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Distributed battery-free bioelectronic implants with improved network power transfer efficiency via magnetoelectrics

Nature Biomedical Engineering (2025)Cite this article

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Abstract

Networks of miniature implants could enable simultaneous sensing and stimulation at different locations in the body, such as the heart and central or peripheral nervous system. This capability would support precise disease tracking and treatment or enable prosthetic technologies with many degrees of freedom. However, wireless power and data transfer are often inefficient through biological tissues, particularly as the number of implanted devices increases. Here we show that magnetoelectric wireless data and power transfer supports a network of millimetre-sized bioelectronic implants in which system efficiency improves with additional devices. We demonstrate wireless, battery-free networks ranging from one to six implants, where the total system efficiency increases from 0.2% to 1.3%, with each node receiving 2.2 mW at 1 cm distance. We show proof-of-concept networks of miniature spinal cord stimulators and cardiac pacing devices in large animals via efficient and robust wireless power transfer. These magnetoelectric implants provide a scalable network architecture of bioelectronic implants for next-generation electronic medicine.

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Fig. 1: A network of wireless, battery-free, ME-powered devices.
Fig. 2: Scaling limits for ME networks.
Fig. 3: A wireless network for epidural SCS.
Fig. 4: A wireless network for cardiac pacing.

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Data availability

The main data supporting the results of this study are available within the paper and its Supplementary Information. Source data for Figs. 2a,c,d, 3b,d and 4f are available via figshare at https://doi.org/10.6084/m9.figshare.29431022, https://doi.org/10.6084/m9.figshare.29430995, https://doi.org/10.6084/m9.figshare.29431034, https://doi.org/10.6084/m9.figshare.29431040 and https://doi.org/10.6084/m9.figshare.29431061 (refs. 50,51,52,53,54).

Code availability

The custom MATLAB code used to preprocess and plot data for Figs. 2c, 3e and 4f are available via figshare at https://doi.org/10.6084/m9.figshare.29430995, https://doi.org/10.6084/m9.figshare.29431040 and https://doi.org/10.6084/m9.figshare.29431061 (refs. 51,53,54).

References

  1. Lee, J. et al. Neural recording and stimulation using wireless networks of microimplants. Nat. Electron. 4, 604–614 (2021).

    Article  Google Scholar 

  2. Tawakol, O. et al. In-vivo testing of a novel wireless intraspinal microstimulation interface for restoration of motor function following spinal cord injury. Artif. Organs 48, 263–273 (2024).

    Article  CAS  PubMed  Google Scholar 

  3. Becerra-Fajardo, L. et al. First-in-human demonstration of floating EMG sensors and stimulators wirelessly powered and operated by volume conduction. J. Neuroeng. Rehabil. 21, 4 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Becerra-Fajardo, L. et al. Floating EMG sensors and stimulators wirelessly powered and operated by volume conduction for networked neuroprosthetics. J. Neuroeng. Rehabil. 19, 57 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Benedict, B. C., Ghanbari, M. M. & Muller, R. Phased array beamforming methods for powering biomedical ultrasonic implants. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 69, 2756–2765 (2022).

    Article  PubMed  Google Scholar 

  6. Costello, J. T. et al. A low-power communication scheme for wireless, 1000 channel brain-machine interfaces. J. Neural. Eng. 19, 036037 (2022).

    Article  Google Scholar 

  7. Dinis, H., Colmiais, I. & Mendes, P. M. Extending the limits of wireless power transfer to miniaturized implantable electronic devices. Micromachines 8, 359 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Lyu, H. et al. Synchronized biventricular heart pacing in a closed-chest porcine model based on wirelessly powered leadless pacemakers. Sci. Rep. 10, 2067 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Nguyen, N., Ha-Van, N. & Seo, C. Midfield wireless power transfer for deep-tissue biomedical implants. IEEE Antennas Wirel. Propag. Lett. 19, 2270–2274 (2020).

    Article  Google Scholar 

  10. Lee, J. et al. A sub-mm3 wireless neural stimulator IC for visual cortical prosthesis with optical power harvesting and 7.5-kb/s data telemetry. IEEE J. Solid-State Circuits https://doi.org/10.1109/JSSC.2023.3349179 (2024).

  11. Kim, W. et al. Magnetoelectrics enables large power delivery to mm-sized wireless bioelectronics. J. Appl. Phys. 134, 094103 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Chen, J. C. et al. A wireless millimetric magnetoelectric implant for the endovascular stimulation of peripheral nerves. Nat. Biomed. Eng. https://doi.org/10.1038/s41551-022-00873-7 (2022).

  13. Bichurin, M. I. et al. Resonance magnetoelectric effects in layered magnetostrictive-piezoelectric composites. Phys. Rev. B 68, 132408 (2003).

    Article  Google Scholar 

  14. Chen, R., Canales, A. & Anikeeva, P. Neural recording and modulation technologies. Nat. Rev. Mater. 2, 16093 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Bottomley, P. A. & Andrew, E. R. RF magnetic field penetration, phase shift and power dissipation in biological tissue: implications for NMR imaging. Phys. Med. Biol. 23, 630 (1978).

    Article  CAS  PubMed  Google Scholar 

  16. Alrashdan, F. T. et al. Wearable wireless power systems for ‘ME-BIT’ magnetoelectric-powered bio implants. J. Neural Eng. 18, 045011 (2021).

    Article  Google Scholar 

  17. Sdrulla, A., Guan, Y. & Raja, S. Spinal cord stimulation: clinical efficacy and potential mechanisms. Pain. Pract. 18, 1048–1067 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Gill, M. L. et al. Neuromodulation of lumbosacral spinal networks enables independent stepping after complete paraplegia. Nat. Med. 24, 1677–1682 (2018).

    Article  CAS  PubMed  Google Scholar 

  19. Angeli, C. A. et al. Recovery of over-ground walking after chronic motor complete spinal cord injury. N. Engl. J. Med. 379, 1244–1250 (2018).

    Article  PubMed  Google Scholar 

  20. Rowald, A. et al. Activity-dependent spinal cord neuromodulation rapidly restores trunk and leg motor functions after complete paralysis. Nat. Med. 28, 260–271 (2022).

    Article  CAS  PubMed  Google Scholar 

  21. Sayenko, D. G., Angeli, C., Harkema, S. J., Edgerton, V. R. & Gerasimenko, Y. P. Neuromodulation of evoked muscle potentials induced by epidural spinal-cord stimulation in paralyzed individuals. J. Neurophysiol. 111, 1088–1099 (2014).

    Article  PubMed  Google Scholar 

  22. Greiner, N. et al. Recruitment of upper-limb motoneurons with epidural electrical stimulation of the cervical spinal cord. Nat. Commun. 12, 435 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Powell, M. P. et al. Epidural stimulation of the cervical spinal cord for post-stroke upper-limb paresis. Nat. Med. 29, 689–699 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. North, R. B. & Prager, J. P. In Neuromodulation 2nd edn (eds. Krames, E. S., Peckham, P. H. & Rezai, A. R.) 587–596 (Academic, 2018).

  25. Woods, J. E. et al. Miniature battery-free epidural cortical stimulators. Sci. Adv. 10, eadn0858 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Alò, K. et al. Factors affecting impedance of percutaneous leads in spinal cord stimulation. Neuromodulation Technol. Neural Interface 9, 128–135 (2006).

    Article  Google Scholar 

  27. Toossi, A. et al. Comparative neuroanatomy of the lumbosacral spinal cord of the rat, cat, pig, monkey, and human. Sci. Rep. 11, 1955 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Steele, A. G. et al. Mapping lumbar efferent and afferent spinal circuitries via paddle array in a porcine model. J. Neurosci. Methods 405, 110104 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Zander, H. J., Graham, R. D., Anaya, C. J. & Lempka, S. F. Anatomical and technical factors affecting the neural response to epidural spinal cord stimulation. J. Neural Eng. 17, 036019 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Abraham, W. T. & Hayes, D. L. Cardiac resynchronization therapy for heart failure. Circulation 108, 2596–2603 (2003).

    Article  PubMed  Google Scholar 

  31. Brabham, W. W. & Gold, M. R. The role of AV and VV optimization for CRT. J. Arrhythmia 29, 153–161 (2013).

    Article  Google Scholar 

  32. Kotsakou, M. et al. Pacemaker insertion. Ann. Transl. Med. 3, 42–42 (2015).

    PubMed  PubMed Central  Google Scholar 

  33. Vouliotis, A. I. et al. Leadless pacemakers: current achievements and future perspectives. Eur. Cardiol. 18, e49 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Furman, S., Hurzeler, P. & Mehra, R. Cardiac pacing and pacemakers IV. Threshold of cardiac stimulation. Am. Heart J. 94, 115–124 (1977).

    Article  CAS  PubMed  Google Scholar 

  35. Abbott. AveirTM Leadless Pacemaker IFU. Product Instructions for Use (2021); https://www.accessdata.fda.gov/cdrh_docs/pdf15/P150035D.pdf

  36. Medtronic. MicraTM AV MC1AVR1 Manual (2020); https://wwwp.medtronic.com/crs-upload/letters/401/401_Micra_AV_Implant_Manual_with_Medical_Procedure_and_EMI_Precautions.pdf

  37. Zangooei, H., Mirbozorgi, S. A. & Mirbozorgi, S. Thermal analysis of heat transfer from catheters and implantable devices to the blood flow. Micromachines 12, 230 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Roujol, S., Tan, A. Y., Anter, E., Josephson, M. E. & Nezafat, R. Towards cardiac and respiratory motion characterization from electrophysiology data for improved real time MR-integration. J. Cardiovasc. Magn. Reson. 15, P68 (2013).

    Article  PubMed Central  Google Scholar 

  39. Werner, R., Ehrhardt, J., Schmidt, R. & Handels, H. Patient-specific finite element modeling of respiratory lung motion using 4D CT image data. Med. Phys. 36, 1500–1511 (2009).

    Article  PubMed  Google Scholar 

  40. Mukherjee, D. & Mallick, D. Magnetoelectric wireless power transfer system for biomedical implants. In 2021 IEEE International Midwest Symposium on Circuits and Systems (MWSCAS) https://doi.org/10.1109/MWSCAS47672.2021.9531861 (IEEE, 2021).

  41. Rupp, T., Truong, B. D., Williams, S. & Roundy, S. Magnetoelectric transducer designs for use as wireless power receivers in wearable and implantable applications. Materials 12, 512 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. García-Moreno, A. et al. Wireless networks of injectable microelectronic stimulators based on rectification of volume conducted high frequency currents. J. Neural Eng. 19, 056015 (2022).

    Article  Google Scholar 

  43. Nair, V. et al. Miniature battery-free bioelectronics. Science 382, eabn4732 (2023).

    Article  CAS  PubMed  Google Scholar 

  44. Liu, Y., Zhang, J., Zhu, C. & Chan, C. C. A study on the safety analysis of an inductive power transfer system for kitchen appliances. Energies 15, 5218 (2022).

    Article  Google Scholar 

  45. Singer, A. & Robinson, J. T. Wireless power delivery techniques for miniature implantable bioelectronics. Adv. Healthc. Mater. 10, 2100664 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Webster, J. G. Design of Cardiac Pacemakers (IEEE, 1995).

  47. Baumgartner, C. et al. IT’IS Database for thermal and electromagnetic parameters of biological tissues. Version 4.2. IT’IS Foundation https://doi.org/10.13099/VIP21000-04-0 (2024).

  48. Yu, Z. et al. MagNI: a magnetoelectrically powered and controlled wireless neurostimulating implant. IEEE Trans. Biomed. Circuits Syst. 14, 1241–1252 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Mathis, A. et al. DeepLabCut: markerless pose estimation of user-defined body parts with deep learning. Nat. Neurosci. 21, 1281–1289 (2018).

    Article  CAS  PubMed  Google Scholar 

  50. Woods, J. E. et al. Dataset for distributed battery-free bioelectronic implants with improved network power transfer efficiency via magnetoelectrics Fig. 2a and Fig. 2d. figshare https://doi.org/10.6084/m9.figshare.29431022 (2025).

  51. Woods, J. E. et al. Dataset for distributed battery-free bioelectronic implants with improved network power transfer efficiency via magnetoelectrics Fig. 2c. figshare https://doi.org/10.6084/m9.figshare.29430995 (2025).

  52. Woods, J. E. et al. Dataset for distributed battery-free bioelectronic implants with improved network power transfer efficiency via magnetoelectrics Fig. 3b. figshare https://doi.org/10.6084/m9.figshare.29431034 (2025).

  53. Woods, J. E. et al. Dataset for distributed battery-free bioelectronic implants with improved network power transfer efficiency via magnetoelectrics Fig. 3e. figshare https://doi.org/10.6084/m9.figshare.29431040 (2025).

  54. Woods, J. E. et al. Dataset for distributed battery-free bioelectronic implants with improved network power transfer efficiency via magnetoelectrics Fig. 4f. figshare https://doi.org/10.6084/m9.figshare.29431061 (2025).

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Acknowledgements

This work was supported in part by the National Heart Lung and Blood Institute of the National Institutes of Health under award no. R01HL144683 (to M.R.), the National Institutes of Health under award no. 1R01NS119587-01A (to D.G.S.), the Walter Neurological Restoration Initiative sponsored by The Paula and J. C. ‘Rusty’ Walter III and the Walter Oil and Gas Corporation, the Wings for Life Foundation (268) (to D.G.S.) and the National Science Foundation GRFP (to J.E.W. and E.C.). We acknowledge the pigs that took part in this study, without whom this would not be possible. We would also like to thank the Texas Heart Institute Veterinary Staff and the Houston Methodist Veterinary Staff for their care of the pigs used in this study.

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  1. These authors contributed equally: Joshua E. Woods, Fatima Alrashdan.

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA

    Joshua E. Woods, Fatima Alrashdan, Ellie C. Chen, Wendy Tan, Amir H. Faraji & Jacob T. Robinson

  2. The Texas Heart Institute at Baylor College of Medicine, Houston, TX, USA

    Mathews John, Lukas Jaworski, Drew Bernard, Allison Post, Angel Moctezuma-Ramirez, Abdelmotagaly Elgalad & Mehdi Razavi

  3. Department of Neurosurgery, Houston Methodist, Houston, TX, USA

    Alexander G. Steele, Sean M. Barber, Philip J. Horner, Amir H. Faraji & Dimitry G. Sayenko

  4. Department of Neurosurgery, Center for Neuroregeneration, Houston Methodist, Houston, TX, USA

    Alexander G. Steele, Sean M. Barber, Philip J. Horner, Amir H. Faraji & Dimitry G. Sayenko

  5. Department of Medicine, Cardiology, Baylor College of Medicine, Houston, TX, USA

    Mehdi Razavi

  6. Department of Bioengineering, Rice University, Houston, TX, USA

    Jacob T. Robinson

  7. Applied Physics Program, Rice University, Houston, TX, USA

    Jacob T. Robinson

  8. Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA

    Jacob T. Robinson

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Contributions

J.E.W. and E.C.C. designed and tested the PCBs. J.E.W., F.A. and W.T. assembled the ME devices. J.E.W. performed the testing, characterization, and simulation of the ME network. J.E.W., F.A., A.G.S., S.M.B., P.J.H., A.H.F. and D.G.S. designed and performed the porcine SCS experiments. J.E.W. and A.G.S. analysed the porcine SCS experiment data. J.E.W., F.A., W.T., E.C.C., M.J., D.B., A.P., A.M.-R., A.E. and M.R. designed and performed the porcine cardiac pacing experiments. J.E.W. and M.J. analysed the cardiac pacing experiment data. J.T.R., J.E.W. and F.A. contributed to the design of experiments. J.W. and J.T.R. prepared the manuscript with input from all authors.

Corresponding author

Correspondence to Jacob T. Robinson.

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Competing interests

J.T.R., F.A. and J.E.W. receive monetary and/or equity compensation from Motif Neurotech. A.F. is a consultant for Medtronic, Inc., Boston Scientific, Inc. and Abbott, Inc. M.R. receives monetary and/or equity compensation from Maxwell Biomedical, Rhythio and XNHealth, consults for Ziopatch and is the medical director for IRhythm. The terms of these arrangements have been reviewed and approved by Rice University, the Houston Methodist Research Institute, Baylor College of Medicine and The Texas Heart Institute in accordance with their policies on conflict of interest in research. The other authors declare no competing interests.

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Nature Biomedical Engineering thanks Peilong Feng and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Tables 1–3, Figs. 1–10 and Descriptions of Movies 1 and 2.

Reporting Summary

Movie 1

A network of 12 wirelessly powered and programmed ME devices. The video shows a programmed sequence of blinking devices, all simultaneously powered and programmed by a single transmitter. The devices can be moved while still receiving power and data, as shown in the first segment by moving one of the devices. Arbitrary sequences can be programmed rapidly as shown in the second segment.

Movie 2

Heart movement simulator testing. The video shows the benchtop testing system used to characterize the cardiac pacing devices. Devices are placed on a moving platform while powered and controlled by a single external TX coil. Then, 2.5 cm of ground beef is placed between the TX coil and devices, and the beef and devices are submerged in 0.9% NaCl.

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Woods, J.E., Alrashdan, F., Chen, E.C. et al. Distributed battery-free bioelectronic implants with improved network power transfer efficiency via magnetoelectrics. Nat. Biomed. Eng (2025). https://doi.org/10.1038/s41551-025-01489-3

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