries of traditional medical methodologies towards more future-centric, precise, and minimally invasive diagnostic processes.

File Document Download Save Streamline Icon: https://streamlinehq.com PDF File Document Download Save Streamline Icon: https://streamlinehq.com Markdown
Youtube Logo Streamline Icon: https://streamlinehq.com

YouTube