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Biosensors
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Implantable, Wireless Biosensors and Biodevices for Neuroscience Research
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Implantable, Wireless Biosensors and Biodevices for Neuroscience Research

A special issue of Biosensors (ISSN 2079-6374). This special issue belongs to the section "Biosensor and Bioelectronic Devices".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 14115

Special Issue Editors

Prof. Dr. Ming Yin

E-Mail Website
Guest Editor
School of Biomedical Engineering, Hainan University, Haikou, China
Interests: wireless implantable biomedical sensors; neural recording; stimulation systems; implantable neural interfaces; brain-computer interfaces
Dr. David A. Borton

E-Mail Website
Guest Editor
1. Associate Professor of Engineering, School of Engineering, Brown University, Providence, RI, USA
2. Biomedical Engineer, Center for Neurotechnology and Neurorestoration, Department of Veterans Affairs, Washington, DC, USA
Interests: neuroengineering; neuromotor disease; neuroprosthetics; responsive neuromodulation; spinal cord injury
Prof. Dr. Jiayi Zhang

E-Mail Website
Guest Editor
Institutes of Brain Science, Fudan University, Shanghai, China
Interests: visual function; brain computer interface; neuroscience

Special Issue Information

Dear Colleagues,

With the rapidly increasing promise of cutting-edge neuroscience research to reach translational success, biosensing and neuromodulation technologies have seen rapid and significant innovation. Among the key innovations driving new research and future therapies is the development of implantable, wireless tools to interact with the nervous system. Implantable systems enable proximal access to biological signal sources and offer high spatial and temporal resolution of signals with a quality that cannot be matched by other modalities. Additionally, cellular-level optical functional imaging can further help in dissecting neural circuits by recordings from genetically targeted neuronal types. However, these systems present significant technological challenges (e.g., miniaturization, biocompatibility, high-speed yet low-power data communication, wireless power transfer, and hermeticity)—challenges which continue to inspire biosensor researchers to exploit multi-disciplinary knowledge to push the limits of the field.  

This Special Issue will gather advances highlighting novel device development and original work on implantable biosensors and biodevices for neuroscience research. Topics of interest include, but are not limited to, implantable microsystems for biosensing; multichannel electrical, optical or chemical electrodes and sensors; bio-interrogation devices; wireless power and data transfer for implantable neurosensors and modulators; low-power and miniaturized electronics for neural data processing; as well as cutting-edge applications of the aforementioned techniques.

Prof. Dr. Ming Yin
Dr. David A. Borton
Prof. Dr. Jiayi Zhang
Guest Editors

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. Biosensors 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 2700 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

  • implantable
  • wireless
  • neurosensing
  • neuromodulation
  • biodevices
  • low-power
  • biocompatibility
  • bidirectional interfaces

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Published Papers (6 papers)

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Research

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21 pages, 3174 KiB  
Article
MLS-Net: An Automatic Sleep Stage Classifier Utilizing Multimodal Physiological Signals in Mice
by Chengyong Jiang, Wenbin Xie, Jiadong Zheng, Biao Yan, Junwen Luo and Jiayi Zhang
Biosensors 2024, 14(8), 406; https://doi.org/10.3390/bios14080406 - 22 Aug 2024
Viewed by 1036
Abstract
Over the past decades, feature-based statistical machine learning and deep neural networks have been extensively utilized for automatic sleep stage classification (ASSC). Feature-based approaches offer clear insights into sleep characteristics and require low computational power but often fail to capture the spatial–temporal context [...] Read more.
Over the past decades, feature-based statistical machine learning and deep neural networks have been extensively utilized for automatic sleep stage classification (ASSC). Feature-based approaches offer clear insights into sleep characteristics and require low computational power but often fail to capture the spatial–temporal context of the data. In contrast, deep neural networks can process raw sleep signals directly and deliver superior performance. However, their overfitting, inconsistent accuracy, and computational cost were the primary drawbacks that limited their end-user acceptance. To address these challenges, we developed a novel neural network model, MLS-Net, which integrates the strengths of neural networks and feature extraction for automated sleep staging in mice. MLS-Net leverages temporal and spectral features from multimodal signals, such as EEG, EMG, and eye movements (EMs), as inputs and incorporates a bidirectional Long Short-Term Memory (bi-LSTM) to effectively capture the spatial–temporal nonlinear characteristics inherent in sleep signals. Our studies demonstrate that MLS-Net achieves an overall classification accuracy of 90.4% and REM state precision of 91.1%, sensitivity of 84.7%, and an F1-Score of 87.5% in mice, outperforming other neural network and feature-based algorithms in our multimodal dataset. Full article
(This article belongs to the Special Issue Implantable, Wireless Biosensors and Biodevices for Neuroscience Research)
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15 pages, 23619 KiB  
Article
A Scalable, Programmable Neural Stimulator for Enhancing Generalizability in Neural Interface Applications
by Meng Yin, Xiao Wang, Liuxindai Zhang, Guijun Shu, Zhen Wang, Shoushuang Huang and Ming Yin
Biosensors 2024, 14(7), 323; https://doi.org/10.3390/bios14070323 - 28 Jun 2024
Viewed by 1065
Abstract
Each application of neurostimulators requires unique stimulation parameter specifications to achieve effective stimulation. Balancing the current magnitude with stimulation resolution, waveform, size, and channel count is challenging, leading to a loss of generalizability across broad neural interfaces. To address this, this paper proposes [...] Read more.
Each application of neurostimulators requires unique stimulation parameter specifications to achieve effective stimulation. Balancing the current magnitude with stimulation resolution, waveform, size, and channel count is challenging, leading to a loss of generalizability across broad neural interfaces. To address this, this paper proposes a highly scalable, programmable neurostimulator with a System-on-Chip (SOC) capable of 32 channels of independent stimulation. The compliance voltage reaches up to ±22.5 V. A pair of 8-bit current-mode DACs support independent waveforms for source and sink operations and feature a user-selectable dual range for low-current intraparenchymal microstimulation with a resolution of 4.31 μA/bit, as well as high current stimulation for spinal cord and DBS applications with a resolution of 48.00 μA/bit, achieving a wide stimulation range of 12.24 mA while maintaining high-resolution biological stimulation. A dedicated communication protocol enables full programmable control of stimulation waveforms, effectively improving the range of stimulation parameters. In vivo electrophysiological experiments successfully validate the functionality of the proposed stimulator. This flexible stimulator architecture aims to enhance its generality across a wide range of neural interfaces and will provide more diverse and refined stimulation strategies. Full article
(This article belongs to the Special Issue Implantable, Wireless Biosensors and Biodevices for Neuroscience Research)
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16 pages, 17525 KiB  
Article
Power-to-Noise Optimization in the Design of Neural Recording Amplifier Based on Current Scaling, Source Degeneration Resistor, and Current Reuse
by Zhen Wang, Xiao Wang, Guijun Shu, Meng Yin, Shoushuang Huang and Ming Yin
Biosensors 2024, 14(2), 111; https://doi.org/10.3390/bios14020111 - 19 Feb 2024
Viewed by 2235
Abstract
This article presents the design of a low-power, low-noise neural signal amplifier for neural recording. The structure reduces the current consumption of the amplifier through current scaling technology and lowers the input-referred noise of the amplifier by combining a source degeneration resistor and [...] Read more.
This article presents the design of a low-power, low-noise neural signal amplifier for neural recording. The structure reduces the current consumption of the amplifier through current scaling technology and lowers the input-referred noise of the amplifier by combining a source degeneration resistor and current reuse technologies. The amplifier was fabricated using a 0.18 μm CMOS MS RF G process. The results show the front-end amplifier exhibits a measured mid-band gain of 40 dB/46 dB and a bandwidth ranging from 0.54 Hz to 6.1 kHz; the amplifier’s input-referred noise was measured to be 3.1 μVrms, consuming a current of 3.8 μA at a supply voltage of 1.8 V, with a Noise Efficiency Factor (NEF) of 2.97. The single amplifier’s active silicon area is 0.082 mm2. Full article
(This article belongs to the Special Issue Implantable, Wireless Biosensors and Biodevices for Neuroscience Research)
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11 pages, 17149 KiB  
Article
An Ultra-Low-Noise, Low Power and Miniaturized Dual-Channel Wireless Neural Recording Microsystem
by Haochuan Wang, Qian Ma, Keming Chen, Hanqing Zhang, Yinyan Yang, Nenggan Zheng and Hui Hong
Biosensors 2022, 12(8), 613; https://doi.org/10.3390/bios12080613 - 8 Aug 2022
Cited by 6 | Viewed by 2443
Abstract
As the basic tools for neuroscience research, invasive neural recording devices can obtain high-resolution neuronal activity signals through electrodes connected to the subject’s brain. Existing wireless neural recording devices are large in size or need external large-scale equipment for wireless power supply, which [...] Read more.
As the basic tools for neuroscience research, invasive neural recording devices can obtain high-resolution neuronal activity signals through electrodes connected to the subject’s brain. Existing wireless neural recording devices are large in size or need external large-scale equipment for wireless power supply, which limits their application. Here, we developed an ultra-low-noise, low power and miniaturized dual-channel wireless neural recording microsystem. With the full-differential front-end structure of the dual operational amplifiers (op-amps), the noise level and power consumption are notably reduced. The hierarchical microassembly technology, which integrates wafer-level packaged op-amps and the miniaturized Bluetooth module, dramatically reduces the size of the wireless neural recording microsystem. The microsystem shows a less than 100 nV/Hz ultra-low noise level, about 10 mW low power consumption, and 9 × 7 × 5 mm3 small size. The neural recording ability was then demonstrated in saline and a chronic rat model. Because of its miniaturization, it can be applied to freely behaving small animals, such as rats. Its features of ultra-low noise and high bandwidth are conducive to low-amplitude neural signal recording, which may help advance neuroscientific discovery. Full article
(This article belongs to the Special Issue Implantable, Wireless Biosensors and Biodevices for Neuroscience Research)
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Review

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23 pages, 1753 KiB  
Review
Non-Invasive Brain Sensing Technologies for Modulation of Neurological Disorders
by Salman Alfihed, Majed Majrashi, Muhammad Ansary, Naif Alshamrani, Shahad H. Albrahim, Abdulrahman Alsolami, Hala A. Alamari, Adnan Zaman, Dhaifallah Almutairi, Abdulaziz Kurdi, Mai M. Alzaydi, Thamer Tabbakh and Faisal Al-Otaibi
Biosensors 2024, 14(7), 335; https://doi.org/10.3390/bios14070335 - 9 Jul 2024
Viewed by 2862
Abstract
The non-invasive brain sensing modulation technology field is experiencing rapid development, with new techniques constantly emerging. This study delves into the field of non-invasive brain neuromodulation, a safer and potentially effective approach for treating a spectrum of neurological and psychiatric disorders. Unlike traditional [...] Read more.
The non-invasive brain sensing modulation technology field is experiencing rapid development, with new techniques constantly emerging. This study delves into the field of non-invasive brain neuromodulation, a safer and potentially effective approach for treating a spectrum of neurological and psychiatric disorders. Unlike traditional deep brain stimulation (DBS) surgery, non-invasive techniques employ ultrasound, electrical currents, and electromagnetic field stimulation to stimulate the brain from outside the skull, thereby eliminating surgery risks and enhancing patient comfort. This study explores the mechanisms of various modalities, including transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS), highlighting their potential to address chronic pain, anxiety, Parkinson’s disease, and depression. We also probe into the concept of closed-loop neuromodulation, which personalizes stimulation based on real-time brain activity. While we acknowledge the limitations of current technologies, our study concludes by proposing future research avenues to advance this rapidly evolving field with its immense potential to revolutionize neurological and psychiatric care and lay the foundation for the continuing advancement of innovative non-invasive brain sensing technologies. Full article
(This article belongs to the Special Issue Implantable, Wireless Biosensors and Biodevices for Neuroscience Research)
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25 pages, 1968 KiB  
Review
Current Practice in Using Voltage Imaging to Record Fast Neuronal Activity: Successful Examples from Invertebrate to Mammalian Studies
by Nikolay Aseyev, Violetta Ivanova, Pavel Balaban and Evgeny Nikitin
Biosensors 2023, 13(6), 648; https://doi.org/10.3390/bios13060648 - 13 Jun 2023
Cited by 1 | Viewed by 2972
Abstract
The optical imaging of neuronal activity with potentiometric probes has been credited with being able to address key questions in neuroscience via the simultaneous recording of many neurons. This technique, which was pioneered 50 years ago, has allowed researchers to study the dynamics [...] Read more.
The optical imaging of neuronal activity with potentiometric probes has been credited with being able to address key questions in neuroscience via the simultaneous recording of many neurons. This technique, which was pioneered 50 years ago, has allowed researchers to study the dynamics of neural activity, from tiny subthreshold synaptic events in the axon and dendrites at the subcellular level to the fluctuation of field potentials and how they spread across large areas of the brain. Initially, synthetic voltage-sensitive dyes (VSDs) were applied directly to brain tissue via staining, but recent advances in transgenic methods now allow the expression of genetically encoded voltage indicators (GEVIs), specifically in selected neuron types. However, voltage imaging is technically difficult and limited by several methodological constraints that determine its applicability in a given type of experiment. The prevalence of this method is far from being comparable to patch clamp voltage recording or similar routine methods in neuroscience research. There are more than twice as many studies on VSDs as there are on GEVIs. As can be seen from the majority of the papers, most of them are either methodological ones or reviews. However, potentiometric imaging is able to address key questions in neuroscience by recording most or many neurons simultaneously, thus providing unique information that cannot be obtained via other methods. Different types of optical voltage indicators have their advantages and limitations, which we focus on in detail. Here, we summarize the experience of the scientific community in the application of voltage imaging and try to evaluate the contribution of this method to neuroscience research. Full article
(This article belongs to the Special Issue Implantable, Wireless Biosensors and Biodevices for Neuroscience Research)
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