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:

A portable and flexible intermediary patch for in vivo magnetic localization

Nature Sensors (2026)Cite this article

Subjects

Abstract

Safe operation in visually obstructed anatomy relies on accurate in vivo localization of medical devices, yet current magnetic systems struggle to adapt across device types and clinical environments. Here we present a portable and flexible patch that functions as an intermediary in a dual-stage localization paradigm of a source–sensors–source configuration, enabling three-dimensional localization in vivo with mean positional errors under 300 µm and orientation errors under 0.3°. The patch can be customized in shape and size to accommodate diverse medical scenarios requiring precise localization. We validate its flexibility and versatility through systematic characterization, and through in vitro and in vivo studies in vascular and gastrointestinal surgery, where the system maintained continuous magnetic capsule tracking for 6 hours. Our magnetic localization patch could potentially broaden the compatibility and adaptability of magnetic localization across various medical applications.

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

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

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

Fig. 1: Overview of the flexible intermediary patch for dual-stage magnetic localization.
Fig. 2: Characterization of the flexible intermediary patch.
Fig. 3: In vitro evaluation on vascular model.
Fig. 4: In vitro evaluation on gastrointestinal model.
Fig. 5: In vivo demonstration on live pig.
Fig. 6: Wearable monitoring of gastrointestinal capsule.

Data availability

The main data supporting the results in this study are available within the paper and its Supplementary Information. Source data are provided with this paper.

Code availability

The code for data acquisition and the detailed implementation of the dual-stage magnetic localization algorithm are available at https://github.com/xpy-zju/Dual-stage-magnetic-localization.

References

  1. Sarikaya, D., Corso, J. J. & Guru, K. A. Detection and localization of robotic tools in robot-assisted surgery videos using deep neural networks for region proposal and detection. IEEE Trans. Med. Imaging 36, 1542–1549 (2017).

    Article  PubMed  Google Scholar 

  2. Li, Z., Gu, L., Wang, W., Nakamura, R. & Sato, Y. Surgical skill assessment via video semantic aggregation. In International Conference on Medical Image Computing and Computer-Assisted Intervention (eds Wang, L. et al.) 410–420 (Springer, 2022).

  3. Iddan, G., Meron, G., Glukhovsky, A. & Swain, P. Wireless capsule endoscopy. Nature 405, 417–417 (2000).

    Article  CAS  PubMed  Google Scholar 

  4. Mezger, U., Jendrewski, C. & Bartels, M. Navigation in surgery. Langenbeck Arch. Surg. 398, 501–514 (2013).

    Article  Google Scholar 

  5. De Vos, B. D. et al. ConvNet-based localization of anatomical structures in 3-D medical images. IEEE Trans. Med. Imaging 36, 1470–1481 (2017).

    Article  PubMed  Google Scholar 

  6. Martel, S., Mohammadi, M., Felfoul, O., Lu, Z. & Pouponneau, P. Flagellated magnetotactic bacteria as controlled MRI-trackable propulsion and steering systems for medical nanorobots operating in the human microvasculature. Int. J. Robot. Res. 28, 571–582 (2009).

    Article  Google Scholar 

  7. Lu, L. et al. Digital subtraction CT angiography for detection of intracranial aneurysms: comparison with three-dimensional digital subtraction angiography. Radiology 262, 605–612 (2012).

    Article  PubMed  Google Scholar 

  8. Ernst, S. et al. Initial experience with remote catheter ablation using a novel magnetic navigation system: magnetic remote catheter ablation. Circulation 109, 1472–1475 (2004).

    Article  PubMed  Google Scholar 

  9. Yang, L., Zhang, Y., Wang, Q., Chan, K.-F. & Zhang, L. Automated control of magnetic spore-based microrobot using fluorescence imaging for targeted delivery with cellular resolution. IEEE Trans. Autom. Sci. Eng. 17, 490–501 (2019).

    Article  Google Scholar 

  10. Keereweer, S. et al. Optical image-guided cancer surgery: challenges and limitations. Clin. Cancer Res. 19, 3745–3754 (2013).

    Article  PubMed  Google Scholar 

  11. Cai, M. et al. Performance-guided rotating magnetic field control in large workspaces with reconfigurable electromagnetic actuation system. IEEE Trans. Robot. 40, 4117–4131 (2024).

    Article  Google Scholar 

  12. Su, S., Yang, X., Li, Z. & Ren, H. A real-time self-sensing approach to sensor array configuration fusing prior knowledge for reconfigurable magnetic tracking systems. IEEE/ASME Trans. Mechatron. 30, 2084–2095 (2024).

    Article  Google Scholar 

  13. Wang, M., Song, S., Liu, J. & Meng, M. Q.-H. Multipoint simultaneous tracking of wireless capsule endoscope using magnetic sensor array. IEEE Trans. Instrum. Meas. 70, 1–10 (2021).

    Google Scholar 

  14. Taylor, C. R. et al. Magnetomicrometry. Sci. Robot. 6, eabg0656 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Than, T. D., Alici, G., Zhou, H., Harvey, S. & Li, W. Enhanced localization of robotic capsule endoscopes using positron emission markers and rigid-body transformation. IEEE Trans. Syst. Man Cybern. Syst. 49, 1270–1284 (2017).

    Article  Google Scholar 

  16. Popek, K. M., Hermans, T. & Abbott, J. J. First demonstration of simultaneous localization and propulsion of a magnetic capsule in a lumen using a single rotating magnet. In 2017 IEEE International Conference on Robotics and Automation (ICRA) 1154–1160 (IEEE, 2017).

  17. Gherardini, M. et al. Restoration of grasping in an upper limb amputee using the myokinetic prosthesis with implanted magnets. Sci. Robot. 9, eadp3260 (2024).

    Article  PubMed  Google Scholar 

  18. Su, S. et al. Magnetic tracking with real-time geomagnetic vector separation for robotic dockable charging. IEEE Trans. Intell. Transp. Syst. 24, 13830–13840 (2023).

    Article  Google Scholar 

  19. Zhang, M., Yang, L., Zhang, C., Yang, Z. & Zhang, L. A 5-D large-workspace magnetic localization and actuation system based on an eye-in-hand magnetic sensor array and mobile coils. IEEE Trans. Instrum. Meas. 72, 1–11 (2023).

    Google Scholar 

  20. Wang, H., Madson, R. & Rajamani, R. Electromagnetic position measurement system immune to ferromagnetic disturbances. IEEE Sens. J. 19, 9662–9671 (2019).

    Article  Google Scholar 

  21. Van Diggelen, F. A-GPS: Assisted GPS, GNSS, and SBAS (Artech House, 2009).

  22. Li, K., Xu, Y., Zhao, Z., Li, A. & Meng, M. Q.-H. Closed-loop magnetic manipulation for robotic transesophageal echocardiography. IEEE Trans. Robot. 39, 3946–3959 (2023).

    Article  Google Scholar 

  23. Sharma, S. et al. Location-aware ingestible microdevices for wireless monitoring of gastrointestinal dynamics. Nat. Electron. 6, 242–256 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Gleich, B., Schmale, I., Nielsen, T. & Rahmer, J. Miniature magneto-mechanical resonators for wireless tracking and sensing. Science 380, 966–971 (2023).

    Article  CAS  PubMed  Google Scholar 

  25. von Arx, D. et al. Simultaneous localization and actuation using electromagnetic navigation systems. IEEE Trans. Robot. 40, 1292–1308 (2023).

    Article  Google Scholar 

  26. Monge, M., Lee-Gosselin, A., Shapiro, M. G. & Emami, A. Localization of microscale devices in vivo using addressable transmitters operated as magnetic spins. Nat. Biomed. Eng. 1, 736–744 (2017).

    Article  CAS  PubMed  Google Scholar 

  27. Shao, G., Tang, Y., Tang, L., Dai, Q. & Guo, Y.-X. A novel passive magnetic localization wearable system for wireless capsule endoscopy. IEEE Sens. J. 19, 3462–3472 (2019).

    Article  Google Scholar 

  28. Son, D., Yim, S. & Sitti, M. A 5-D localization method for a magnetically manipulated untethered robot using a 2-D array of Hall-effect sensors. IEEE/ASME Trans. Mechatron. 21, 708–716 (2015).

    Article  Google Scholar 

  29. Huang, J., Mori, T., Takashima, K., Hashi, S. & Kitamura, Y. IM6D: Magnetic tracking system with 6-DOF passive markers for dexterous 3D interaction and motion. ACM Trans. Graph. 34, 1–10 (2015).

    Google Scholar 

  30. Lei, L. et al. Robotic needle insertion with 2D ultrasound–3D CT fusion guidance. IEEE Trans. Autom. Sci. Eng. 21, 6152–6164 (2023).

    Article  Google Scholar 

  31. Hu, C. et al. Locating intra-body capsule object by three-magnet sensing system. IEEE Sens. J. 16, 5167–5176 (2016).

    Article  Google Scholar 

  32. Huang, Z. et al. Enhanced localization strategy for magnetic capsule robot using on-board nine-axis IMU through incorporation of alternating magnetic field. IEEE Trans. Instrum. Meas. 73, 1–12 (2024).

    Google Scholar 

  33. Wang, H. et al. 3-D electromagnetic position estimation system using high-magnetic-permeability metal for continuum medical robots. IEEE Robot. Autom. Lett. 7, 2581–2588 (2022).

    Article  Google Scholar 

  34. Su, S. et al. A wearable, reconfigurable, and modular magnetic tracking system for wireless capsule robots. IEEE Trans.Industr. Inform. 20, 13600–13611 (2024).

    Article  Google Scholar 

  35. Sharma, S. et al. Wireless 3D surgical navigation and tracking system with 100μm accuracy using magnetic-field gradient-based localization. IEEE Trans. Med. Imaging 40, 2066–2079 (2021).

    Article  PubMed  Google Scholar 

  36. Liu, S. & Wang, H. A Wireless 6-DoF pose tracking system using a triaxially anisotropic soft magnet. IEEE/ASME Trans. Mechatron. 30, 1224–1235 (2024).

    Article  Google Scholar 

  37. Yang, W., Zhang, C., Dai, H., Hu, C. & Xia, X. A novel wireless 5-D electromagnetic tracking system based on nine-channel sinusoidal signals. IEEE/ASME Trans. Mechatron. 26, 246–254 (2020).

    Google Scholar 

  38. Bianchi, F. et al. Hybrid 6-DoF magnetic localization for robotic capsule endoscopes compatible with high-grade magnetic field navigation. IEEE Access 10, 4414–4430 (2021).

    Article  Google Scholar 

  39. Christiansen, M. G., Stöcklin, L. R., Forbrigger, C., Venkatesh, S. A. & Schuerle, S. Inductive sensing of magnetic microrobots under actuation by rotating magnetic fields. PNAS Nexus 2, pgad297 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Kim, M. K. et al. Flexible submental sensor patch with remote monitoring controls for management of oropharyngeal swallowing disorders. Sci. Adv. 5, eaay3210 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Che, Z. et al. Speaking without vocal folds using a machine-learning-assisted wearable sensing-actuation system. Nat. Commun. 15, 1873 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Zhou, S. et al. Transcranial volumetric imaging using a conformal ultrasound patch. Nature 629, 810–818 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Zweng, M. et al. Automatic guide-wire detection for neurointerventions using low-rank sparse matrix decomposition and denoising. in Proc. Augmented Environments for Computer-Assisted Interventions: 10th International Workshop, AE-CAI 2015 (eds Linte, C. A. et al.) 114–123 (Springer, 2015).

  44. Zhang, D.-Y. et al. Real-time continuous image guidance for endoscopic retrograde cholangiopancreatography based on 3D/2D registration and respiratory compensation. World J. Gastroenterol. 29, 3157 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Ausserlechner, U., Motz, M. & Holliber, M. Compensation of the piezo-Hall effect in integrated Hall sensors on (100)-Si. IEEE Sens. J. 7, 1475–1482 (2007).

    Article  Google Scholar 

  46. Motz, M., Ausserlechner, U. & Holliber, M. Compensation of mechanical stress-induced drift of bandgap references with on-chip stress sensor. IEEE Sens. J. 15, 5115–5121 (2015).

    Article  Google Scholar 

  47. Li, Y., Long, J., Chen, Y., Huang, Y. & Zhao, N. Crosstalk-free, high-resolution pressure sensor arrays enabled by high-throughput laser manufacturing. Adv. Mater. 34, 2200517 (2022).

    Article  CAS  Google Scholar 

  48. Qu, R. et al. A biomimetic fiber-entangled permeable electronic skin for strain-insensitive and high-resolution tactile sensing. Adv. Sci. 12, e12111 (2025).

    Article  CAS  Google Scholar 

  49. Caciagli, A., Baars, R. J., Philipse, A. P. & Kuipers, B. W. Exact expression for the magnetic field of a finite cylinder with arbitrary uniform magnetization. J. Magn. Magn. Mater. 456, 423–432 (2018).

    Article  CAS  Google Scholar 

  50. Beiki, M., Clark, D. A., Austin, J. R. & Foss, C. A. Estimating source location using normalized magnetic source strength calculated from magnetic gradient tensor data. Geophysics 77, J23–J37 (2012).

    Article  Google Scholar 

  51. Moré, J. J. The Levenberg-Marquardt algorithm: Implementation and theory. in Proc. Biennial Conferenceof Numerical Analysis 105–116 (Springer, 2006).

  52. Zhang, J., Yao, Y. & Deng, B. Fast and robust iterative closest point. IEEE Trans. Pattern Anal. Mach. Intell. 44, 3450–3466 (2021).

    Google Scholar 

Download references

Acknowledgements

We appreciate the valuable contribution of Z. Chen from Zhejiang University to this project. We gratefully acknowledge W. Li from Shenzhen Advanced Medical Service for the assistance provided in the animal experiments. We thank S. Fu from Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences for the maintenance of the guidewire and phantom. We are also grateful to K. Qiu from Zhejiang University for the discussion of formulas. We express our gratitude to S. Wang, Z. Chen and S. Huang from the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, as well as D. Zhuang from Fuwai Hospital, Chinese Academy of Medical Sciences, for their support in the animal experiments and analysis of experimental results. This work was supported by National Key Research and Development Project under grant 2023YFB4705300 (T.X.); National Natural Science Foundation of China under grant 62303407 (H.L.), T2293724 (H.L.), U22A2064 (T.X.); Shenzhen Science and Technology Program under grant RCJC20231211085926038 (T.X.); State Key Laboratory of Industrial Control Technology under grant ICT2024A08 (H.L.); Youth Innovation Promotion Association of CAS (T.X.); State Key Laboratory of Industrial Control Technology under grant ICT2025A08 (Y.W.); Xiaomi Foundation (H.L.).

Author information

Author notes

  1. These authors contributed equally: Pingyu Xiang, Danying Sun, Guoyao Ma.

Authors and Affiliations

  1. Department of Control Science and Engineering, Zhejiang University, Hangzhou, China

    Pingyu Xiang, Danying Sun, Hongye Zhang, Rong Xiong, Yue Wang & Haojian Lu

  2. The Guangdong Provincial Key Laboratory of Robotics and Intelligent System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Guoyao Ma & Tiantian Xu

  3. University of Chinese Academy of Sciences, Beijing, China

    Guoyao Ma

  4. Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Zhejiang Key Laboratory of Oral Biomedical, Hangzhou, China

    Haojian Lu

  5. Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, China

    Haojian Lu

  6. The Key Laboratory of Biomedical Imaging Science and System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Tiantian Xu

Authors
  1. Pingyu Xiang
    View author publications

    Search author on:PubMed Google Scholar

  2. Danying Sun
    View author publications

    Search author on:PubMed Google Scholar

  3. Guoyao Ma
    View author publications

    Search author on:PubMed Google Scholar

  4. Hongye Zhang
    View author publications

    Search author on:PubMed Google Scholar

  5. Rong Xiong
    View author publications

    Search author on:PubMed Google Scholar

  6. Yue Wang
    View author publications

    Search author on:PubMed Google Scholar

  7. Haojian Lu
    View author publications

    Search author on:PubMed Google Scholar

  8. Tiantian Xu
    View author publications

    Search author on:PubMed Google Scholar

Contributions

Conceptualization: H.L. and T.X. Methodology: P.X. and D.S. Investigation: P.X., D.S. and G.M. Visualization: P.X., G.M. and H.Z. Software: P.X., D.S. and H.Z. Funding acquisition: Y.W., H.L. and T.X. Project administration: H.L. and T.X. Supervision: H.L., T.X., R.X. and Y.W. Writing—original draft: P.X., D.S. and G.M. Writing—review and editing: H.L. and T.X.

Corresponding authors

Correspondence to Haojian Lu or Tiantian Xu.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Sensors thanks Michael Christiansen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

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

Supplementary information

Supplementary Information

Supplementary Notes 1–14, Figs. 1–31, Tables 1–6 and video legends 1–5.

Reporting Summary

Supplementary Video 1

Demonstration of flexibility.

Supplementary Video 2

Demonstration of characterization experiments.

Supplementary Video 3

Demonstration of localization in femoral artery vascular intervention.

Supplementary Video 4

Demonstration of localization in cerebral artery vascular intervention.

Supplementary Video 5

Demonstration of localization in ERCP.

Source data

Source Data Fig. 2

Source characterization data.

Source Data Fig. 3

Source localization data from in vitro vascular intervention.

Source Data Fig. 4

Source localization data from in vitro simulated ERCP.

Source Data Fig. 5

Source localization data from in vivo experiments on live pig.

Source Data Fig. 6

Source localization data from gastrointestinal capsule tracking.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xiang, P., Sun, D., Ma, G. et al. A portable and flexible intermediary patch for in vivo magnetic localization. Nat. Sens. (2026). https://doi.org/10.1038/s44460-025-00017-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • DOI: https://doi.org/10.1038/s44460-025-00017-9

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