Skip to main content

Thank you for visiting 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.

Location-aware ingestible microdevices for wireless monitoring of gastrointestinal dynamics


Localization and tracking of ingestible microdevices in the gastrointestinal (GI) tract is valuable for the diagnosis and treatment of GI disorders. Such systems require a large field-of-view of tracking, high spatiotemporal resolution, wirelessly operated microdevices and a non-obstructive field generator that is safe to use in practical settings. However, the capabilities of current systems remain limited. Here, we report three dimensional (3D) localization and tracking of wireless ingestible microdevices in the GI tract of large animals in real time and with millimetre-scale resolution. This is achieved by generating 3D magnetic field gradients in the GI field-of-view using high-efficiency planar electromagnetic coils that encode each spatial point with a distinct magnetic field magnitude. The field magnitude is measured and transmitted by the miniaturized, low-power and wireless microdevices to decode their location as they travel through the GI tract. This system could be useful for quantitative assessment of the GI transit-time, precision targeting of therapeutic interventions and minimally invasive procedures.

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

Access options

Rent or buy this article

Get just this article for as long as you need it


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

Fig. 1: System overview.
Fig. 2: iMAG device architecture and characterization.
Fig. 3: Magnetic-field-gradient generation and characterization.
Fig. 4: In vivo localization of iMAG in the GI tract under acute and chronic conditions.
Fig. 5: Application of iMAG in FI and magnetic label tracking.

Data availability

The data that support the findings of this study are available from the corresponding authors upon reasonable request.

Code availability

Codes used in this study are available from the corresponding authors upon request.


  1. Steiger, C. et al. Ingestible electronics for diagnostics and therapy. Nat. Rev. Mater. 4, 83–98 (2019).

    Article  Google Scholar 

  2. Keller, J. et al. Advances in the diagnosis and classification of gastric and intestinal motility disorders. Nat. Rev. Gastroenterol. Hepatol. 15, 291–308 (2018).

    Article  Google Scholar 

  3. Rao, S. S. C. et al. Evaluation of gastrointestinal transit in clinical practice: position paper of the American and European Neurogastroenterology and Motility Societies. Neurogastroenterol. Motil. 23, 8–23 (2011).

    Article  Google Scholar 

  4. Mimee, M. et al. An ingestible bacterial-electronic system to monitor gastrointestinal health. Science 360, 915–918 (2018).

    Article  Google Scholar 

  5. Kuo, B. et al. Comparison of gastric emptying of a nondigestible capsule to a radio-labelled meal in healthy and gastroparetic subjects. Aliment. Pharmacol. Ther. 27, 186–196 (2008).

    Article  Google Scholar 

  6. Wang, A. et al. Wireless capsule endoscopy. Gastrointest. Endosc. 78, 805–815 (2013).

    Article  Google Scholar 

  7. Hejazi, R. A. et al. Video capsule endoscopy: a tool for the assessment of small bowel transit time. Front. Med. 3, 6 (2016).

  8. Maqbool, S. et al. Wireless capsule motility: comparison of the SmartPill GI monitoring system with scintigraphy for measuring whole gut transit. Digestive Dis. Sci. 54, 2167–2174 (2009).

    Article  Google Scholar 

  9. Dagdeviren, C. et al. Flexible piezoelectric devices for gastrointestinal motility sensing. Nat. Biomed. Eng. 1, 807–817 (2017).

    Article  Google Scholar 

  10. Haase, A. M. et al. Gastrointestinal motility during sleep assessed by tracking of telemetric capsules combined with polysomnography—a pilot study. Clin. Exp. Gastroenterol. 8, 327–332 (2015).

    Article  Google Scholar 

  11. Gharibans, A. A. et al. Artifact rejection methodology enables continuous, noninvasive measurement of gastric myoelectric activity in ambulatory subjects. Sci. Rep. 8, 5019 (2018).

  12. Chen, H. et al. Advances in functional X-ray imaging techniques and contrast agents. Phys. Chem. Chem. Phys. 14, 13469–13486 (2012).

    Article  Google Scholar 

  13. Monge, M. et al. Localization of microscale devices in vivo using addressable transmitters operated as magnetic spins. Nat. Biomed. Eng. 1, 736–744 (2017).

    Article  Google Scholar 

  14. Worsøe, J. et al. Gastric transit and small intestinal transit time and motility assessed by a magnet tracking system. BMC Gastroenterol. 11, 145 (2011).

  15. Andrä, W. et al. A novel method for real-time magnetic marker monitoring in the gastrointestinal tract. Phys. Med. Biol. 45, 3081–3093 (2000).

    Article  Google Scholar 

  16. Son, D. et al. 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 (2016).

    Article  Google Scholar 

  17. Pourhomayoun, M. et al. Accurate localization of in-body medical implants based on spatial sparsity. IEEE Trans. Biomed. Eng. 61, 590–597 (2014).

    Article  Google Scholar 

  18. Weitschies, W. et al. Magnetic marker monitoring: high resolution real-time tracking of oral solid dosage forms in the gastrointestinal tract. Eur. J. Pharm. Biopharm. 74, 93–101 (2010).

    Article  Google Scholar 

  19. Franz, A. M. et al. Electromagnetic tracking in medicine—a review of technology, validation, and applications. IEEE Trans. Med. Imaging 33, 1702–1725 (2014).

    Article  Google Scholar 

  20. Brink, C. E. et al. Magnetic tracking of gastrointestinal motility. Physiol. Meas. 41, 12TR01 (2020).

    Article  Google Scholar 

  21. Baker-Jarvis, J. & Kim, Sung The interaction of radio-frequency fields with dielectric materials at macroscopic to mesoscopic scales. J. Res. Natl Inst. Stand. Technol. 117, 1–60 (2012).

    Article  Google Scholar 

  22. Schiller, C. et al. Intestinal fluid volumes and transit of dosage forms as assessed by magnetic resonance imaging. Aliment. Pharmacol. Ther. 22, 971–979 (2005).

    Article  Google Scholar 

  23. Mudie, D. M. et al. Physiological parameters for oral delivery and in vitro testing. Mol. Pharmaceutics 7, 1388–1405 (2010).

    Article  Google Scholar 

  24. Dove, I. Analysis of radio propagation inside the human body for in-body localization purposes. Thesis, University of Twente (2014).

  25. 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  Google Scholar 

  26. Ham, C. L. G. et al. Peripheral nerve stimulation during MRI: effects of high gradient amplitudes and switching rates. J. Magn. Reson. Imaging 7, 933–937 (1997).

    Article  Google Scholar 

  27. Schaefer, D. J. et al. Review of patient safety in time-varying gradient fields. J. Magn. Reson. Imaging 20, 20–29 (2000).

    Article  Google Scholar 

  28. Klein, V. et al. Investigating cardiac stimulation limits of MRI gradient coils using electromagnetic and electrophysiological simulations in human and canine body models. Magn. Reson. Med. 85, 1047–1061 (2021).

    Article  Google Scholar 

  29. Sharma, S. et al. 20.4 3D surgical alignment with 100µm resolution using magnetic-field gradient-based localization. In Proc. 2020 IEEE International Solid-State Circuits Conference—(ISSCC) 318–320 (IEEE, 2020).

  30. Mostafaei, F. et al. Variations of MRI-assessed peristaltic motions during radiation therapy. PLoS ONE 13, e0205917 (2018).

    Article  Google Scholar 

  31. Swindle, M. M. et al. Swine as models in biomedical research and toxicology testing. Vet. Pathol. 49, 344–356 (2012).

    Article  Google Scholar 

  32. Ruiz, N. S. et al. Fecal incontinence—challenges and solutions. World J. Gastroenterol. 23, 11–24 (2017).

    Article  Google Scholar 

  33. Lo, Y. K. et al. A wireless implant for gastrointestinal motility disorders. Micromachines 9, 17 (2018).

  34. Kong, Y. L. et al. 3D-printed gastric resident electronics. Adv. Mater. Technol. 4, 1800490 (2019).

    Article  Google Scholar 

  35. Ramadi, K.B., Srinivasan, S.S. & Traverso, G. Electroceuticals in the gastrointestinal tract. Trends Pharmacol. Sci. 41, 960–976 (2020).

    Article  Google Scholar 

  36. Traverso, G. et al. Physiologic status monitoring via the gastrointestinal tract. PLoS ONE 10, e0141666 (2015).

    Article  Google Scholar 

  37. Menciassi, A. et al. Clamping tools of a capsule for monitoring the gastrointestinal tract problem analysis and preliminary technological activity. In Proc. 2005 IEEE International Conference on Robotics and Automation 1309–1314 (IEEE, 2005).

  38. Than, T. D. et al. A review of localization systems for robotic endoscopic capsules. IEEE Trans. Biomed. Eng. 59, 2387–2399 (2012).

    Article  Google Scholar 

  39. Su, S. et al. Investigation of the relationship between tracking accuracy and tracking distance of a novel magnetic tracking system. IEEE Sens. J. 17, 4928–4937 (2017).

    Article  Google Scholar 

  40. Bianchi, F. et al. Localization strategies for robotic endoscopic capsules: a review. Expert Rev. Med. Devices 16, 381–403 (2019).

    Article  Google Scholar 

  41. Pham, D. M. et al. A real-time localization system for an endoscopic capsule using magnetic sensors. Sensors 14, 20910–20929 (2014).

    Article  Google Scholar 

  42. Bass, D. M. et al. Gastrointestinal safety of an extended-release, nondeformable, oral dosage form (OROS®)1. Drug-Saf. 25, 1021–1033 (2002).

    Article  Google Scholar 

  43. Huang, J. et al. IM6D: magnetic tracking system with 6-DOF passive markers for dexterous 3D interaction and motion. ACM Trans. Graph. 34, 217 (2015).

    Article  Google Scholar 

  44. Vasisht, D. et al. In-body backscatter communication and localization. In Proc. 2018 Conference of the ACM Special Interest Group on Data Communication 132–146 (ACM, 2018).

  45. Nadeau, P. et al. Prolonged energy harvesting for ingestible devices. Nat. Biomed. Eng. 1, 0022 (2017).

  46. Talkhooncheh, A. H. et al. A fully-integrated biofuel-cell-based energy harvester with 86% peak efficiency and 0.25V minimum input voltage using source-adaptive MPPT. In 2020 IEEE Custom Integrated Circuits Conference (CICC) 1–4 (IEEE, 2020).

  47. Talkhooncheh, A. H. et al. A biofuel-cell-based energy harvester with 86% peak efficiency and 0.25-V minimum input voltage using source-adaptive MPPT. IEEE J. Solid-State Circuits 56, 715–728 (2021).

    Article  Google Scholar 

  48. Turner, R. Gradient coil design: a review of methods. Magn. Reson. Imaging 11, 903–920 (1993).

    Article  Google Scholar 

  49. Hidalgo-Tobon, S. S. Theory of gradient coil design methods for magnetic resonance imaging. Concepts Magn. Reson. 36A, 223–242 (2010).

    Article  Google Scholar 

  50. Sharma, S. et al. Electromagnet gradient coil apparatus for micro-device localization. US patent 11,457,835 B2 (2021).

  51. Sharma, S. et al. In-vivo monitoring of an internal volume of a mammal using magnetic field gradients. US patent 20,210,137,412 (2021).

  52. Sharma, S. et al. Surgical alignment by magnetic field gradient localization. US patent 11,399,848 B2 (2019).

  53. Khadra, I. et al. Statistical investigation of simulated intestinal fluid composition on the equilibrium solubility of biopharmaceutics classification system class II drugs. Eur. J. Pharm. Sci. 25, 65–75 (2015).

    Article  Google Scholar 

  54. Vertzoni, M. et al. Dissolution media simulating the intralumenal composition of the small intestine: physiological issues and practical aspects. J. Pharm. Pharmacol. 56, 453–462 (2004).

    Article  Google Scholar 

  55. Nevo, E. et al. Method and apparatus to estimate location and orientation of objects during magnetic resonance imaging. US patent 6,516,213 B1 (2003).

Download references


We acknowledge the contribution of Standard Technology Inc. (FL) in the assembly of gradient coils. We are grateful to the members of MICS Lab (Caltech) for insightful comments and discussions. This research was funded in part by the National Science Foundation under grant 1823036 (A.E. and M.G.S.); in part by the Rothenberg Innovation Initiative under grant 101170 (A.E. and M.G.S.); in part by the Heritage Medical Research Institute under grant 150901 (A.E. and M.G.S.); and in part by a grant from the Karl van Tassel (1925) Career Development Professorship, the Department of Mechanical Engineering at MIT (G.T.). K.B.R. was supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) of the National Institutes of Health (NIH) under award no. F32DK122762 and the Division of Engineering at New York University, Abu Dhabi.

Author information

Authors and Affiliations



S.S., K.B.R., N.H.P., S.S.S., M.G.S., G.T. and A.E. conceived and designed the research. S.S. designed and assembled the iMAG devices, EM coils for gradient generation and all the electronics. S.S. performed all the in vitro characterization and localization experiments. K.B.R., S.S. and S.S.S. performed the in vivo characterization and localization experiments. N.H.P. and S.S. programmed the nRF chipset on iMAG and the receiver. S.S. performed all the data processing. K.I., J.K. and J.J. helped during the in vivo experiments. F.A. helped with the iMAG PCB design. M.B.S. helped during the in vitro characterization. S.S. wrote the manuscript, with input from all the other authors. M.G.S., G.T. and A.E. supervised the research.

Corresponding authors

Correspondence to Saransh Sharma, Giovanni Traverso or Azita Emami.

Ethics declarations

Competing interests

S.S., M.G.S. and A.E. have joint US patents (20,210,137,412 and 11,457,835 B2) on the localization and magnetic-field generation concepts. M.G.S. and A.E. are founding members of Tychon Technologies. All the other authors declare no competing interests.

Peer review

Peer review information

Nature Electronics thanks the anonymous reviewers 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.

Extended data

Extended Data Fig. 1 Coil embodiments for different use-cases.

a, The flat-spiral Z-coil is shown and is made using several loops of copper wire beginning from an inner diameter of 26 cm and extending to an outer diameter of 60 cm. Using different diameters of the copper wire, different embodiments of the Z-coil (and similarly the X and Y coils) can be realized. b, Gradient profiles generated by the Z-coil of Embodiment-1 carrying 15 A of d.c. current. The prototype used in this work is an implementation of Embodiment-1. c, Gradient profiles generated by the Z-coil of Embodiment-2 carrying 350 mA of d.c. current. The gradient in Embodiment-2 is only 5x lower than the gradient in Embodiment-1, while the d.c. current is 43x lower. d, This is achieved by using a much smaller diameter of the copper wire for Embodiment-2 that results in ≈9x increase in the number of turns that can be fitted in the same coil footprint. The 350 mA of current leads to only 0.25 W of heat (corresponding to <0.1 °C increase in the surface temperature of the coils) for a measurement done every minute, which is sufficient for monitoring the GI transit-time and motility. For applications requiring a higher sampling rate (maximum achievable 3.3 Hz by the current system), thermal insulators can be used around the coils to alleviate the heating. The 7.5 mm of mean position resolution for Embodiment-2 is acceptable for localization in the GI tract. The total weight of the coils in Embodiment-2 and the required battery for powering the coils is suitable for portable prototypes such as jackets or backpacks.

Extended Data Fig. 2 Localization error of iMAG as a function of distance from the coils.

a, The spatial error while localizing a single iMAG relative to the gradient coils is plotted for Z = 6 cm plane. The X, Y and Z errors (shown below the coil-setup) are close to the lower error-bound of the system (≈1 mm). b, The spatial errors are plotted for Z = 12 cm plane and the errors in most regions of the FOV are in 1–2 mm range. The transition to the higher error-bound of the system (≈5 mm) is visible at the boundary panes of the FOV. c, The spatial errors are plotted for Z = 18 cm plane and the presence of the higher error-bound of the system (yellow regions) is more prominent at the boundary planes of the FOV compared to the Z = 12 cm plane. The FOV ends at Z = 20 cm and the remaining half of the 40x40x40cm3 FOV is covered by the other set of the gradient coils shown in Fig. 4a.

Extended Data Fig. 3 X-Ray scans for fecal incontinence study.

a-r, Consecutive X-ray scans obtained while moving the iMAG (connected to a catheter) out of the anal sphincter in steps of five mm during the fecal incontinence study. Detailed results shown in Fig. 5a–c.

Extended Data Fig. 4 X-ray scans for magnetic label tracking.

a-p, Consecutive X-ray scans obtained while moving the iMAG (connected to a catheter) out of the anal sphincter in steps of five mm during the magnetic label (barium beads) tracking study. Detailed results shown in Fig. 5d–i.

Extended Data Fig. 5 iMAG trajectory compared to the meanders in colon.

a, Pig’s colon shown for comparison. b, iMAG trajectory from the fecal incontinence monitoring study. c, iMAG trajectory from the magnetic label tracking study. The two sharp bends in the rectum are prominently visible (highlighted by green arrows) in (a) and are captured by both the iMAG trajectories shown in (b) and (c). This shows that our technology can distinguish anatomical features for organs that are retroperitoneally fixed in the GI tract, like colon. The trajectory maps in (b) and (c) are created by plotting together all the decoded position coordinates of iMAG using the magnetic field measurements performed by it as it moves along the colon.

Extended Data Fig. 6 iMAG for smart toilets.

a, Front-view of the gradient coils assembly mounted on a toilet seat for continuous GI monitoring. b, Side-view of the toilet seat with the gradient coils. Two iMAG devices are placed in a tank filled with saline solution to demonstrate 3D localization. The experiment is repeated for n = 20 different locations of the iMAG devices in the FOV. c, Error obtained at all the locations is clustered together and plotted. d, Error at each location is plotted separately. Error reported as mean ± s.d.: 1.09 ± 1.29 mm (X), 1.25 ± 1.22 mm (Y), 0.95 ± 1.05 mm (Z). This prototype shows the ability of our technology to be deployed in common human-specific settings.

Supplementary information

Supplementary Information

Supplementary Figs. 1–15, Table 1 and links to videos for Extended Data Figs. 3 and 4.

Reporting Summary

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

Verify currency and authenticity via CrossMark

Cite this article

Sharma, S., Ramadi, K.B., Poole, N.H. et al. Location-aware ingestible microdevices for wireless monitoring of gastrointestinal dynamics. Nat Electron 6, 242–256 (2023).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:


Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research