Joshua E. Woods, Fatima Alrashdan, Ellie C. Chen, Wendy Tan, Mathews John, Lukas Jaworski, Drew Bernard, Allison Post, Angel Moctezuma-Ramirez, Abdelmotagaly Elgalad, Alexander G. Steele, Sean M. Barber, Philip J. Horner, Amir H. Faraji, Dimitry G. Sayenko, Mehdi Razavi, Jacob T. Robinson
{"title":"Distributed battery-free bioelectronic implants with improved network power transfer efficiency via magnetoelectrics","authors":"Joshua E. Woods, Fatima Alrashdan, Ellie C. Chen, Wendy Tan, Mathews John, Lukas Jaworski, Drew Bernard, Allison Post, Angel Moctezuma-Ramirez, Abdelmotagaly Elgalad, Alexander G. Steele, Sean M. Barber, Philip J. Horner, Amir H. Faraji, Dimitry G. Sayenko, Mehdi Razavi, Jacob T. Robinson","doi":"10.1038/s41551-025-01489-3","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":"13 1","pages":""},"PeriodicalIF":26.8000,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Biomedical Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1038/s41551-025-01489-3","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
Nature Biomedical Engineering is an online-only monthly journal that was launched in January 2017. It aims to publish original research, reviews, and commentary focusing on applied biomedicine and health technology. The journal targets a diverse audience, including life scientists who are involved in developing experimental or computational systems and methods to enhance our understanding of human physiology. It also covers biomedical researchers and engineers who are engaged in designing or optimizing therapies, assays, devices, or procedures for diagnosing or treating diseases. Additionally, clinicians, who make use of research outputs to evaluate patient health or administer therapy in various clinical settings and healthcare contexts, are also part of the target audience.