Submillimeter Multifunctional Ferromagnetic Fiber Robots for Navigation, Sensing, and Modulation.

Journal: Advanced healthcare materials
PMID:

Abstract

Small-scale robots capable of remote active steering and navigation offer great potential for biomedical applications. However, the current design and manufacturing procedure impede their miniaturization and integration of various diagnostic and therapeutic functionalities. Herein, submillimeter fiber robots that can integrate navigation, sensing, and modulation functions are presented. These fiber robots are fabricated through a scalable thermal drawing process at a speed of 4 meters per minute, which enables the integration of ferromagnetic, electrical, optical, and microfluidic composite with an overall diameter of as small as 250 µm and a length of as long as 150 m. The fiber tip deflection angle can reach up to 54 under a uniform magnetic field of 45 mT. These fiber robots can navigate through complex and constrained environments, such as artificial vessels and brain phantoms. Moreover, Langendorff mouse hearts model, glioblastoma micro platforms, and in vivo mouse models are utilized to demonstrate the capabilities of sensing electrophysiology signals and performing a localized treatment. Additionally, it is demonstrated that the fiber robots can serve as endoscopes with embedded waveguides. These fiber robots provide a versatile platform for targeted multimodal detection and treatment at hard-to-reach locations in a minimally invasive and remotely controllable manner.

Authors

  • Yujing Zhang
    Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA, 24061, USA.
  • Xiaobo Wu
    Translational Biology, Medicine, and Health Graduate Program, Virginia Tech, Roanoke, VA, 24016, USA.
  • Ram Anand Vadlamani
    Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA, 24061, USA.
  • Youngmin Lim
    Department of Physics, Virginia Tech, Blacksburg, VA, 24061, USA.
  • Jongwoon Kim
    Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA, 24061, USA.
  • Kailee David
    Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA, 24061, USA.
  • Earl Gilbert
    Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA, 24061, USA.
  • You Li
    CFAR and I2R, Agency for Science, Technology and Research, Singapore.
  • Ruixuan Wang
    School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, P. R. China. wangruix5@mail.sysu.edu.cn.
  • Shan Jiang
    Emergency Center, Hubei Clinical Research Center for Emergency and Resuscitaion, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.
  • Anbo Wang
    Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA, 24061, USA.
  • Harald Sontheimer
    Department of Neuroscience, University of Virginia, Charlottesville, VA, 22903, USA.
  • Daniel Fine English
    School of Neuroscience, Virginia Tech, Blacksburg, VA, 24061, USA.
  • Satoru Emori
    Department of Physics, Virginia Tech, Blacksburg, VA, 24061, USA.
  • Rafael V Davalos
    Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA, 24061, USA.
  • Steven Poelzing
    Translational Biology, Medicine, and Health Graduate Program, Virginia Tech, Roanoke, VA, 24016, USA.
  • Xiaoting Jia
    Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA, 24061, USA.