Advances toward a New Generation of Neural Interfaces Based on Minimally Invasive Technologies

Dear Colleagues,

Neural interfaces are well known to the biomedical community and, increasingly, to the general public. In comparison with non-invasive technologies, implantable approaches are usually advantageous in terms of spatial selectivity, quality of signal (i.e., higher signal-to-noise ratio), and usability. However, there are some important risks associated with implantable devices, such as tissue damage or infection. Thanks to technological advances in recent years, many authors have proposed several minimally invasive approaches based on miniaturized and wireless implants with different capabilities (e.g., stimulation or sensing). In addition, recent developments regarding soft and ultrathin implantable electrodes have contributed to reducing mechanical mismatch, thus minimizing tissue damage. This promising and disruptive new generation of neural interfaces will minimize the risks associated with implantable devices, while keeping the advantages over non-invasive interfaces. This ecosystem of wireless micro-implants constitutes a new challenging and multidisciplinary framework.

This Special Issue aims to present a collection of studies that address the advances, challenges, and prospects in the framework of neural interfaces based on minimally invasive technologies. This encompasses implant design (e.g., biosensors, electrodes, electronics, encapsulation), wireless power transfer methods (e.g., near/mid/far-field, radiation/coupling), networking and communication protocols (centralized approach, distributed networks, media access control, internetworking, remote management, etc.), biosignal acquisition and processing (e.g., scalable processing, large-scale processing), applications, and use cases.

Dr. Jesus Minguillon
Dr. Miguel Ángel López Gordo
Prof. Dr. Antoni Ivorra
Guest Editors

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• minimally invasive neural interfaces
• electronic implants
• wireless power transfer
• communication protocols for implants
• biosignal acquisition and processing
• stimulation and sensing applications