The minimally invasive implantation strategy for NeuroWorm electrodes. [Photo/en.xum.edu.cn]

A research team led by Xie Ruijie, assistant professor at the Institute of Flexible Electronics (IFE, Future Technologies) of Xiamen University (XMU), in collaboration with Yan Wei, professor of Donghua University, and Researcher Liu Zhiyuan and Research Xu Tiantian of the Chinese Academy of Sciences, have make significant headway in the study of dynamic NeuroWorm electrodes.

Their work, titled "A movable long-term implantable soft microfibre for dynamic bioelectronics", was published in Nature on Sept 17.

Implantable neural electrodes face two major challenges: maintaining long-term stability and controlling the position of electrodes after implantation. Conventional electrodes often cause tissue damage during implantation.

To overcome these challenges, the team developed a minimally invasive implantation strategy for NeuroWorm electrodes.

By designing nanometer-thin conductive films with "C" and "L" patterns and rolling them into fibre devices, they were able to create multifunctional microfibres with longitudinally distributed electrode arrays for simultaneous electrophysiological and biomechanical monitoring.

60 electrode channels were integrated on a single fibre through this strategy, which can be sutured into muscle through an incision of just 200 micrometers. The devices enabled stable bioelectrical monitoring for more than 43 weeks and after 57 weeks, the fibre shows minimal fibroblast encapsulation, indicating excellent biocompatibility.

A magnetic tip added to the fibre allows the electrode to be steerably positioned under an external magnetic field. This enables the monitoring of brain signals in cortical and deep regions, as well as electromyographic signals in fascia between muscle and skin.

This "dynamic electrode" paradigm surpasses traditional static implants and offers a promising platform for long-term, minimally invasive, and mobile evaluation of the nervous system, opening new directions for human–machine interface research.