1
|
Zhao Q, Gribkova E, Shen Y, Cui J, Naughton N, Liu L, Seo J, Tong B, Gazzola M, Gillette R, Zhao H. Highly stretchable and customizable microneedle electrode arrays for intramuscular electromyography. SCIENCE ADVANCES 2024; 10:eadn7202. [PMID: 38691612 PMCID: PMC11062587 DOI: 10.1126/sciadv.adn7202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Accepted: 03/29/2024] [Indexed: 05/03/2024]
Abstract
Stretchable three-dimensional (3D) penetrating microelectrode arrays have potential utility in various fields, including neuroscience, tissue engineering, and wearable bioelectronics. These 3D microelectrode arrays can penetrate and conform to dynamically deforming tissues, thereby facilitating targeted sensing and stimulation of interior regions in a minimally invasive manner. However, fabricating custom stretchable 3D microelectrode arrays presents material integration and patterning challenges. In this study, we present the design, fabrication, and applications of stretchable microneedle electrode arrays (SMNEAs) for sensing local intramuscular electromyography signals ex vivo. We use a unique hybrid fabrication scheme based on laser micromachining, microfabrication, and transfer printing to enable scalable fabrication of individually addressable SMNEA with high device stretchability (60 to 90%). The electrode geometries and recording regions, impedance, array layout, and length distribution are highly customizable. We demonstrate the use of SMNEAs as bioelectronic interfaces in recording intramuscular electromyography from various muscle groups in the buccal mass of Aplysia.
Collapse
Affiliation(s)
- Qinai Zhao
- Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, CA, USA
- Center for Advanced Manufacturing, University of Southern California, Los Angeles, CA, USA
| | - Ekaterina Gribkova
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Yiyang Shen
- Center for Advanced Manufacturing, University of Southern California, Los Angeles, CA, USA
- Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA, USA
| | - Jilai Cui
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Noel Naughton
- Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Liangshu Liu
- Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, CA, USA
- Center for Advanced Manufacturing, University of Southern California, Los Angeles, CA, USA
| | - Jaemin Seo
- Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, CA, USA
- Center for Advanced Manufacturing, University of Southern California, Los Angeles, CA, USA
| | - Baixin Tong
- Center for Advanced Manufacturing, University of Southern California, Los Angeles, CA, USA
- Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA, USA
| | - Mattia Gazzola
- Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Rhanor Gillette
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Hangbo Zhao
- Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, CA, USA
- Center for Advanced Manufacturing, University of Southern California, Los Angeles, CA, USA
- Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
| |
Collapse
|
2
|
Abu Shihada J, Jung M, Decke S, Koschinski L, Musall S, Rincón Montes V, Offenhäusser A. Highly Customizable 3D Microelectrode Arrays for In Vitro and In Vivo Neuronal Tissue Recordings. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2305944. [PMID: 38240370 PMCID: PMC10987114 DOI: 10.1002/advs.202305944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 12/05/2023] [Indexed: 02/16/2024]
Abstract
Planar microelectrode arrays (MEAs) for - in vitro or in vivo - neuronal signal recordings lack the spatial resolution and sufficient signal-to-noise ratio (SNR) required for a detailed understanding of neural network function and synaptic plasticity. To overcome these limitations, a highly customizable three-dimensional (3D) printing process is used in combination with thin film technology and a self-aligned template-assisted electrochemical deposition process to fabricate 3D-printed-based MEAs on stiff or flexible substrates. Devices with design flexibility and physical robustness are shown for recording neural activity in different in vitro and in vivo applications, achieving high-aspect ratio 3D microelectrodes of up to 33:1. Here, MEAs successfully record neural activity in 3D neuronal cultures, retinal explants, and the cortex of living mice, thereby demonstrating the versatility of the 3D MEA while maintaining high-quality neural recordings. Customizable 3D MEAs provide unique opportunities to study neural activity under regular or various pathological conditions, both in vitro and in vivo, and contribute to the development of drug screening and neuromodulation systems that can accurately monitor the activity of large neural networks over time.
Collapse
Affiliation(s)
- J. Abu Shihada
- Institute of Biological Information Processing (IBI‐3) – BioelectronicsForschungszentrum52428JülichGermany
- RWTH Aachen University52062AachenGermany
| | - M. Jung
- Institute of Biological Information Processing (IBI‐3) – BioelectronicsForschungszentrum52428JülichGermany
- RWTH Aachen University52062AachenGermany
| | - S. Decke
- Institute of Biological Information Processing (IBI‐3) – BioelectronicsForschungszentrum52428JülichGermany
| | - L. Koschinski
- Institute of Biological Information Processing (IBI‐3) – BioelectronicsForschungszentrum52428JülichGermany
- RWTH Aachen University52062AachenGermany
- Helmholtz Nano Facility (HNF)Forschungszentrum Jülich52428JülichGermany
| | - S. Musall
- Institute of Biological Information Processing (IBI‐3) – BioelectronicsForschungszentrum52428JülichGermany
- RWTH Aachen University52062AachenGermany
- Faculty of MedicineInstitute of Experimental Epileptology and Cognition ResearchUniversity of Bonn53127BonnGermany
- University Hospital Bonn53127BonnGermany
| | - V. Rincón Montes
- Institute of Biological Information Processing (IBI‐3) – BioelectronicsForschungszentrum52428JülichGermany
| | - A. Offenhäusser
- Institute of Biological Information Processing (IBI‐3) – BioelectronicsForschungszentrum52428JülichGermany
| |
Collapse
|
3
|
Richie J, Letner JG, Mclane-Svoboda A, Huan Y, Ghaffari DH, Valle ED, Patel PR, Chiel HJ, Pelled G, Weiland JD, Chestek CA. Fabrication and Validation of Sub-Cellular Carbon Fiber Electrodes. IEEE Trans Neural Syst Rehabil Eng 2024; 32:739-749. [PMID: 38294928 PMCID: PMC10919889 DOI: 10.1109/tnsre.2024.3360866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Abstract
Multielectrode arrays for interfacing with neurons are of great interest for a wide range of medical applications. However, current electrodes cause damage over time. Ultra small carbon fibers help to address issues but controlling the electrode site geometry is difficult. Here we propose a methodology to create small, pointed fiber electrodes (SPFe). We compare the SPFe to previously made blowtorched fibers in characterization. The SPFe result in small site sizes [Formula: see text] with consistently sharp points (20.8 ± 7.64°). Additionally, these electrodes were able to record and/or stimulate neurons multiple animal models including rat cortex, mouse retina, Aplysia ganglia and octopus axial cord. In rat cortex, these electrodes recorded significantly higher peak amplitudes than the traditional blowtorched fibers. These SPFe may be applicable to a wide range of applications requiring a highly specific interface with individual neurons.
Collapse
|
4
|
De Koninck Y, Alonso J, Bancelin S, Béïque JC, Bélanger E, Bouchard C, Canossa M, Chaniot J, Choquet D, Crochetière MÈ, Cui N, Danglot L, De Koninck P, Devor A, Ducros M, Getz AM, Haouat M, Hernández IC, Jowett N, Keramidis I, Larivière-Loiselle C, Lavoie-Cardinal F, MacGillavry HD, Malkoç A, Mancinelli M, Marquet P, Minderler S, Moreaud M, Nägerl UV, Papanikolopoulou K, Paquet ME, Pavesi L, Perrais D, Sansonetti R, Thunemann M, Vignoli B, Yau J, Zaccaria C. Understanding the nervous system: lessons from Frontiers in Neurophotonics. NEUROPHOTONICS 2024; 11:014415. [PMID: 38545127 PMCID: PMC10972537 DOI: 10.1117/1.nph.11.1.014415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/17/2024]
Abstract
The Frontiers in Neurophotonics Symposium is a biennial event that brings together neurobiologists and physicists/engineers who share interest in the development of leading-edge photonics-based approaches to understand and manipulate the nervous system, from its individual molecular components to complex networks in the intact brain. In this Community paper, we highlight several topics that have been featured at the symposium that took place in October 2022 in Québec City, Canada.
Collapse
Affiliation(s)
- Yves De Koninck
- CERVO Brain Research Centre, Québec City, Québec, Canada
- Laval University, Department of Psychiatry and Neurosciences, Faculty of Medicine, Québec City, Québec, Canada
| | - Johanna Alonso
- CERVO Brain Research Centre, Québec City, Québec, Canada
| | - Stéphane Bancelin
- University of Bordeaux, Interdisciplinary Institute for Neuroscience, National Centre for Scientific Research (CNRS), Bordeaux, France
| | - Jean-Claude Béïque
- University of Ottawa, Brain and Mind Research Institute, Centre of Neural Dynamics, Ottawa, Ontario, Canada
| | - Erik Bélanger
- CERVO Brain Research Centre, Québec City, Québec, Canada
- Laval University, Department of Psychiatry and Neurosciences, Faculty of Medicine, Québec City, Québec, Canada
- Laval University, Département de physique, de génie physique et d’optique, Québec City, Québec, Canada
| | - Catherine Bouchard
- CERVO Brain Research Centre, Québec City, Québec, Canada
- Laval University, Institute Intelligence and Data, Québec City, Québec, Canada
| | - Marco Canossa
- University of Trento, Department of Cellular Computational and Integrative Biology, Trento, Italy
| | - Johan Chaniot
- CERVO Brain Research Centre, Québec City, Québec, Canada
- Laval University, Department of Psychiatry and Neurosciences, Faculty of Medicine, Québec City, Québec, Canada
| | - Daniel Choquet
- University of Bordeaux, Interdisciplinary Institute for Neuroscience, National Centre for Scientific Research (CNRS), Bordeaux, France
- University of Bordeaux, CNRS, Institut national de la santé et de la recherche médicale (INSERM), Bordeaux Imaging Center (BIC), Bordeaux, France
| | | | - Nanke Cui
- Harvard Medical School, Surgical Photonics & Engineering Laboratory, Mass Eye and Ear, Boston, Massachusetts, United States
| | - Lydia Danglot
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris, INSERM U1266, Paris, France
| | - Paul De Koninck
- CERVO Brain Research Centre, Québec City, Québec, Canada
- Laval University, Department of Biochemistry, Microbiology, and Bioinformatics, Faculty of Science and Engineering, Québec City, Québec, Canada
| | - Anna Devor
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
- Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Mathieu Ducros
- University of Bordeaux, CNRS, Institut national de la santé et de la recherche médicale (INSERM), Bordeaux Imaging Center (BIC), Bordeaux, France
| | - Angela M. Getz
- University of Bordeaux, Interdisciplinary Institute for Neuroscience, National Centre for Scientific Research (CNRS), Bordeaux, France
- University of Bordeaux, CNRS, Institut national de la santé et de la recherche médicale (INSERM), Bordeaux Imaging Center (BIC), Bordeaux, France
| | - Mohamed Haouat
- CERVO Brain Research Centre, Québec City, Québec, Canada
- Laval University, Department of Psychiatry and Neurosciences, Faculty of Medicine, Québec City, Québec, Canada
| | - Iván Coto Hernández
- Harvard Medical School, Surgical Photonics & Engineering Laboratory, Mass Eye and Ear, Boston, Massachusetts, United States
| | - Nate Jowett
- Harvard Medical School, Surgical Photonics & Engineering Laboratory, Mass Eye and Ear, Boston, Massachusetts, United States
| | | | - Céline Larivière-Loiselle
- CERVO Brain Research Centre, Québec City, Québec, Canada
- Laval University, Département de physique, de génie physique et d’optique, Québec City, Québec, Canada
| | - Flavie Lavoie-Cardinal
- CERVO Brain Research Centre, Québec City, Québec, Canada
- Laval University, Department of Psychiatry and Neurosciences, Faculty of Medicine, Québec City, Québec, Canada
- Laval University, Institute Intelligence and Data, Québec City, Québec, Canada
| | - Harold D. MacGillavry
- Utrecht University, Faculty of Science, Division of Cell Biology, Neurobiology and Biophysics, Department of Biology, Utrecht, The Netherlands
| | - Asiye Malkoç
- University of Trento, Department of Cellular Computational and Integrative Biology, Trento, Italy
- University of Trento, Department of Physics, Trento, Italy
| | | | - Pierre Marquet
- CERVO Brain Research Centre, Québec City, Québec, Canada
- Laval University, Department of Psychiatry and Neurosciences, Faculty of Medicine, Québec City, Québec, Canada
- Laval University, Centre d’optique, photonique et laser (COPL), Québec City, Québec, Canada
| | - Steven Minderler
- Harvard Medical School, Surgical Photonics & Engineering Laboratory, Mass Eye and Ear, Boston, Massachusetts, United States
| | - Maxime Moreaud
- CERVO Brain Research Centre, Québec City, Québec, Canada
- IFP Energies nouvelles, Solaize, France
| | - U. Valentin Nägerl
- University of Bordeaux, Interdisciplinary Institute for Neuroscience, National Centre for Scientific Research (CNRS), Bordeaux, France
| | - Katerina Papanikolopoulou
- Institute for Fundamental Biomedical Research, Biomedical Sciences Research Center Alexander Fleming, Vari, Greece
| | | | - Lorenzo Pavesi
- University of Trento, Department of Physics, Trento, Italy
| | - David Perrais
- University of Bordeaux, Interdisciplinary Institute for Neuroscience, National Centre for Scientific Research (CNRS), Bordeaux, France
| | | | - Martin Thunemann
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Beatrice Vignoli
- University of Trento, Department of Cellular Computational and Integrative Biology, Trento, Italy
- University of Trento, Department of Physics, Trento, Italy
| | - Jenny Yau
- Harvard Medical School, Surgical Photonics & Engineering Laboratory, Mass Eye and Ear, Boston, Massachusetts, United States
| | - Clara Zaccaria
- University of Trento, Department of Physics, Trento, Italy
| |
Collapse
|
5
|
Jiao Y, Lei M, Zhu J, Chang R, Qu X. Advances in electrode interface materials and modification technologies for brain-computer interfaces. BIOMATERIALS TRANSLATIONAL 2023; 4:213-233. [PMID: 38282708 PMCID: PMC10817795 DOI: 10.12336/biomatertransl.2023.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 11/13/2023] [Accepted: 11/24/2023] [Indexed: 01/30/2024]
Abstract
Recent advances in neuroelectrode interface materials and modification technologies are reviewed. Brain-computer interface is the new method of human-computer interaction, which not only can realise the exchange of information between the human brain and external devices, but also provides a brand-new means for the diagnosis and treatment of brain-related diseases. The neural electrode interface part of brain-computer interface is an important area for electrical, optical and chemical signal transmission between brain tissue system and external electronic devices, which determines the performance of brain-computer interface. In order to solve the problems of insufficient flexibility, insufficient signal recognition ability and insufficient biocompatibility of traditional rigid electrodes, researchers have carried out extensive studies on the neuroelectrode interface in terms of materials and modification techniques. This paper introduces the biological reactions that occur in neuroelectrodes after implantation into brain tissue and the decisive role of the electrode interface for electrode function. Following this, the latest research progress on neuroelectrode materials and interface materials is reviewed from the aspects of neuroelectrode materials and modification technologies, firstly taking materials as a clue, and then focusing on the preparation process of neuroelectrode coatings and the design scheme of functionalised structures.
Collapse
Affiliation(s)
- Yunke Jiao
- Key Laboratory for Ultrafine Materials of Ministry of Education, School of Material Science and Engineering, Frontiers Science Center for Materiobiology and Dynamic Chemistry, East China University of Science and Technology, Shanghai, China
| | - Miao Lei
- Key Laboratory for Ultrafine Materials of Ministry of Education, School of Material Science and Engineering, Frontiers Science Center for Materiobiology and Dynamic Chemistry, East China University of Science and Technology, Shanghai, China
| | - Jianwei Zhu
- Key Laboratory for Ultrafine Materials of Ministry of Education, School of Material Science and Engineering, Frontiers Science Center for Materiobiology and Dynamic Chemistry, East China University of Science and Technology, Shanghai, China
| | - Ronghang Chang
- Key Laboratory for Ultrafine Materials of Ministry of Education, School of Material Science and Engineering, Frontiers Science Center for Materiobiology and Dynamic Chemistry, East China University of Science and Technology, Shanghai, China
| | - Xue Qu
- Key Laboratory for Ultrafine Materials of Ministry of Education, School of Material Science and Engineering, Frontiers Science Center for Materiobiology and Dynamic Chemistry, East China University of Science and Technology, Shanghai, China
- Wenzhou Institute of Shanghai University, Wenzhou, Zhejiang Province, China
- Shanghai Frontier Science Center of Optogenetic Techniques for Cell Metabolism, Shanghai, China
| |
Collapse
|
6
|
Wang J, Wang T, Liu H, Wang K, Moses K, Feng Z, Li P, Huang W. Flexible Electrodes for Brain-Computer Interface System. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2211012. [PMID: 37143288 DOI: 10.1002/adma.202211012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 04/27/2023] [Indexed: 05/06/2023]
Abstract
Brain-computer interface (BCI) has been the subject of extensive research recently. Governments and companies have substantially invested in relevant research and applications. The restoration of communication and motor function, the treatment of psychological disorders, gaming, and other daily and therapeutic applications all benefit from BCI. The electrodes hold the key to the essential, fundamental BCI precondition of electrical brain activity detection and delivery. However, the traditional rigid electrodes are limited due to their mismatch in Young's modulus, potential damages to the human body, and a decline in signal quality with time. These factors make the development of flexible electrodes vital and urgent. Flexible electrodes made of soft materials have grown in popularity in recent years as an alternative to conventional rigid electrodes because they offer greater conformance, the potential for higher signal-to-noise ratio (SNR) signals, and a wider range of applications. Therefore, the latest classifications and future developmental directions of fabricating these flexible electrodes are explored in this paper to further encourage the speedy advent of flexible electrodes for BCI. In summary, the perspectives and future outlook for this developing discipline are provided.
Collapse
Affiliation(s)
- Junjie Wang
- Frontiers Science Center for Flexible Electronics (FSCFE), Xi'an Institute of Flexible Electronics (IFE) & Xi'an Institute of Biomedical Materials and Engineering (IBME), Northwestern Polytechnical University (NPU), 127 West Youyi Road, Xi'an, Shaanxi, 710072, P. R. China
| | - Tengjiao Wang
- Frontiers Science Center for Flexible Electronics (FSCFE), Xi'an Institute of Flexible Electronics (IFE) & Xi'an Institute of Biomedical Materials and Engineering (IBME), Northwestern Polytechnical University (NPU), 127 West Youyi Road, Xi'an, Shaanxi, 710072, P. R. China
| | - Haoyan Liu
- Department of Computer Science & Computer Engineering (CSCE), University of Arkansas, Fayetteville, AR, 72701, USA
| | - Kun Wang
- Frontiers Science Center for Flexible Electronics (FSCFE), Xi'an Institute of Flexible Electronics (IFE) & Xi'an Institute of Biomedical Materials and Engineering (IBME), Northwestern Polytechnical University (NPU), 127 West Youyi Road, Xi'an, Shaanxi, 710072, P. R. China
| | - Kumi Moses
- Frontiers Science Center for Flexible Electronics (FSCFE), Xi'an Institute of Flexible Electronics (IFE) & Xi'an Institute of Biomedical Materials and Engineering (IBME), Northwestern Polytechnical University (NPU), 127 West Youyi Road, Xi'an, Shaanxi, 710072, P. R. China
| | - Zhuoya Feng
- Frontiers Science Center for Flexible Electronics (FSCFE), Xi'an Institute of Flexible Electronics (IFE) & Xi'an Institute of Biomedical Materials and Engineering (IBME), Northwestern Polytechnical University (NPU), 127 West Youyi Road, Xi'an, Shaanxi, 710072, P. R. China
| | - Peng Li
- Frontiers Science Center for Flexible Electronics (FSCFE), Xi'an Institute of Flexible Electronics (IFE) & Xi'an Institute of Biomedical Materials and Engineering (IBME), Northwestern Polytechnical University (NPU), 127 West Youyi Road, Xi'an, Shaanxi, 710072, P. R. China
| | - Wei Huang
- Frontiers Science Center for Flexible Electronics (FSCFE), Xi'an Institute of Flexible Electronics (IFE) & Xi'an Institute of Biomedical Materials and Engineering (IBME), Northwestern Polytechnical University (NPU), 127 West Youyi Road, Xi'an, Shaanxi, 710072, P. R. China
| |
Collapse
|
7
|
Qin Y, Zhang Y, Zhang Y, Liu S, Guo X. Application and Development of EEG Acquisition and Feedback Technology: A Review. BIOSENSORS 2023; 13:930. [PMID: 37887123 PMCID: PMC10605290 DOI: 10.3390/bios13100930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 10/05/2023] [Accepted: 10/16/2023] [Indexed: 10/28/2023]
Abstract
This review focuses on electroencephalogram (EEG) acquisition and feedback technology and its core elements, including the composition and principles of the acquisition devices, a wide range of applications, and commonly used EEG signal classification algorithms. First, we describe the construction of EEG acquisition and feedback devices encompassing EEG electrodes, signal processing, and control and feedback systems, which collaborate to measure faint EEG signals from the scalp, convert them into interpretable data, and accomplish practical applications using control feedback systems. Subsequently, we examine the diverse applications of EEG acquisition and feedback across various domains. In the medical field, EEG signals are employed for epilepsy diagnosis, brain injury monitoring, and sleep disorder research. EEG acquisition has revealed associations between brain functionality, cognition, and emotions, providing essential insights for psychologists and neuroscientists. Brain-computer interface technology utilizes EEG signals for human-computer interaction, driving innovation in the medical, engineering, and rehabilitation domains. Finally, we introduce commonly used EEG signal classification algorithms. These classification tasks can identify different cognitive states, emotional states, brain disorders, and brain-computer interface control and promote further development and application of EEG technology. In conclusion, EEG acquisition technology can deepen the understanding of EEG signals while simultaneously promoting developments across multiple domains, such as medicine, science, and engineering.
Collapse
Affiliation(s)
- Yong Qin
- Institute of Advanced Structure Technology, Beijing Institute of Technology, Beijing 100081, China;
| | - Yanpeng Zhang
- Beijing Perfect-Protection Technology Co., Ltd., Beijing 101601, China; (Y.Z.); (Y.Z.); (S.L.)
| | - Yan Zhang
- Beijing Perfect-Protection Technology Co., Ltd., Beijing 101601, China; (Y.Z.); (Y.Z.); (S.L.)
| | - Sheng Liu
- Beijing Perfect-Protection Technology Co., Ltd., Beijing 101601, China; (Y.Z.); (Y.Z.); (S.L.)
| | - Xiaogang Guo
- Institute of Advanced Structure Technology, Beijing Institute of Technology, Beijing 100081, China;
| |
Collapse
|
8
|
Khatib M, Zhao ET, Wei S, Abramson A, Bishop ES, Chen CH, Thomas AL, Xu C, Park J, Lee Y, Hamnett R, Yu W, Root SE, Yuan L, Chakhtoura D, Kim KK, Zhong D, Nishio Y, Zhao C, Wu C, Jiang Y, Zhang A, Li J, Wang W, Salimi-Jazi F, Rafeeqi TA, Hemed NM, Tok JBH, Chen X, Kaltschmidt JA, Dunn JC, Bao Z. Spiral NeuroString: High-Density Soft Bioelectronic Fibers for Multimodal Sensing and Stimulation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.02.560482. [PMID: 37873341 PMCID: PMC10592902 DOI: 10.1101/2023.10.02.560482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Bioelectronic fibers hold promise for both research and clinical applications due to their compactness, ease of implantation, and ability to incorporate various functionalities such as sensing and stimulation. However, existing devices suffer from bulkiness, rigidity, limited functionality, and low density of active components. These limitations stem from the difficulty to incorporate many components on one-dimensional (1D) fiber devices due to the incompatibility of conventional microfabrication methods (e.g., photolithography) with curved, thin and long fiber structures. Herein, we introduce a fabrication approach, ‶spiral transformation″, to convert two-dimensional (2D) films containing microfabricated devices into 1D soft fibers. This approach allows for the creation of high density multimodal soft bioelectronic fibers, termed Spiral NeuroString (S-NeuroString), while enabling precise control over the longitudinal, angular, and radial positioning and distribution of the functional components. We show the utility of S-NeuroString for motility mapping, serotonin sensing, and tissue stimulation within the dynamic and soft gastrointestinal (GI) system, as well as for single-unit recordings in the brain. The described bioelectronic fibers hold great promises for next-generation multifunctional implantable electronics.
Collapse
Affiliation(s)
- Muhammad Khatib
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Eric Tianjiao Zhao
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Shiyuan Wei
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Alex Abramson
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Division of Digestive Diseases, Emory University School of Medicine, Atlanta, GA 30332, USA
| | - Estelle Spear Bishop
- Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, California, USA
| | - Chih-Hsin Chen
- Department of Surgery/Pediatric Surgery, Stanford University, Stanford, CA, USA
| | - Anne-Laure Thomas
- Department of Surgery/Pediatric Surgery, Stanford University, Stanford, CA, USA
| | - Chengyi Xu
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Jaeho Park
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Yeongjun Lee
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Ryan Hamnett
- Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, 94305, USA
| | - Weilai Yu
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Samuel E. Root
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Lei Yuan
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Dorine Chakhtoura
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Kyun Kyu Kim
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Donglai Zhong
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Yuya Nishio
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Chuanzhen Zhao
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Can Wu
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Yuanwen Jiang
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Anqi Zhang
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Jinxing Li
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
- Department of Biomedical Engineering and Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI 48823, USA
| | - Weichen Wang
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | | | - Talha A. Rafeeqi
- Department of Surgery/Pediatric Surgery, Stanford University, Stanford, CA, USA
| | - Nofar Mintz Hemed
- Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, United States
| | - Jeffrey B.-H. Tok
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Xiaoke Chen
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Julia A. Kaltschmidt
- Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, 94305, USA
| | - James C.Y. Dunn
- Department of Surgery/Pediatric Surgery, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Zhenan Bao
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
| |
Collapse
|
9
|
Luan L, Yin R, Zhu H, Xie C. Emerging Penetrating Neural Electrodes: In Pursuit of Large Scale and Longevity. Annu Rev Biomed Eng 2023; 25:185-205. [PMID: 37289556 PMCID: PMC11078330 DOI: 10.1146/annurev-bioeng-090622-050507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Penetrating neural electrodes provide a powerful approach to decipher brain circuitry by allowing for time-resolved electrical detections of individual action potentials. This unique capability has contributed tremendously to basic and translational neuroscience, enabling both fundamental understandings of brain functions and applications of human prosthetic devices that restore crucial sensations and movements. However, conventional approaches are limited by the scarce number of available sensing channels and compromised efficacy over long-term implantations. Recording longevity and scalability have become the most sought-after improvements in emerging technologies. In this review, we discuss the technological advances in the past 5-10 years that have enabled larger-scale, more detailed, and longer-lasting recordings of neural circuits at work than ever before. We present snapshots of the latest advances in penetration electrode technology, showcase their applications in animal models and humans, and outline the underlying design principles and considerations to fuel future technological development.
Collapse
Affiliation(s)
- Lan Luan
- Department of Electrical and Computer Engineering, Rice University, Houston, Texas, USA;
- Rice Neuroengineering Initiative, Rice University, Houston, Texas, USA
- Department of Bioengineering, Rice University, Houston, Texas, USA
| | - Rongkang Yin
- Department of Electrical and Computer Engineering, Rice University, Houston, Texas, USA;
- Rice Neuroengineering Initiative, Rice University, Houston, Texas, USA
| | - Hanlin Zhu
- Department of Electrical and Computer Engineering, Rice University, Houston, Texas, USA;
- Rice Neuroengineering Initiative, Rice University, Houston, Texas, USA
| | - Chong Xie
- Department of Electrical and Computer Engineering, Rice University, Houston, Texas, USA;
- Rice Neuroengineering Initiative, Rice University, Houston, Texas, USA
- Department of Bioengineering, Rice University, Houston, Texas, USA
| |
Collapse
|
10
|
Chen X, Gong Y, Chen W. Advanced Temporally-Spatially Precise Technologies for On-Demand Neurological Disorder Intervention. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2207436. [PMID: 36929323 PMCID: PMC10190591 DOI: 10.1002/advs.202207436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 02/18/2023] [Indexed: 05/18/2023]
Abstract
Temporal-spatial precision has attracted increasing attention for the clinical intervention of neurological disorders (NDs) to mitigate adverse effects of traditional treatments and achieve point-of-care medicine. Inspiring steps forward in this field have been witnessed in recent years, giving the credit to multi-discipline efforts from neurobiology, bioengineering, chemical materials, artificial intelligence, and so on, exhibiting valuable clinical translation potential. In this review, the latest progress in advanced temporally-spatially precise clinical intervention is highlighted, including localized parenchyma drug delivery, precise neuromodulation, as well as biological signal detection to trigger closed-loop control. Their clinical potential in both central and peripheral nervous systems is illustrated meticulously related to typical diseases. The challenges relative to biosafety and scaled production as well as their future perspectives are also discussed in detail. Notably, these intelligent temporally-spatially precision intervention systems could lead the frontier in the near future, demonstrating significant clinical value to support billions of patients plagued with NDs.
Collapse
Affiliation(s)
- Xiuli Chen
- Department of Pharmacology, School of Basic MedicineTongji Medical CollegeHuazhong University of Science and Technology430030WuhanChina
- Hubei Key Laboratory of Drug Target Research and Pharmacodynamic EvaluationHuazhong University of Science and Technology430030WuhanChina
| | - Yusheng Gong
- Department of Pharmacology, School of Basic MedicineTongji Medical CollegeHuazhong University of Science and Technology430030WuhanChina
- Hubei Key Laboratory of Drug Target Research and Pharmacodynamic EvaluationHuazhong University of Science and Technology430030WuhanChina
| | - Wei Chen
- Department of Pharmacology, School of Basic MedicineTongji Medical CollegeHuazhong University of Science and Technology430030WuhanChina
- Hubei Key Laboratory of Drug Target Research and Pharmacodynamic EvaluationHuazhong University of Science and Technology430030WuhanChina
| |
Collapse
|
11
|
Luo Y, Abidian MR, Ahn JH, Akinwande D, Andrews AM, Antonietti M, Bao Z, Berggren M, Berkey CA, Bettinger CJ, Chen J, Chen P, Cheng W, Cheng X, Choi SJ, Chortos A, Dagdeviren C, Dauskardt RH, Di CA, Dickey MD, Duan X, Facchetti A, Fan Z, Fang Y, Feng J, Feng X, Gao H, Gao W, Gong X, Guo CF, Guo X, Hartel MC, He Z, Ho JS, Hu Y, Huang Q, Huang Y, Huo F, Hussain MM, Javey A, Jeong U, Jiang C, Jiang X, Kang J, Karnaushenko D, Khademhosseini A, Kim DH, Kim ID, Kireev D, Kong L, Lee C, Lee NE, Lee PS, Lee TW, Li F, Li J, Liang C, Lim CT, Lin Y, Lipomi DJ, Liu J, Liu K, Liu N, Liu R, Liu Y, Liu Y, Liu Z, Liu Z, Loh XJ, Lu N, Lv Z, Magdassi S, Malliaras GG, Matsuhisa N, Nathan A, Niu S, Pan J, Pang C, Pei Q, Peng H, Qi D, Ren H, Rogers JA, Rowe A, Schmidt OG, Sekitani T, Seo DG, Shen G, Sheng X, Shi Q, Someya T, Song Y, Stavrinidou E, Su M, Sun X, Takei K, Tao XM, Tee BCK, Thean AVY, Trung TQ, Wan C, Wang H, Wang J, Wang M, Wang S, Wang T, Wang ZL, Weiss PS, Wen H, Xu S, Xu T, Yan H, Yan X, Yang H, Yang L, Yang S, Yin L, Yu C, Yu G, Yu J, Yu SH, Yu X, Zamburg E, Zhang H, Zhang X, Zhang X, Zhang X, Zhang Y, Zhang Y, Zhao S, Zhao X, Zheng Y, Zheng YQ, Zheng Z, Zhou T, Zhu B, Zhu M, Zhu R, Zhu Y, Zhu Y, Zou G, Chen X. Technology Roadmap for Flexible Sensors. ACS NANO 2023; 17:5211-5295. [PMID: 36892156 PMCID: PMC11223676 DOI: 10.1021/acsnano.2c12606] [Citation(s) in RCA: 171] [Impact Index Per Article: 171.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.
Collapse
Affiliation(s)
- Yifei Luo
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, #08-03 Innovis, Singapore 138634, Republic of Singapore
- Innovative Centre for Flexible Devices (iFLEX), School of Materials Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore
| | - Mohammad Reza Abidian
- Department of Biomedical Engineering, University of Houston, Houston, Texas 77024, United States
| | - Jong-Hyun Ahn
- School of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Republic of Korea
| | - Deji Akinwande
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
- Microelectronics Research Center, The University of Texas at Austin, Austin, Texas 78758, United States
| | - Anne M Andrews
- Department of Chemistry and Biochemistry, California NanoSystems Institute, and Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, and Hatos Center for Neuropharmacology, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Markus Antonietti
- Colloid Chemistry Department, Max Planck Institute of Colloids and Interfaces, 14476 Potsdam, Germany
| | - Zhenan Bao
- Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States
| | - Magnus Berggren
- Laboratory of Organic Electronics, Department of Science and Technology, Campus Norrköping, Linköping University, 83 Linköping, Sweden
- Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC), SE-100 44 Stockholm, Sweden
| | - Christopher A Berkey
- Department of Materials Science and Engineering, Stanford University, Stanford, California 94301, United States
| | - Christopher John Bettinger
- Department of Biomedical Engineering and Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States
| | - Jun Chen
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Peng Chen
- School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore 637457, Singapore
| | - Wenlong Cheng
- Nanobionics Group, Department of Chemical and Biological Engineering, Monash University, Clayton, Australia, 3800
- Monash Institute of Medical Engineering, Monash University, Clayton, Australia3800
| | - Xu Cheng
- Applied Mechanics Laboratory, Department of Engineering Mechanics, Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, PR China
| | - Seon-Jin Choi
- Division of Materials of Science and Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, Republic of Korea
| | - Alex Chortos
- School of Mechanical Engineering, Purdue University, West Lafayette, Indiana 47906, United States
| | - Canan Dagdeviren
- Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Reinhold H Dauskardt
- Department of Materials Science and Engineering, Stanford University, Stanford, California 94301, United States
| | - Chong-An Di
- Beijing National Laboratory for Molecular Sciences, CAS Key Laboratory of Organic Solids, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Michael D Dickey
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27606, United States
| | - Xiangfeng Duan
- Department of Chemistry and Biochemistry, California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Antonio Facchetti
- Department of Chemistry and the Materials Research Center, Northwestern University, Evanston, Illinois 60208, United States
| | - Zhiyong Fan
- Department of Electronic and Computer Engineering and Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China
| | - Yin Fang
- School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore 637457, Singapore
| | - Jianyou Feng
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, PR China
| | - Xue Feng
- Laboratory of Flexible Electronics Technology, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China
| | - Huajian Gao
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore
- Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Republic of Singapore
| | - Wei Gao
- Andrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, California, 91125, United States
| | - Xiwen Gong
- Department of Chemical Engineering, Department of Materials Science and Engineering, Department of Electrical Engineering and Computer Science, Applied Physics Program, and Macromolecular Science and Engineering Program, University of Michigan, Ann Arbor, Michigan, 48109 United States
| | - Chuan Fei Guo
- Department of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Xiaojun Guo
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Martin C Hartel
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Zihan He
- Beijing National Laboratory for Molecular Sciences, CAS Key Laboratory of Organic Solids, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - John S Ho
- Institute for Health Innovation and Technology, National University of Singapore, Singapore 117599, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore
- The N.1 Institute for Health, National University of Singapore, Singapore 117456, Singapore
| | - Youfan Hu
- School of Electronics and Center for Carbon-Based Electronics, Peking University, Beijing 100871, China
| | - Qiyao Huang
- School of Fashion and Textiles, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China
| | - Yu Huang
- Department of Materials Science and Engineering, California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Fengwei Huo
- Key Laboratory of Flexible Electronics (KLOFE) and Institute of Advanced Materials (IAM), Nanjing Tech University (NanjingTech), 30 South Puzhu Road, Nanjing 211816, PR China
| | - Muhammad M Hussain
- mmh Labs, Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47906, United States
| | - Ali Javey
- Electrical Engineering and Computer Sciences, University of California, Berkeley, California 94720, United States
- Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Unyong Jeong
- Department of Materials Science and Engineering, Pohang University of Science and Engineering (POSTECH), Pohang, Gyeong-buk 37673, Korea
| | - Chen Jiang
- Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
| | - Xingyu Jiang
- Department of Biomedical Engineering, Southern University of Science and Technology, No 1088, Xueyuan Road, Xili, Nanshan District, Shenzhen, Guangdong 518055, PR China
| | - Jiheong Kang
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Daniil Karnaushenko
- Research Center for Materials, Architectures and Integration of Nanomembranes (MAIN), Chemnitz University of Technology, Chemnitz 09126, Germany
| | | | - Dae-Hyeong Kim
- Center for Nanoparticle Research, Institute for Basic Science (IBS), School of Chemical and Biological Engineering, Seoul National University, Seoul 08826, Republic of Korea
| | - Il-Doo Kim
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
| | - Dmitry Kireev
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
- Microelectronics Research Center, The University of Texas at Austin, Austin, Texas 78758, United States
| | - Lingxuan Kong
- School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore 637457, Singapore
| | - Chengkuo Lee
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore
- Center for Intelligent Sensors and MEMS (CISM), National University of Singapore, Singapore 117608, Singapore
- National University of Singapore Suzhou Research Institute (NUSRI), Suzhou Industrial Park, Suzhou 215123, China
- NUS Graduate School-Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore 119077, Singapore
| | - Nae-Eung Lee
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon, Kyunggi-do 16419, Republic of Korea
| | - Pooi See Lee
- School of Materials Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore
- Singapore-HUJ Alliance for Research and Enterprise (SHARE), Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Tae-Woo Lee
- Department of Materials Science and Engineering, Seoul National University, Seoul 08826, Republic of Korea
- School of Chemical and Biological Engineering, Seoul National University, Seoul 08826, Republic of Korea
- Institute of Engineering Research, Research Institute of Advanced Materials, Seoul National University, Soft Foundry, Seoul 08826, Republic of Korea
- Interdisciplinary Program in Bioengineering, Seoul National University, Seoul 08826, Republic of Korea
| | - Fengyu Li
- College of Chemistry and Materials Science, Jinan University, Guangzhou, Guangdong 510632, China
| | - Jinxing Li
- Department of Biomedical Engineering, Department of Electrical and Computer Engineering, Neuroscience Program, BioMolecular Science Program, and Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, Michigan 48823, United States
| | - Cuiyuan Liang
- School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Chwee Teck Lim
- Department of Biomedical Engineering, National University of Singapore, Singapore 117583, Singapore
- Mechanobiology Institute, National University of Singapore, Singapore 117411, Singapore
- Institute for Health Innovation and Technology, National University of Singapore, Singapore 119276, Singapore
| | - Yuanjing Lin
- School of Microelectronics, Southern University of Science and Technology, Shenzhen 518055, China
| | - Darren J Lipomi
- Department of Nano and Chemical Engineering, University of California, San Diego, La Jolla, California 92093-0448, United States
| | - Jia Liu
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, Massachusetts, 02134, United States
| | - Kai Liu
- School of Chemistry and Chemical Engineering, Frontiers Science Center for Transformative Molecules, Shanghai Jiao Tong University, Shanghai 200240, PR China
| | - Nan Liu
- Beijing Key Laboratory of Energy Conversion and Storage Materials, College of Chemistry, Beijing Normal University, Beijing 100875, PR China
| | - Ren Liu
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, Massachusetts, 02134, United States
| | - Yuxin Liu
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, #08-03 Innovis, Singapore 138634, Republic of Singapore
- Department of Biomedical Engineering, N.1 Institute for Health, Institute for Health Innovation and Technology (iHealthtech), National University of Singapore, Singapore 119077, Singapore
| | - Yuxuan Liu
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Zhiyuan Liu
- Neural Engineering Centre, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China 518055
| | - Zhuangjian Liu
- Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Republic of Singapore
| | - Xian Jun Loh
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, #08-03 Innovis, Singapore 138634, Republic of Singapore
| | - Nanshu Lu
- Department of Aerospace Engineering and Engineering Mechanics, Department of Electrical and Computer Engineering, Department of Mechanical Engineering, Department of Biomedical Engineering, Texas Materials Institute, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Zhisheng Lv
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, #08-03 Innovis, Singapore 138634, Republic of Singapore
| | - Shlomo Magdassi
- Institute of Chemistry and the Center for Nanoscience and Nanotechnology, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - George G Malliaras
- Electrical Engineering Division, Department of Engineering, University of Cambridge CB3 0FA, Cambridge United Kingdom
| | - Naoji Matsuhisa
- Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
| | - Arokia Nathan
- Darwin College, University of Cambridge, Cambridge CB3 9EU, United Kingdom
| | - Simiao Niu
- Department of Biomedical Engineering, Rutgers University, Piscataway, New Jersey 08854, United States
| | - Jieming Pan
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore
| | - Changhyun Pang
- School of Chemical Engineering and Samsung Advanced Institute for Health Science and Technology, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Qibing Pei
- Department of Materials Science and Engineering, Department of Mechanical and Aerospace Engineering, California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Huisheng Peng
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, PR China
| | - Dianpeng Qi
- School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Huaying Ren
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, California, 90095, United States
| | - John A Rogers
- Querrey Simpson Institute for Bioelectronics, Northwestern University, Evanston, Illinois 60208, United States
- Department of Materials Science and Engineering, Department of Mechanical Engineering, Department of Biomedical Engineering, Departments of Electrical and Computer Engineering and Chemistry, and Department of Neurological Surgery, Northwestern University, Evanston, Illinois 60208, United States
| | - Aaron Rowe
- Becton, Dickinson and Company, 1268 N. Lakeview Avenue, Anaheim, California 92807, United States
- Ready, Set, Food! 15821 Ventura Blvd #450, Encino, California 91436, United States
| | - Oliver G Schmidt
- Research Center for Materials, Architectures and Integration of Nanomembranes (MAIN), Chemnitz University of Technology, Chemnitz 09126, Germany
- Material Systems for Nanoelectronics, Chemnitz University of Technology, Chemnitz 09107, Germany
- Nanophysics, Faculty of Physics, TU Dresden, Dresden 01062, Germany
| | - Tsuyoshi Sekitani
- The Institute of Scientific and Industrial Research (SANKEN), Osaka University, Osaka, Japan 5670047
| | - Dae-Gyo Seo
- Department of Materials Science and Engineering, Seoul National University, Seoul 08826, Republic of Korea
| | - Guozhen Shen
- School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing 100081, China
| | - Xing Sheng
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Institute for Precision Medicine, Center for Flexible Electronics Technology, and IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, 100084, China
| | - Qiongfeng Shi
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore
- Center for Intelligent Sensors and MEMS (CISM), National University of Singapore, Singapore 117608, Singapore
- National University of Singapore Suzhou Research Institute (NUSRI), Suzhou Industrial Park, Suzhou 215123, China
| | - Takao Someya
- Department of Electrical Engineering and Information Systems, Graduate School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan
| | - Yanlin Song
- Key Laboratory of Green Printing, Institute of Chemistry, Chinese Academy of Sciences, Beijing, Beijing 100190, China
| | - Eleni Stavrinidou
- Laboratory of Organic Electronics, Department of Science and Technology, Linköping University, SE-601 74 Norrkoping, Sweden
| | - Meng Su
- Key Laboratory of Green Printing, Institute of Chemistry, Chinese Academy of Sciences, Beijing, Beijing 100190, China
| | - Xuemei Sun
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, and Laboratory of Advanced Materials, Fudan University, Shanghai 200438, PR China
| | - Kuniharu Takei
- Department of Physics and Electronics, Osaka Metropolitan University, Sakai, Osaka 599-8531, Japan
| | - Xiao-Ming Tao
- Research Institute for Intelligent Wearable Systems, School of Fashion and Textiles, Hong Kong Polytechnic University, Hong Kong, China
| | - Benjamin C K Tee
- Materials Science and Engineering, National University of Singapore, Singapore 117575, Singapore
- iHealthtech, National University of Singapore, Singapore 119276, Singapore
| | - Aaron Voon-Yew Thean
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore
- Singapore Hybrid-Integrated Next-Generation μ-Electronics Centre (SHINE), Singapore 117583, Singapore
| | - Tran Quang Trung
- School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon, Kyunggi-do 16419, Republic of Korea
| | - Changjin Wan
- School of Electronic Science and Engineering, Nanjing University, Nanjing 210023, China
| | - Huiliang Wang
- Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas 78712, United States
| | - Joseph Wang
- Department of Nanoengineering, University of California, San Diego, California 92093, United States
| | - Ming Wang
- Frontier Institute of Chip and System, State Key Laboratory of Integrated Chip and Systems, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, 200433, China
- the Shanghai Qi Zhi Institute, 41th Floor, AI Tower, No.701 Yunjin Road, Xuhui District, Shanghai 200232, China
| | - Sihong Wang
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois, 60637, United States
| | - Ting Wang
- State Key Laboratory of Organic Electronics and Information Displays and Jiangsu Key Laboratory for Biosensors, Institute of Advanced Materials (IAM), Nanjing University of Posts and Telecommunications, 9 Wenyuan Road, Nanjing 210023, China
| | - Zhong Lin Wang
- Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 100083, China
- Georgia Institute of Technology, Atlanta, Georgia 30332-0245, United States
| | - Paul S Weiss
- California NanoSystems Institute, Department of Chemistry and Biochemistry, Department of Bioengineering, and Department of Materials Science and Engineering, University of California, Los Angeles, Los Angeles, California 90095, United States
| | - Hanqi Wen
- School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore 637457, Singapore
- Institute of Flexible Electronics Technology of THU, Jiaxing, Zhejiang, China 314000
| | - Sheng Xu
- Department of Nanoengineering, Department of Electrical and Computer Engineering, Materials Science and Engineering Program, and Department of Bioengineering, University of California San Diego, La Jolla, California, 92093, United States
| | - Tailin Xu
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong, 518060, PR China
| | - Hongping Yan
- Department of Chemical Engineering, Stanford University, Stanford, California 94305, United States
| | - Xuzhou Yan
- School of Chemistry and Chemical Engineering, Frontiers Science Center for Transformative Molecules, Shanghai Jiao Tong University, Shanghai 200240, PR China
| | - Hui Yang
- Tianjin Key Laboratory of Molecular Optoelectronic Sciences, Department of Chemistry, School of Science, Tianjin University, Tianjin, China, 300072
| | - Le Yang
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, #08-03 Innovis, Singapore 138634, Republic of Singapore
- Department of Materials Science and Engineering, National University of Singapore (NUS), 9 Engineering Drive 1, #03-09 EA, Singapore 117575, Singapore
| | - Shuaijian Yang
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, United Kingdom
| | - Lan Yin
- School of Materials Science and Engineering, The Key Laboratory of Advanced Materials of Ministry of Education, State Key Laboratory of New Ceramics and Fine Processing, and Center for Flexible Electronics Technology, Tsinghua University, Beijing, 100084, China
| | - Cunjiang Yu
- Department of Engineering Science and Mechanics, Department of Biomedical Engineering, Department of Material Science and Engineering, Materials Research Institute, Pennsylvania State University, University Park, Pennsylvania, 16802, United States
| | - Guihua Yu
- Materials Science and Engineering Program and Walker Department of Mechanical Engineering, The University of Texas at Austin, Austin, Texas, 78712, United States
| | - Jing Yu
- School of Materials Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore
| | - Shu-Hong Yu
- Department of Chemistry, Institute of Biomimetic Materials and Chemistry, Hefei National Research Center for Physical Science at the Microscale, University of Science and Technology of China, Hefei 230026, China
| | - Xinge Yu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Evgeny Zamburg
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore
- Singapore Hybrid-Integrated Next-Generation μ-Electronics Centre (SHINE), Singapore 117583, Singapore
| | - Haixia Zhang
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication; Beijing Advanced Innovation Center for Integrated Circuits, School of Integrated Circuits, Peking University, Beijing 100871, China
| | - Xiangyu Zhang
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore
- Singapore Hybrid-Integrated Next-Generation μ-Electronics Centre (SHINE), Singapore 117583, Singapore
| | - Xiaosheng Zhang
- School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Xueji Zhang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong 518060, PR China
| | - Yihui Zhang
- Applied Mechanics Laboratory, Department of Engineering Mechanics; Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, PR China
| | - Yu Zhang
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore
- Singapore Hybrid-Integrated Next-Generation μ-Electronics Centre (SHINE), Singapore 117583, Singapore
| | - Siyuan Zhao
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, Massachusetts, 02134, United States
| | - Xuanhe Zhao
- Department of Mechanical Engineering, Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139, United States
| | - Yuanjin Zheng
- Center for Integrated Circuits and Systems, School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
| | - Yu-Qing Zheng
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication; School of Integrated Circuits, Peking University, Beijing 100871, China
| | - Zijian Zheng
- Department of Applied Biology and Chemical Technology, Faculty of Science, Research Institute for Intelligent Wearable Systems, Research Institute for Smart Energy, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China
| | - Tao Zhou
- Center for Neural Engineering, Department of Engineering Science and Mechanics, The Huck Institutes of the Life Sciences, Materials Research Institute, The Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Bowen Zhu
- Key Laboratory of 3D Micro/Nano Fabrication and Characterization of Zhejiang Province, School of Engineering, Westlake University, Hangzhou 310024, China
| | - Ming Zhu
- Institute for Digital Molecular Analytics and Science (IDMxS), Nanyang Technological University, 59 Nanyang Drive, Singapore 636921, Singapore
| | - Rong Zhu
- Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Yangzhi Zhu
- Terasaki Institute for Biomedical Innovation, Los Angeles, California, 90064, United States
| | - Yong Zhu
- Department of Mechanical and Aerospace Engineering, Department of Materials Science and Engineering, and Department of Biomedical Engineering, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Guijin Zou
- Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632, Republic of Singapore
| | - Xiaodong Chen
- Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), 2 Fusionopolis Way, #08-03 Innovis, Singapore 138634, Republic of Singapore
- Innovative Center for Flexible Devices (iFLEX), Max Planck-NTU Joint Laboratory for Artificial Senses, School of Materials Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore
| |
Collapse
|
12
|
Cortelli G, Grob L, Patruno L, Cramer T, Mayer D, Fraboni B, Wolfrum B, de Miranda S. Determination of Stiffness and the Elastic Modulus of 3D-Printed Micropillars with Atomic Force Microscopy-Force Spectroscopy. ACS APPLIED MATERIALS & INTERFACES 2023; 15:7602-7609. [PMID: 36706051 PMCID: PMC9923676 DOI: 10.1021/acsami.2c21921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 01/17/2023] [Indexed: 06/18/2023]
Abstract
Nowadays, many applications in diverse fields are taking advantage of micropillars such as optics, tribology, biology, and biomedical engineering. Among them, one of the most attractive is three-dimensional microelectrode arrays for in vivo and in vitro studies, such as cellular recording, biosensors, and drug delivery. Depending on the application, the micropillar's optimal mechanical response ranges from soft to stiff. For long-term implantable devices, a mechanical mismatch between the micropillars and the biological tissue must be avoided. For drug delivery patches, micropillars must penetrate the skin without breaking or bending. The accurate mechanical characterization of the micropillar is pivotal in the fabrication and optimization of such devices, as it determines whether the device will fail or not. In this work, we demonstrate an experimental method based only on atomic force microscopy-force spectroscopy that allows us to measure the stiffness of a micropillar and the elastic modulus of its constituent material. We test our method with four different types of 3D inkjet-printed micropillars: silver micropillars sintered at 100 and 150 °C and polyacrylate microstructures with and without a metallic coating. The estimated elastic moduli are found to be comparable with the corresponding bulk values. Furthermore, our findings show that neither the sintering temperature nor the presence of a thin metal coating plays a major role in defining the mechanical properties of the micropillar.
Collapse
Affiliation(s)
- Giorgio Cortelli
- Department
of Civil, Chemical, Environmental and Materials Engineering, University of Bologna, Viale del Risorgimento 2, 40136 Bologna, Italy
| | - Leroy Grob
- Neuroelectronics,
Munich Institute of Biomedical Engineering, Department of Electrical
Engineering, Technical University of Munich, 85748 Garching, Germany
| | - Luca Patruno
- Department
of Civil, Chemical, Environmental and Materials Engineering, University of Bologna, Viale del Risorgimento 2, 40136 Bologna, Italy
| | - Tobias Cramer
- Department
of Physics and Astronomy, University of
Bologna, Viale Berti
Pichat 6/2, 40127 Bologna, Italy
| | - Dirk Mayer
- Institute
of Biological Information Processing (IBI-3), Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
| | - Beatrice Fraboni
- Department
of Physics and Astronomy, University of
Bologna, Viale Berti
Pichat 6/2, 40127 Bologna, Italy
| | - Bernhard Wolfrum
- Neuroelectronics,
Munich Institute of Biomedical Engineering, Department of Electrical
Engineering, Technical University of Munich, 85748 Garching, Germany
| | - Stefano de Miranda
- Department
of Civil, Chemical, Environmental and Materials Engineering, University of Bologna, Viale del Risorgimento 2, 40136 Bologna, Italy
| |
Collapse
|
13
|
Ghosh A, Nag S, Gomes A, Gosavi A, Ghule G, Kundu A, Purohit B, Srivastava R. Applications of Smart Material Sensors and Soft Electronics in Healthcare Wearables for Better User Compliance. MICROMACHINES 2022; 14:121. [PMID: 36677182 PMCID: PMC9862021 DOI: 10.3390/mi14010121] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/25/2022] [Accepted: 12/27/2022] [Indexed: 06/17/2023]
Abstract
The need for innovation in the healthcare sector is essential to meet the demand of a rapidly growing population and the advent of progressive chronic ailments. Over the last decade, real-time monitoring of health conditions has been prioritized for accurate clinical diagnosis and access to accelerated treatment options. Therefore, the demand for wearable biosensing modules for preventive and monitoring purposes has been increasing over the last decade. Application of machine learning, big data analysis, neural networks, and artificial intelligence for precision and various power-saving approaches are used to increase the reliability and acceptance of smart wearables. However, user compliance and ergonomics are key areas that need focus to make the wearables mainstream. Much can be achieved through the incorporation of smart materials and soft electronics. Though skin-friendly wearable devices have been highlighted recently for their multifunctional abilities, a detailed discussion on the integration of smart materials for higher user compliance is still missing. In this review, we have discussed the principles and applications of sustainable smart material sensors and soft electronics for better ergonomics and increased user compliance in various healthcare devices. Moreover, the importance of nanomaterials and nanotechnology is discussed in the development of smart wearables.
Collapse
Affiliation(s)
- Arnab Ghosh
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Sagnik Nag
- Department of Biotechnology, School of Biosciences & Technology, Vellore Institute of Technology (VIT), Tiruvalam Road, Vellore 632014, Tamil Nadu, India
| | - Alyssa Gomes
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Apurva Gosavi
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Gauri Ghule
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Aniket Kundu
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Buddhadev Purohit
- DTU Bioengineering, Technical University of Denmark, Søltofts Plads 221, 2800 Kongens Lyngby, Denmark
| | - Rohit Srivastava
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| |
Collapse
|
14
|
Steins H, Mierzejewski M, Brauns L, Stumpf A, Kohler A, Heusel G, Corna A, Herrmann T, Jones PD, Zeck G, von Metzen R, Stieglitz T. A flexible protruding microelectrode array for neural interfacing in bioelectronic medicine. MICROSYSTEMS & NANOENGINEERING 2022; 8:131. [PMID: 36568135 PMCID: PMC9772315 DOI: 10.1038/s41378-022-00466-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 06/23/2022] [Accepted: 07/07/2022] [Indexed: 05/31/2023]
Abstract
Recording neural signals from delicate autonomic nerves is a challenging task that requires the development of a low-invasive neural interface with highly selective, micrometer-sized electrodes. This paper reports on the development of a three-dimensional (3D) protruding thin-film microelectrode array (MEA), which is intended to be used for recording low-amplitude neural signals from pelvic nervous structures by penetrating the nerves transversely to reduce the distance to the axons. Cylindrical gold pillars (Ø 20 or 50 µm, ~60 µm height) were fabricated on a micromachined polyimide substrate in an electroplating process. Their sidewalls were insulated with parylene C, and their tips were optionally modified by wet etching and/or the application of a titanium nitride (TiN) coating. The microelectrodes modified by these combined techniques exhibited low impedances (~7 kΩ at 1 kHz for Ø 50 µm microelectrode with the exposed surface area of ~5000 µm²) and low intrinsic noise levels. Their functionalities were evaluated in an ex vivo pilot study with mouse retinae, in which spontaneous neuronal spikes were recorded with amplitudes of up to 66 µV. This novel process strategy for fabricating flexible, 3D neural interfaces with low-impedance microelectrodes has the potential to selectively record neural signals from not only delicate structures such as retinal cells but also autonomic nerves with improved signal quality to study neural circuits and develop stimulation strategies in bioelectronic medicine, e.g., for the control of vital digestive functions.
Collapse
Affiliation(s)
- Helen Steins
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering, University of Freiburg, Freiburg, Germany
| | - Michael Mierzejewski
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany
| | - Lisa Brauns
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany
| | - Angelika Stumpf
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany
| | - Alina Kohler
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany
| | - Gerhard Heusel
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany
| | - Andrea Corna
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany
- Institute of Biomedical Electronics, TU Wien, Vienna, Austria
| | - Thoralf Herrmann
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany
| | - Peter D. Jones
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany
| | - Günther Zeck
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany
- Institute of Biomedical Electronics, TU Wien, Vienna, Austria
| | - Rene von Metzen
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany
| | - Thomas Stieglitz
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering, University of Freiburg, Freiburg, Germany
- Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany
- BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany
| |
Collapse
|
15
|
Cao X, Chen G. Advances in microneedles for non-transdermal applications. Expert Opin Drug Deliv 2022; 19:1081-1097. [DOI: 10.1080/17425247.2022.2118711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Affiliation(s)
- Xiaona Cao
- Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
- Rosalind & Morris Goodman Cancer Institute, McGill University, Montreal, Quebec, Canada
- School of Nursing, Tianjin Medical University, Tianjin, China
| | - Guojun Chen
- Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
- Rosalind & Morris Goodman Cancer Institute, McGill University, Montreal, Quebec, Canada
| |
Collapse
|
16
|
Mamun AA, Zhao F. In-Plane Si Microneedles: Fabrication, Characterization, Modeling and Applications. MICROMACHINES 2022; 13:657. [PMID: 35630124 PMCID: PMC9146885 DOI: 10.3390/mi13050657] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 04/16/2022] [Accepted: 04/17/2022] [Indexed: 01/26/2023]
Abstract
Microneedles are getting more and more attention in research and commercialization since their advancement in the 1990s due to the advantages over traditional hypodermic needles such as minimum invasiveness, low material and fabrication cost, and precise needle geometry control, etc. The design and fabrication of microneedles depend on various factors such as the type of materials used, fabrication planes and techniques, needle structures, etc. In the past years, in-plane and out-of-plane microneedle technologies made by silicon (Si), polymer, metal, and other materials have been developed for numerous biomedical applications including drug delivery, sample collections, medical diagnostics, and bio-sensing. Among these microneedle technologies, in-plane Si microneedles excel by the inherent properties of Si such as mechanical strength, wear resistance, biocompatibility, and structural advantages of in-plane configuration such as a wide range of length, readiness of integration with other supporting components, and complementary metal-oxide-semiconductor (CMOS) compatible fabrication. This article aims to provide a review of in-plane Si microneedles with a focus on fabrication techniques, theoretical and numerical analysis, experimental characterization of structural and fluidic behaviors, major applications, potential challenges, and future prospects.
Collapse
Affiliation(s)
| | - Feng Zhao
- Micro/Nanoelectronics and Energy Laboratory, School of Engineering and Computer Science, Washington State University, Vancouver, WA 98686, USA;
| |
Collapse
|