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Micromachines
Special Issues
Intelligent Bioelectronics and Neural Interfaces
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Intelligent Bioelectronics and Neural Interfaces

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "B：Biology and Biomedicine".

Deadline for manuscript submissions: 30 September 2024 | Viewed by 1630

Special Issue Editor

Dr. Liuyang Sun

E-Mail Website
Guest Editor
2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China
Interests: micro/nano sensing; neural engineering; nanophotonics

Special Issue Information

Dear Colleagues,

From brain–computer interfaces that empower paralyzed individuals to regain mobility, to smart prosthetics that are able to mimic human limbs, the fusion of intelligent bioelectronics and neural interfaces is revolutionizing our understanding of human–machine symbiosis. With the development of multi-disciplinary research, intelligent bioelectronics and neural interfaces have also witnessed numerous breakthroughs. For example, implantable devices can record neural signals for research purposes or deliver precise stimulation for therapeutic interventions; neural probes with multiple electrodes can be inserted into brain tissue to record neural activity from multiple locations simultaneously; and micromachining techniques can contribute to the development of flexible and stretchable electronic devices that can conform to the body's movements, just to name a few. Nevertheless, challenges persist in the realm of intelligent bioelectronics. For devices, efficient signal acquisition and application, as well as enhanced biocompatibility, are urgent issues. In the field of neural interfaces, accurately deciphering complex neural signals and achieving long-term implantation remain forefront challenges. These hurdles necessitate collaborative interdisciplinary efforts and innovative approaches. Accordingly, this Special Issue seeks to showcase research papers, communications, and review articles that focus on the following topics: advanced bioelectronics processing, i.e., biocompatible materials for neuro interfaces, implantable devices, high-throughput systems in intelligent bioelectronics, clinical applications and translational research.

Dr. Liuyang Sun
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Micromachines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • neural signal encoding and decoding
  • neural electrodes: flexible electrodes, stretchable electrodes
  • bio-sensors and bio-actuators
  • neural signal processing unit
  • BMI-based robots
  • implantable bioelectronics
  • neuroprosthetics
  • neurological disorder diagnosis and treatment

Published Papers (3 papers)

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Research

14 pages, 9925 KiB  
Article
Modulation Steering Motion by Quantitative Electrical Stimulation in Pigeon Robots
by Mingxuan Bi, Huimin Zhang, Yaohong Ma, Hao Wang, Wenbo Wang, Yuan Shi, Wenlong Sheng, Qiushun Li, Guangheng Gao and Lei Cai
Micromachines 2024, 15(5), 595; https://doi.org/10.3390/mi15050595 - 29 Apr 2024
Viewed by 259
Abstract
The pigeon robot has attracted significant attention in the field of animal robotics thanks to its outstanding mobility and adaptive capability in complex environments. However, research on pigeon robots is currently facing bottlenecks, and achieving fine control over the motion behavior of pigeon [...] Read more.
The pigeon robot has attracted significant attention in the field of animal robotics thanks to its outstanding mobility and adaptive capability in complex environments. However, research on pigeon robots is currently facing bottlenecks, and achieving fine control over the motion behavior of pigeon robots through brain–machine interfaces remains challenging. Here, we systematically quantify the relationship between electrical stimulation and stimulus-induced motion behaviors, and provide an analytical method to demonstrate the effectiveness of pigeon robots based on electrical stimulation. In this study, we investigated the influence of gradient voltage intensity (1.2–3.0 V) on the indoor steering motion control of pigeon robots. Additionally, we discussed the response time of electrical stimulation and the effective period of the brain–machine interface. The results indicate that pigeon robots typically exhibit noticeable behavioral responses at a 2.0 V voltage stimulus. Increasing the stimulation intensity significantly controls the steering angle and turning radius (p < 0.05), enabling precise control of pigeon robot steering motion through stimulation intensity regulation. When the threshold voltage is reached, the average response time of a pigeon robot to the electrical stimulation is 220 ms. This study quantifies the role of each stimulation parameter in controlling pigeon robot steering behavior, providing valuable reference information for the precise steering control of pigeon robots. Based on these findings, we offer a solution for achieving precise control of pigeon robot steering motion and contribute to solving the problem of encoding complex trajectory motion in pigeon robots. Full article
(This article belongs to the Special Issue Intelligent Bioelectronics and Neural Interfaces)
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12 pages, 2421 KiB  
Article
Flexible Peripheral Nerve Interfacing Electrode for Joint Position Control in Closed-Loop Neuromuscular Stimulation
by Sia Kim and Kang-Il Song
Micromachines 2024, 15(5), 594; https://doi.org/10.3390/mi15050594 - 29 Apr 2024
Viewed by 212
Abstract
Addressing peripheral nerve disorders with electronic medicine poses significant challenges, especially in replicating the dynamic mechanical properties of nerves and understanding their functionality. In the field of electronic medicine, it is crucial to design a system that thoroughly understands the functions of the [...] Read more.
Addressing peripheral nerve disorders with electronic medicine poses significant challenges, especially in replicating the dynamic mechanical properties of nerves and understanding their functionality. In the field of electronic medicine, it is crucial to design a system that thoroughly understands the functions of the nervous system and ensures a stable interface with nervous tissue, facilitating autonomous neural adaptation. Herein, we present a novel neural interface platform that modulates the peripheral nervous system using flexible nerve electrodes and advanced neuromodulation techniques. Specifically, we have developed a surface-based inverse recruitment model for effective joint position control via direct electrical nerve stimulation. Utilizing barycentric coordinates, this model constructs a three-dimensional framework that accurately interpolates inverse isometric recruitment values across various joint positions, thereby enhancing control stability during stimulation. Experimental results from rabbit ankle joint control trials demonstrate our model’s effectiveness. In combination with a proportional–integral–derivative (PID) controller, it shows superior performance by achieving reduced settling time (less than 1.63 s), faster rising time (less than 0.39 s), and smaller steady-state error (less than 3 degrees) compared to the legacy model. Moreover, the model’s compatibility with recent advances in flexible interfacing technologies and its integration into a closed-loop controlled functional neuromuscular stimulation (FNS) system highlight its potential for precise neuroprosthetic applications in joint position control. This approach marks a significant advancement in the management of neurological disorders with advanced neuroprosthetic solutions. Full article
(This article belongs to the Special Issue Intelligent Bioelectronics and Neural Interfaces)
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14 pages, 45842 KiB  
Article
A Comparative Study on the Effect of Substrate Structure on Electrochemical Performance and Stability of Electrodeposited Platinum and Iridium Oxide Coatings for Neural Electrodes
by Linze Li, Changqing Jiang and Luming Li
Micromachines 2024, 15(1), 70; https://doi.org/10.3390/mi15010070 - 29 Dec 2023
Viewed by 854
Abstract
Implantable electrodes are crucial for stimulation safety and recording quality of neuronal activity. To enhance their electrochemical performance, electrodeposited nanostructured platinum (nanoPt) and iridium oxide (IrOx) have been proposed due to their advantages of in situ deposition and ease of processing. [...] Read more.
Implantable electrodes are crucial for stimulation safety and recording quality of neuronal activity. To enhance their electrochemical performance, electrodeposited nanostructured platinum (nanoPt) and iridium oxide (IrOx) have been proposed due to their advantages of in situ deposition and ease of processing. However, their unstable adhesion has been a challenge in practical applications. This study investigated the electrochemical performance and stability of nanoPt and IrOx coatings on hierarchical platinum-iridium (Pt-Ir) substrates prepared by femtosecond laser, compared with the coatings on smooth Pt-Ir substrates. Ultrasonic testing, agarose gel testing, and cyclic voltammetry (CV) testing were used to evaluate the coatings’ stability. Results showed that the hierarchical Pt-Ir substrate significantly enhanced the charge-storage capacity of electrodes with both coatings to more than 330 mC/cm2, which was over 75 times that of the smooth Pt-Ir electrode. The hierarchical substrate could also reduce the cracking of nanoPt coatings after ultrasonic, agarose gel and CV testing. Although some shedding was observed in the IrOx coating on the hierarchical substrate after one hour of sonication, it showed good stability in the agarose gel and CV tests. Stable nanoPt and IrOx coatings may not only improve the electrochemical performance but also benefit the function of neurobiochemical detection. Full article
(This article belongs to the Special Issue Intelligent Bioelectronics and Neural Interfaces)
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