Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Localization of microscale devices in vivo using addressable transmitters operated as magnetic spins

Nature Biomedical Engineering volume 1, pages 736–744 (2017)Cite this article

Subjects

Abstract

The function of miniature wireless medical devices, such as capsule endoscopes, biosensors and drug-delivery systems, depends critically on their location inside the body. However, existing electromagnetic, acoustic and imaging-based methods for localizing and communicating with such devices suffer from limitations arising from physical tissue properties or from the performance of the imaging modality. Here, we embody the principles of nuclear magnetic resonance in a silicon integrated-circuit approach for microscale device localization. Analogous to the behaviour of nuclear spins, the engineered miniaturized radio frequency transmitters encode their location in space by shifting their output frequency in proportion to the local magnetic field; applied field gradients thus allow each device to be located precisely from its signal’s frequency. The devices are integrated in circuits smaller than 0.7 mm3 and manufactured through a standard complementary-metal-oxide-semiconductor process, and are capable of sub-millimetre localization in vitro and in vivo. The technology is inherently robust to tissue properties, scalable to multiple devices, and suitable for the development of microscale devices to monitor and treat disease.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Sitti, M. et al. Biomedical applications of untethered mobile milli/microrobots. Proc. IEEE103, 205–224 (2015).

    Article  CAS  Google Scholar 

  2. Bergeles, C. & Yang, G. Z. From passive tool holders to microsurgeons: safer, smaller, smarter surgical robots. IEEE Trans. Biomed. Eng.61, 1565–1576 (2014).

    Article  Google Scholar 

  3. Ciuti, G., Menciassi, A. & Dario, P. Capsule endoscopy: from current achievements to open challenges. IEEE Rev. Biomed. Eng.4, 59–72 (2011).

    Article  Google Scholar 

  4. Yim, S., Gultepe, E., Gracias, D. H. & Sitti, M. Biopsy using a magnetic capsule endoscope carrying, releasing, and retrieving untethered microgrippers. IEEE Trans. Biomed. Eng.61, 513–521 (2014).

    Article  Google Scholar 

  5. Ciuti, G. et al. Frontiers of robotic endoscopic capsules: a review. J. Micro-Bio Robot.11, 1–18 (2016).

    Article  Google Scholar 

  6. Alivisatos, A. P. et al. Nanotools for neuroscience and brain activity mapping. ACS Nano7, 1850–1866 (2013).

    Article  CAS  Google Scholar 

  7. Seo, D. et al. Wireless recording in the peripheral nervous system with ultrasonic neural dust neuron neuroresource wireless recording in the peripheral nervous system with ultrasonic neural dust. Neuron91, 529–539 (2016).

    Article  CAS  Google Scholar 

  8. Williams, B. J., Anand, S. V., Rajagopalan, J. & Saif, M. T. A self-propelled biohybrid swimmer at low Reynolds number. Nat. Commun.5, 3081 (2014).

    Article  Google Scholar 

  9. Nelson, B. J., Kaliakatsos, I. K. & Abbott, J. J. Microrobots for minimally invasive medicine. Annu. Rev. Biomed. Eng.12, 55–85 (2010).

    Article  CAS  Google Scholar 

  10. Liu, L., Towfighian, S. & Hila, A. A review of locomotion systems for capsule endoscopy. IEEE Rev. Biomed. Eng.8, 138–151 (2015).

    Article  Google Scholar 

  11. Than, T. D., Alici, G., Zhou, H. & Li, W. A review of localization systems for robotic endoscopic capsules. IEEE Trans. Biomed. Eng.59, 2387–2399 (2012).

    Article  Google Scholar 

  12. Pourhomayoun, M., Jin, Z. & Fowler, M. L. Accurate localization of in-body medical implants based on spatial sparsity. IEEE Trans. Biomed. Eng.61, 590–597 (2014).

    Article  Google Scholar 

  13. Ye, Y., Pahlavan, K., Bao, G., Swar, P. & Ghaboosi, K. Comparative performance evaluation of RF localization for wireless capsule endoscopy applications. Int. J. Wirel. Inf. Networks21, 208–222 (2014).

    Article  Google Scholar 

  14. Chandra, R., Johansson, A. J., Gustafsson, M. & Tufvesson, F. A microwave imaging-based technique to localize an in-body RF source for biomedical applications. IEEE Trans. Biomed. Eng.62, 1231–1241 (2015).

    Article  Google Scholar 

  15. Bao, G., Pahlavan, K. & Mi, L. Hybrid localization of microrobotic endoscopic capsule inside small intestine by data fusion of vision and RF sensors. IEEE Sens. J.15, 2669–2678 (2015).

    Article  Google Scholar 

  16. Hu, C. et al. A cubic 3-axis magnetic sensor array for wirelessly tracking magnet position and orientation. Sensors J. IEEE10, 903–913 (2010).

    Google Scholar 

  17. Schlageter, V., Besse, P. A., Popovic, R. S. & Kucera, P. Tracking system with five degrees of freedom using a 2D-array of Hall sensors and a permanent magnet. Sensors Actuat. A Phys.92, 37–42 (2001).

    Article  CAS  Google Scholar 

  18. Schlageter, V., Drljaca, P., Popovic, R. S. & Kucera, P. A magnetic tracking system based on highly sensitive integrated Hall sensors. JSME Int. J. Ser. C45, 967–973 (2002).

    Article  Google Scholar 

  19. Wu, X. et al. Wearable magnetic locating and tracking system for MEMS medical capsule. Sensors Actuat. A Phys.141, 432–439 (2008).

    Article  CAS  Google Scholar 

  20. Nagaoka, T. & Uchiyama, A. Development of a small wireless position sensor for medical capsule devices. Conf. Proc. IEEE Eng. Med. Biol. Soc.3, 2137–2140 (2004).

    CAS  PubMed  Google Scholar 

  21. Guo, X., Yan, G. & He, W. A novel method of three-dimensional localization based on a neural network algorithm. J. Med. Eng. Technol.33, 192–198 (2009).

    Article  CAS  Google Scholar 

  22. Hashi, S., Yabukami, S., Kanetaka, H., Ishiyama, K. & Arai, K. I. Numerical study on the improvement of detection accuracy for a wireless motion capture system. IEEE Trans. Magnet.45, 2736–2739 (2009).

    Article  CAS  Google Scholar 

  23. Hashi, S., Yabukami, S., Kanetaka, H., Ishiyama, K. & Arai, K. I. Wireless magnetic position-sensing system using optimized pickup coils for higher accuracy. IEEE Trans. Magnet.47, 3542–3545 (2011).

    Article  Google Scholar 

  24. Carpi, F., Kastelein, N., Talcott, M. & Pappone, C. Magnetically controllable gastrointestinal steering of video capsules. IEEE Trans. Biomed. Eng.58, 231–234 (2011).

    Article  Google Scholar 

  25. Kuth, R., Reinschke, J. & Rockelein, R. Method for determining the position and orientation of an endoscopy capsule guided through an examination object by using a navigating magnetic field generated by means of a navigation device. German patent US20070038063 (2007).

  26. Boese, J., Rahn, N. & Sandkamp, B. Method for determining the position and orientation of an object, especially of a catheter, from two-dimensional X-ray images. German patent US7801342 (2010).

  27. Than, T. D. et al. An effective localization method for robotic endoscopic capsules using multiple positron emission markers. IEEE Trans. Robot.30, 1174–1186 (2014).

    Article  Google Scholar 

  28. Dumoulin, C. L., Souza, S. P. & Darrow, R. D. Real-time position monitoring of invasive devices using magnetic resonance. Magn. Reson. Med.29, 411–415 (1993).

    Article  CAS  Google Scholar 

  29. Krieger, A. et al. An MRI-compatible robotic system with hybrid tracking for MRI-guided prostate intervention. IEEE Trans. Biomed. Eng.58, 3049–3060 (2011).

    Article  Google Scholar 

  30. Zabow, G., Dodd, S., Moreland, J. & Koretsky, A. Micro-engineered local field control for high-sensitivity multispectral MRI. Nature453, 1058–1063 (2008).

    Article  CAS  Google Scholar 

  31. Nagy, Z. et al. in Proc. IEEE International Conference on Robotics and Automation 2593–2598 (2009).

  32. Gumprecht, J. D. J., Lueth, T. C. & Khamesee, M. B. Navigation of a robotic capsule endoscope with a novel ultrasound tracking system. Microsyst. Technol.19, 1415–1423 (2013).

    Article  Google Scholar 

  33. Wells, P. Current status and future technical advances of ultrasonic imaging. Eng. Med. Biol. Mag. IEEE19, 14–20 (2000).

    Article  CAS  Google Scholar 

  34. Carpi, F. & Shaheed, H. Grand challenges in magnetic capsule endoscopy. Expert Rev. Med. Devices10, 433–436 (2013).

    Article  CAS  Google Scholar 

  35. Popovic, R. S. Hall Effect Devices 2nd edn (CRC Press, Boca Raton, FL, 2003).

  36. Saritas, E. U. et al. Magnetic particle imaging (MPI) for NMR and MRI researchers. J. Magn. Reson.229, 116–126 (2013).

    Article  CAS  Google Scholar 

  37. Agrawal, D. R. et al. Conformal phased surfaces for wireless powering of bioelectronic microdevices. Nat. Biomed. Eng.1, 0043 (2017).

    Article  Google Scholar 

  38. Agarwal, A. et al. A 4 µW, ADPLL-based implantable amperometric biosensor in 65 µm CMOS. In 2017 Symposia on VLSI Circuits (2017).

  39. Nazari, M. H., Mujeeb-U-Rahman, M. & Scherer, A. An implantable continuous glucose monitoring microsystem in 0.18 µm CMOS. In 2014 Symposium on VLSI Circuits Digest of Technical Papers 1–2 (2014).

  40. Ning, H. et al. Holographic patterning of high-performance on-chip 3D lithium-ion microbatteries. Proc. Natl Acad. Sci. USA112, 6573–6578 (2015).

    Article  CAS  Google Scholar 

  41. Liu, T. et al. High-density lithium-ion energy storage utilizing the surface redox reactions in folded graphene films. Chem. Mater.27, 3291–3298 (2015).

    Article  CAS  Google Scholar 

  42. Lai, W. et al. Ultrahigh-energy-density microbatteries enabled by new electrode architecture and micropackaging design. Adv. Mater.22, e139–e144 (2010).

    Article  CAS  Google Scholar 

  43. Biederman, W. et al. A 4.78 mm2 fully-integrated neuromodulation SoC combining 64 acquisition channels with digital compression and simultaneous dual stimulation. IEEE J. Solid-State Circ.50, 1038–1047 (2015).

    Article  Google Scholar 

  44. Monge, M. et al. A fully intraocular high-density self-calibrating epiretinal prosthesis. IEEE Trans. Biomed. Circuits Syst.7, 747–760 (2013).

    Article  Google Scholar 

  45. Ritchie, C. J. et al. Minimum scan speeds for suppression of motion artifacts in CT. Radiology185, 37–42 (1992).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The authors thank A. Agarwal for insightful discussions and assistance with the chip design, and A. Shapero for assistance with chip encapsulation. We thank K.-C. Chen, M. Raj, B. Abiri, A. Safaripur, F. Bohn, H. Davis, P. Ramesh and G. Lu for helpful and constructive discussions. We appreciate the help and assistance of the Caltech High-speed Integrated Circuits group. This research was supported by the Heritage Medical Research Institute (M.G.S. and A.E.), the Burroughs Wellcome Fund (M.G.S.) and the Caltech Rosen Bioengineering Center graduate scholarship (M.M.).

Author information

Authors and Affiliations

  1. Division of Engineering and Applied Sciences, California Institute of Technology, Pasadena, CA, 91125, USA

    Manuel Monge & Azita Emami

  2. Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, 91125, USA

    Audrey Lee-Gosselin & Mikhail G. Shapiro

Authors
  1. Manuel Monge
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Audrey Lee-Gosselin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mikhail G. Shapiro
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Azita Emami
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

M.M., M.G.S. and A.E. conceived and planned the research. M.M. designed the integrated circuit and all printed circuit boards, and developed the code to program the FPGA. M.M. performed characterization and in vitro experiments. M.M. and A.L.-G. performed in vivo experiments. M.M. analysed data. M.M., M.G.S. and A.E. wrote the manuscript with input from all other authors. M.G.S. and A.E. supervised the research.

Corresponding authors

Correspondence to Mikhail G. Shapiro or Azita Emami.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Supplementary Information

Supplementary discussion, figures and references.

Life sciences reporting summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Monge, M., Lee-Gosselin, A., Shapiro, M.G. et al. Localization of microscale devices in vivo using addressable transmitters operated as magnetic spins. Nat Biomed Eng 1, 736–744 (2017). https://doi.org/10.1038/s41551-017-0129-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41551-017-0129-2

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing