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Jia Q, Liu Y, Lv S, Wang Y, Jiao P, Xu W, Xu Z, Wang M, Cai X. Wireless closed-loop deep brain stimulation using microelectrode array probes. J Zhejiang Univ Sci B 2024:1-21. [PMID: 38423536 DOI: 10.1631/jzus.b2300400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 08/25/2023] [Indexed: 03/02/2024]
Abstract
Deep brain stimulation (DBS), including optical stimulation and electrical stimulation, has been demonstrated considerable value in exploring pathological brain activity and developing treatments for neural disorders. Advances in DBS microsystems based on implantable microelectrode array (MEA) probes have opened up new opportunities for closed-loop DBS (CL-DBS) in situ. This technology can be used to detect damaged brain circuits and test the therapeutic potential for modulating the output of these circuits in a variety of diseases simultaneously. Despite the success and rapid utilization of MEA probe-based CL-DBS microsystems, key challenges, including excessive wired communication, need to be urgently resolved. In this review, we considered recent advances in MEA probe-based wireless CL-DBS microsystems and outlined the major issues and promising prospects in this field. This technology has the potential to offer novel therapeutic options for psychiatric disorders in the future.
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Affiliation(s)
- Qianli Jia
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yaoyao Liu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shiya Lv
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yiding Wang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Peiyao Jiao
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Xu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhaojie Xu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Mixia Wang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China.
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Xinxia Cai
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China. ,
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China. ,
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Shen K, Chen O, Edmunds JL, Piech DK, Maharbiz MM. Translational opportunities and challenges of invasive electrodes for neural interfaces. Nat Biomed Eng 2023; 7:424-442. [PMID: 37081142 DOI: 10.1038/s41551-023-01021-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 02/15/2023] [Indexed: 04/22/2023]
Abstract
Invasive brain-machine interfaces can restore motor, sensory and cognitive functions. However, their clinical adoption has been hindered by the surgical risk of implantation and by suboptimal long-term reliability. In this Review, we highlight the opportunities and challenges of invasive technology for clinically relevant electrophysiology. Specifically, we discuss the characteristics of neural probes that are most likely to facilitate the clinical translation of invasive neural interfaces, describe the neural signals that can be acquired or produced by intracranial electrodes, the abiotic and biotic factors that contribute to their failure, and emerging neural-interface architectures.
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Affiliation(s)
- Konlin Shen
- University of California, Berkeley - University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA.
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA, USA.
| | - Oliver Chen
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA, USA
| | - Jordan L Edmunds
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA, USA
| | - David K Piech
- University of California, Berkeley - University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA
| | - Michel M Maharbiz
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA, USA
- Department of Bioengineering, University of California, Berkeley, CA, USA
- Chan-Zuckerberg Biohub, San Francisco, CA, USA
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3
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Martinez S, Veirano F, Constandinou TG, Silveira F. Trends in volumetric-energy efficiency of implantable neurostimulators: a review from a circuits and systems perspective. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2022; PP:2-20. [PMID: 37015536 DOI: 10.1109/tbcas.2022.3228895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
This paper presents a comprehensive review of state-of-the-art, commercially available neurostimulators. We analyse key design parameters and performance metrics of 45 implantable medical devices across six neural target categories: deep brain, vagus nerve, spinal cord, phrenic nerve, sacral nerve and hypoglossal nerve. We then benchmark these alongside modern cardiac pacemaker devices that represent a more established market. This work studies trends in device size, electrode number, battery technology (i.e., primary and secondary use and chemistry), power consumption and longevity. This information is analysed to show the course of design decisions adopted by industry and identifying opportunity for further innovation. We identify fundamental limits in power consumption, longevity and size as well as the interdependencies and trade-offs. We propose a figure of merit to quantify volumetric efficiency within specific therapeutic targets, battery technologies/capacities, charging capabilities and electrode count. Finally, we compare commercially available implantable medical devices with recently developed systems in the research community. We envisage this analysis to aid circuit and system designers in system optimisation and identifying innovation opportunities, particularly those related to low power circuit design techniques.
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Erofeev A, Antifeev I, Bolshakova A, Bezprozvanny I, Vlasova O. In Vivo Penetrating Microelectrodes for Brain Electrophysiology. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22239085. [PMID: 36501805 PMCID: PMC9735502 DOI: 10.3390/s22239085] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 11/14/2022] [Accepted: 11/22/2022] [Indexed: 05/13/2023]
Abstract
In recent decades, microelectrodes have been widely used in neuroscience to understand the mechanisms behind brain functions, as well as the relationship between neural activity and behavior, perception and cognition. However, the recording of neuronal activity over a long period of time is limited for various reasons. In this review, we briefly consider the types of penetrating chronic microelectrodes, as well as the conductive and insulating materials for microelectrode manufacturing. Additionally, we consider the effects of penetrating microelectrode implantation on brain tissue. In conclusion, we review recent advances in the field of in vivo microelectrodes.
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Affiliation(s)
- Alexander Erofeev
- Laboratory of Molecular Neurodegeneration, Graduate School of Biomedical Systems and Technologies, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
- Correspondence: (A.E.); (O.V.)
| | - Ivan Antifeev
- Laboratory of Methods and Instruments for Genetic and Immunoassay Analysis, Institute for Analytical Instrumentation of the Russian Academy of Sciences, 198095 Saint Petersburg, Russia
| | - Anastasia Bolshakova
- Laboratory of Molecular Neurodegeneration, Graduate School of Biomedical Systems and Technologies, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
| | - Ilya Bezprozvanny
- Laboratory of Molecular Neurodegeneration, Graduate School of Biomedical Systems and Technologies, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
- Department of Physiology, University of Texas Southwestern Medical Center at Dallas, Dallas, TX 75390, USA
| | - Olga Vlasova
- Laboratory of Molecular Neurodegeneration, Graduate School of Biomedical Systems and Technologies, Institute of Biomedical Systems and Biotechnology, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia
- Correspondence: (A.E.); (O.V.)
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5
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Noise Power Minimization in CMOS Brain-Chip Interfaces. Bioengineering (Basel) 2022; 9:bioengineering9020042. [PMID: 35200396 PMCID: PMC8869152 DOI: 10.3390/bioengineering9020042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 12/25/2021] [Accepted: 01/13/2022] [Indexed: 11/17/2022] Open
Abstract
This paper presents specific noise minimization strategies to be adopted in silicon–cell interfaces. For this objective, a complete and general model for the analog processing of the signal coming from cell–silicon junctions is presented. This model will then be described at the level of the single stages and of the fundamental parameters that characterize them (bandwidth, gain and noise). Thanks to a few design equations, it will therefore be possible to simulate the behavior of a time-division multiplexed acquisition channel, including the most relevant parameters for signal processing, such as amplification (or power of the analog signal) and noise. This model has the undoubted advantage of being particularly simple to simulate and implement, while maintaining high accuracy in estimating the signal quality (i.e., the signal-to-noise ratio, SNR). Thanks to the simulation results of the model, it will be possible to set an optimal operating point for the front-end to minimize the artifacts introduced by the time-division multiplexing (TDM) scheme and to maximize the SNR at the a-to-d converter input. The proposed results provide an SNR of 12 dB at 10 µVRMS of noise power and 50 µVRMS of signal power (both evaluated at input of the analog front-end, AFE). This is particularly relevant for cell–silicon junctions because it demonstrates that it is possible to detect weak extracellular events (of the order of few µVRMS) without necessarily increasing the total amplification of the front-end (and, therefore, as a first approximation, the dissipated electrical power), while adopting a specific gain distribution through the acquisition chain.
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Kmon P. Highly Configurable 100 Channel Recording and Stimulating Integrated Circuit for Biomedical Experiments. SENSORS (BASEL, SWITZERLAND) 2021; 21:8482. [PMID: 34960575 PMCID: PMC8705452 DOI: 10.3390/s21248482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 12/13/2021] [Accepted: 12/16/2021] [Indexed: 11/16/2022]
Abstract
This paper presents the design results of a 100-channel integrated circuit dedicated to various biomedical experiments requiring both electrical stimulation and recording ability. The main design motivation was to develop an architecture that would comprise not only the recording and stimulation, but would also block allowing to meet different experimental requirements. Therefore, both the controllability and programmability were prime concerns, as well as the main chip parameters uniformity. The recording stage allows one to set their parameters independently from channel to channel, i.e., the frequency bandwidth can be controlled in the (0.3 Hz-1 kHz)-(20 Hz-3 kHz) (slow signal path) or (0.3 Hz-1 kHz)-4.7 kHz (fast signal path) range, while the voltage gain can be set individually either to 43.5 dB or 52 dB. Importantly, thanks to in-pixel circuitry, main system parameters may be controlled individually allowing to mitigate the circuitry components spread, i.e., lower corner frequency can be tuned in the 54 dB range with approximately 5% precision, and the upper corner frequency spread is only 4.2%, while the voltage gain spread is only 0.62%. The current stimulator may also be controlled in the broad range (69 dB) with its current setting precision being no worse than 2.6%. The recording channels' input-referred noise is equal to 8.5 µVRMS in the 10 Hz-4.7 kHz bandwidth. The single-pixel occupies 0.16 mm2 and consumes 12 µW (recording part) and 22 µW (stimulation blocks).
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Affiliation(s)
- Piotr Kmon
- Department of Measurement and Electronics, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Cracow, Poland
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7
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Analysis and Reduction of Nonlinear Distortion in AC-Coupled CMOS Neural Amplifiers with Tunable Cutoff Frequencies. SENSORS 2021; 21:s21093116. [PMID: 33946209 PMCID: PMC8125415 DOI: 10.3390/s21093116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 04/16/2021] [Accepted: 04/21/2021] [Indexed: 11/16/2022]
Abstract
Integrated CMOS neural amplifiers are key elements of modern large-scale neuroelectronic interfaces. The neural amplifiers are routinely AC-coupled to electrodes to remove the DC voltage. The large resistances required for the AC coupling circuit are usually realized using MOSFETs that are nonlinear. Specifically, designs with tunable cutoff frequency of the input high‑pass filter may suffer from excessive nonlinearity, since the gate-source voltages of the transistors forming the pseudoresistors vary following the signal being amplified. Consequently, the nonlinear distortion in such circuits may be high for signal frequencies close to the cutoff frequency of the input filter. Here we propose a simple modification of the architecture of a tunable AC-coupled amplifier, in which the bias voltages Vgs of the transistors forming the pseudoresistor are kept constant independently of the signal levels, what results in significantly improved linearity. Based on numerical simulations of the proposed circuit designed in 180 nm technology we analyze the Total Harmonic Distortion levels as a function of signal frequency and amplitude. We also investigate the impact of basic amplifier parameters—gain, cutoff frequency of the AC coupling circuit, and silicon area—on the distortion and noise performance. The post-layout simulations of the complete test ASIC show that the distortion is very significantly reduced at frequencies near the cutoff frequency, when compared to the commonly used circuits. The THD values are below 1.17% for signal frequencies 1 Hz–10 kHz and signal amplitudes up to 10 mV peak-to-peak. The preamplifier area is only 0.0046 mm2 and the noise is 8.3 µVrms in the 1 Hz–10 kHz range. To our knowledge this is the first report on a CMOS neural amplifier with systematic characterization of THD across complete range of frequencies and amplitudes of neuronal signals recorded by extracellular electrodes.
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Cai L, Gutruf P. Soft, Wireless and subdermally implantable recording and neuromodulation tools. J Neural Eng 2021; 18. [PMID: 33607646 DOI: 10.1088/1741-2552/abe805] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2020] [Accepted: 02/19/2021] [Indexed: 12/14/2022]
Abstract
Progress in understanding neuronal interaction and circuit behavior of the central and peripheral nervous system strongly relies on the advancement of tools that record and stimulate with high fidelity and specificity. Currently, devices used in exploratory research predominantly utilize cables or tethers to provide pathways for power supply, data communication, stimulus delivery and recording, which constrains the scope and use of such devices. In particular, the tethered connection, mechanical mismatch to surrounding soft tissues and bones frustrate the interface leading to irritation and limitation of motion of the subject, which in the case of fundamental and preclinical studies, impacts naturalistic behaviors of animals and precludes the use in experiments involving social interaction and ethologically relevant three-dimensional environments, limiting the use of current tools to mostly rodents and exclude species such as birds and fish. This review explores the current state-of-the-art in wireless, subdermally implantable tools that quantitively expand capabilities in analysis and perturbation of the central and peripheral nervous system by removing tethers and externalized features of implantable neuromodulation and recording tools. Specifically, the review explores power harvesting strategies, wireless communication schemes, and soft materials and mechanics that enable the creation of such devices and discuss their capabilities in the context of freely-behaving subjects. Highlights of this class of devices includes wireless battery-free and fully implantable operation with capabilities in cell specific recording, multimodal neural stimulation and electrical, optogenetic and pharmacological neuromodulation capabilities. We conclude with discussion on translation of such technologies which promises routes towards broad dissemination.
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Affiliation(s)
- Le Cai
- Biomedical Engineering, University of Arizona, 1230 N Cherry Ave., Tucson, Arizona, 85719, UNITED STATES
| | - Philipp Gutruf
- Biomedical Engineering, University of Arizona, 1230 N Cherry Ave., Tucson, Arizona, 85719, UNITED STATES
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9
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Forro C, Caron D, Angotzi GN, Gallo V, Berdondini L, Santoro F, Palazzolo G, Panuccio G. Electrophysiology Read-Out Tools for Brain-on-Chip Biotechnology. MICROMACHINES 2021; 12:124. [PMID: 33498905 PMCID: PMC7912435 DOI: 10.3390/mi12020124] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 01/18/2021] [Accepted: 01/19/2021] [Indexed: 02/07/2023]
Abstract
Brain-on-Chip (BoC) biotechnology is emerging as a promising tool for biomedical and pharmaceutical research applied to the neurosciences. At the convergence between lab-on-chip and cell biology, BoC couples in vitro three-dimensional brain-like systems to an engineered microfluidics platform designed to provide an in vivo-like extrinsic microenvironment with the aim of replicating tissue- or organ-level physiological functions. BoC therefore offers the advantage of an in vitro reproduction of brain structures that is more faithful to the native correlate than what is obtained with conventional cell culture techniques. As brain function ultimately results in the generation of electrical signals, electrophysiology techniques are paramount for studying brain activity in health and disease. However, as BoC is still in its infancy, the availability of combined BoC-electrophysiology platforms is still limited. Here, we summarize the available biological substrates for BoC, starting with a historical perspective. We then describe the available tools enabling BoC electrophysiology studies, detailing their fabrication process and technical features, along with their advantages and limitations. We discuss the current and future applications of BoC electrophysiology, also expanding to complementary approaches. We conclude with an evaluation of the potential translational applications and prospective technology developments.
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Affiliation(s)
- Csaba Forro
- Tissue Electronics, Fondazione Istituto Italiano di Tecnologia, Largo Barsanti e Matteucci, 53-80125 Naples, Italy; (C.F.); (F.S.)
- Department of Chemistry, Stanford University, Stanford, CA 94305, USA
| | - Davide Caron
- Enhanced Regenerative Medicine, Fondazione Istituto Italiano di Tecnologia, Via Morego, 30-16163 Genova, Italy; (D.C.); (V.G.)
| | - Gian Nicola Angotzi
- Microtechnology for Neuroelectronics, Fondazione Istituto Italiano di Tecnologia, Via Morego, 30-16163 Genova, Italy; (G.N.A.); (L.B.)
| | - Vincenzo Gallo
- Enhanced Regenerative Medicine, Fondazione Istituto Italiano di Tecnologia, Via Morego, 30-16163 Genova, Italy; (D.C.); (V.G.)
| | - Luca Berdondini
- Microtechnology for Neuroelectronics, Fondazione Istituto Italiano di Tecnologia, Via Morego, 30-16163 Genova, Italy; (G.N.A.); (L.B.)
| | - Francesca Santoro
- Tissue Electronics, Fondazione Istituto Italiano di Tecnologia, Largo Barsanti e Matteucci, 53-80125 Naples, Italy; (C.F.); (F.S.)
| | - Gemma Palazzolo
- Enhanced Regenerative Medicine, Fondazione Istituto Italiano di Tecnologia, Via Morego, 30-16163 Genova, Italy; (D.C.); (V.G.)
| | - Gabriella Panuccio
- Enhanced Regenerative Medicine, Fondazione Istituto Italiano di Tecnologia, Via Morego, 30-16163 Genova, Italy; (D.C.); (V.G.)
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Cotero V, Miwa H, Graf J, Ashe J, Loghin E, Di Carlo D, Puleo C. Peripheral Focused Ultrasound Neuromodulation (pFUS). J Neurosci Methods 2020; 341:108721. [DOI: 10.1016/j.jneumeth.2020.108721] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 03/03/2020] [Accepted: 04/01/2020] [Indexed: 01/28/2023]
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Gu X, Zhang J. Probability model of sensitive similarity measures in information retrieval. INT J ADV ROBOT SYST 2020. [DOI: 10.1177/1729881420901425] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
In today’s Internet age, a lot of data is stored and used, which is very important. In people’s daily life, if these data are sorted, information retrieval technology will be used, and in information retrieval, some information retrieval inaccuracies often appear. Information retrieval model is an important framework and method for fast, complete, and accurate user information retrieval. With the rapid development of information technology, great changes have taken place in people’s production and life. Various information network technologies are widely used in people’s lives. The resulting flow of information shows explosive growth, information retrieval. User requirements are getting higher and higher. How to complete personalized information retrieval in a large amount of mixed information, so that retrieval technology can help us obtain effective retrieval results, has become a realistic problem worth exploring. In this article, the application of probability model based on sensitive similarity measure in information retrieval model is analyzed, and a similarity measure algorithm based on spectral clustering is proposed. By improving the similarity measure, the sensitivity problem of scale parameters is overcome and the retrieval precision is improved. In order to better reflect the superiority of the proposed algorithm, this article compares with ng-jordan-weiss (NJW) and deep sparse subspace clustering (DSSC) algorithms. The experimental results show that the proposed algorithm is superior to NJW and DSSC algorithms for different data sets in different evaluation indicators (Rand and F-measure).
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Affiliation(s)
- Xiaolong Gu
- National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Chongqing, China
- College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Jie Zhang
- National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Chongqing, China
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Putzeys J, Raducanu BC, Carton A, De Ceulaer J, Karsh B, Siegle JH, Van Helleputte N, Harris TD, Dutta B, Musa S, Mora Lopez C. Neuropixels Data-Acquisition System: A Scalable Platform for Parallel Recording of 10 000+ Electrophysiological Signals. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2019; 13:1635-1644. [PMID: 31545742 DOI: 10.1109/tbcas.2019.2943077] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Although CMOS fabrication has enabled a quick evolution in the design of high-density neural probes and neural-recording chips, the scaling and miniaturization of the complete data-acquisition systems has happened at a slower pace. This is mainly due to the complexity and the many requirements that change depending on the specific experimental settings. In essence, the fundamental challenge of a neural-recording system is getting the signals describing the largest possible set of neurons out of the brain and down to data storage for analysis. This requires a complete system optimization that considers the physical, electrical, thermal and signal-processing requirements, while accounting for available technology, manufacturing constraints and budget. Here we present a scalable and open-standards-based open-source data-acquisition system capable of recording from over 10,000 channels of raw neural data simultaneously. The components and their interfaces have been optimized to ensure robustness and minimum invasiveness in small-rodent electrophysiology.
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Loncar-Turukalo T, Zdravevski E, Machado da Silva J, Chouvarda I, Trajkovik V. Literature on Wearable Technology for Connected Health: Scoping Review of Research Trends, Advances, and Barriers. J Med Internet Res 2019; 21:e14017. [PMID: 31489843 PMCID: PMC6818529 DOI: 10.2196/14017] [Citation(s) in RCA: 84] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Revised: 06/09/2019] [Accepted: 06/19/2019] [Indexed: 02/03/2023] Open
Abstract
Background Wearable sensing and information and communication technologies are key enablers driving the transformation of health care delivery toward a new model of connected health (CH) care. The advances in wearable technologies in the last decade are evidenced in a plethora of original articles, patent documentation, and focused systematic reviews. Although technological innovations continuously respond to emerging challenges and technology availability further supports the evolution of CH solutions, the widespread adoption of wearables remains hindered. Objective This study aimed to scope the scientific literature in the field of pervasive wearable health monitoring in the time interval from January 2010 to February 2019 with respect to four important pillars: technology, safety and security, prescriptive insight, and user-related concerns. The purpose of this study was multifold: identification of (1) trends and milestones that have driven research in wearable technology in the last decade, (2) concerns and barriers from technology and user perspective, and (3) trends in the research literature addressing these issues. Methods This study followed the scoping review methodology to identify and process the available literature. As the scope surpasses the possibilities of manual search, we relied on the natural language processing tool kit to ensure an efficient and exhaustive search of the literature corpus in three large digital libraries: Institute of Electrical and Electronics Engineers, PubMed, and Springer. The search was based on the keywords and properties to be found in articles using the search engines of the digital libraries. Results The annual number of publications in all segments of research on wearable technology shows an increasing trend from 2010 to February 2019. The technology-related topics dominated in the number of contributions, followed by research on information delivery, safety, and security, whereas user-related concerns were the topic least addressed. The literature corpus evidences milestones in sensor technology (miniaturization and placement), communication architectures and fifth generation (5G) cellular network technology, data analytics, and evolution of cloud and edge computing architectures. The research lag in battery technology makes energy efficiency a relevant consideration in the design of both sensors and network architectures with computational offloading. The most addressed user-related concerns were (technology) acceptance and privacy, whereas research gaps indicate that more efforts should be invested into formalizing clear use cases with timely and valuable feedback and prescriptive recommendations. Conclusions This study confirms that applications of wearable technology in the CH domain are becoming mature and established as a scientific domain. The current research should bring progress to sustainable delivery of valuable recommendations, enforcement of privacy by design, energy-efficient pervasive sensing, seamless monitoring, and low-latency 5G communications. To complement technology achievements, future work involving all stakeholders providing research evidence on improved care pathways and cost-effectiveness of the CH model is needed.
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Affiliation(s)
| | - Eftim Zdravevski
- Faculty of Computer Science and Engineering, Saints Cyril and Methodius University, Skopje, North Macedonia
| | - José Machado da Silva
- Institute for Systems and Computer Engineering, Technology and Science, Faculty of Engineering, University of Porto, Porto, Portugal
| | - Ioanna Chouvarda
- Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Vladimir Trajkovik
- Faculty of Computer Science and Engineering, Saints Cyril and Methodius University, Skopje, North Macedonia
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14
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Tam WK, Wu T, Zhao Q, Keefer E, Yang Z. Human motor decoding from neural signals: a review. BMC Biomed Eng 2019; 1:22. [PMID: 32903354 PMCID: PMC7422484 DOI: 10.1186/s42490-019-0022-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Accepted: 07/21/2019] [Indexed: 01/24/2023] Open
Abstract
Many people suffer from movement disability due to amputation or neurological diseases. Fortunately, with modern neurotechnology now it is possible to intercept motor control signals at various points along the neural transduction pathway and use that to drive external devices for communication or control. Here we will review the latest developments in human motor decoding. We reviewed the various strategies to decode motor intention from human and their respective advantages and challenges. Neural control signals can be intercepted at various points in the neural signal transduction pathway, including the brain (electroencephalography, electrocorticography, intracortical recordings), the nerves (peripheral nerve recordings) and the muscles (electromyography). We systematically discussed the sites of signal acquisition, available neural features, signal processing techniques and decoding algorithms in each of these potential interception points. Examples of applications and the current state-of-the-art performance were also reviewed. Although great strides have been made in human motor decoding, we are still far away from achieving naturalistic and dexterous control like our native limbs. Concerted efforts from material scientists, electrical engineers, and healthcare professionals are needed to further advance the field and make the technology widely available in clinical use.
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Affiliation(s)
- Wing-kin Tam
- Department of Biomedical Engineering, University of Minnesota Twin Cities, 7-105 Hasselmo Hall, 312 Church St. SE, Minnesota, 55455 USA
| | - Tong Wu
- Department of Biomedical Engineering, University of Minnesota Twin Cities, 7-105 Hasselmo Hall, 312 Church St. SE, Minnesota, 55455 USA
| | - Qi Zhao
- Department of Computer Science and Engineering, University of Minnesota Twin Cities, 4-192 Keller Hall, 200 Union Street SE, Minnesota, 55455 USA
| | - Edward Keefer
- Nerves Incorporated, Dallas, TX P. O. Box 141295 USA
| | - Zhi Yang
- Department of Biomedical Engineering, University of Minnesota Twin Cities, 7-105 Hasselmo Hall, 312 Church St. SE, Minnesota, 55455 USA
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15
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Robinson JT, Pohlmeyer E, Gather MC, Kemere C, Kitching JE, Malliaras GG, Marblestone A, Shepard KL, Stieglitz T, Xie C. Developing Next-generation Brain Sensing Technologies - A Review. IEEE SENSORS JOURNAL 2019; 19:10.1109/jsen.2019.2931159. [PMID: 32116472 PMCID: PMC7047830 DOI: 10.1109/jsen.2019.2931159] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Advances in sensing technology raise the possibility of creating neural interfaces that can more effectively restore or repair neural function and reveal fundamental properties of neural information processing. To realize the potential of these bioelectronic devices, it is necessary to understand the capabilities of emerging technologies and identify the best strategies to translate these technologies into products and therapies that will improve the lives of patients with neurological and other disorders. Here we discuss emerging technologies for sensing brain activity, anticipated challenges for translation, and perspectives for how to best transition these technologies from academic research labs to useful products for neuroscience researchers and human patients.
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Affiliation(s)
- Jacob T. Robinson
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA
- Department of Bioengineering, Rice University, Houston, TX 77005, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
| | - Eric Pohlmeyer
- John Hopkins University Applied Physics Laboratory, Laurel, MD 20723, USA
| | - Malte C. Gather
- SUPA, School of Physics & Astronomy, University of St Andrews, St Andrews KY16 9SS Scotland, UK
| | - Caleb Kemere
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA
- Department of Bioengineering, Rice University, Houston, TX 77005, USA
| | - John E. Kitching
- Time and Frequency Division, NIST, 325 Broadway, Boulder, Colorado 80305, USA
| | - George G. Malliaras
- Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK
| | - Adam Marblestone
- MIT Media Lab, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA
| | - Kenneth L. Shepard
- Department of Electrical Engineering, Columbia University, New York, NY 10027, USA
| | - Thomas Stieglitz
- Institute of Microsystem Technology, Laboratory for Biomedical Microtechnology, D-79110 Freiburg, Germany
- Cluster of Excellence BrainLinks-BrainTools, University of Freiburg, 79110 Freiburg, Germany
- Bernstein Center Freiburg, University of Freiburg, 79104 Freiburg, Germany
| | - Chong Xie
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA
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16
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Parastarfeizabadi M, Kouzani AZ, Beckinghausen J, Lin T, Sillitoe RV. A Programmable Multi-biomarker Neural Sensor for Closed-loop DBS. IEEE ACCESS : PRACTICAL INNOVATIONS, OPEN SOLUTIONS 2018; 7:230-244. [PMID: 30976472 PMCID: PMC6453143 DOI: 10.1109/access.2018.2885336] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Most of the current closed-loop DBS devices use a single biomarker in their feedback loop which may limit their performance and applications. This paper presents design, fabrication, and validation of a programmable multi-biomarker neural sensor which can be integrated into closed-loop DBS devices. The device is capable of sensing a combination of low-frequency (7-45 Hz), and high-frequency (200-1000 Hz) neural signals. The signals can be amplified with a digitally programmable gain within the range 50-100 dB. The neural signals can be stored into a local memory for processing and validation. The sensing and storage functions are implemented via a combination of analog and digital circuits involving preamplifiers, filters, programmable post-amplifiers, microcontroller, digital potentiometer, and flash memory. The device is fabricated, and its performance is validated through: (i) bench tests using sinusoidal and pre-recorded neural signals, (ii) in-vitro tests using pre-recorded neural signals in saline solution, and (iii) in-vivo tests by recording neural signals from freely-moving laboratory mice. The animals were implanted with a PlasticsOne electrode, and recording was conducted after recovery from the electrode implantation surgery. The experimental results are presented and discussed confirming the successful operation of the device. The size and weight of the device enable tetherless back-mountable use in pre-clinical trials.
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Affiliation(s)
| | - Abbas Z. Kouzani
- School of Engineering, Deakin University, Geelong, VIC 3216, Australia
| | - Jaclyn Beckinghausen
- Department of Pathology and Immunology, Department of Neuroscience, and Jan and Dan Duncan Neurological Research Institute of Texas Children’s Hospital, 1250 Moursund Street, Suite 1325, Houston Texas 77030, USA
| | - Tao Lin
- Department of Pathology and Immunology, and Jan and Dan Duncan Neurological Research Institute of Texas Children’s Hospital, 1250 Moursund Street, Suite 1325, Houston Texas 77030, USA
| | - Roy V. Sillitoe
- Department of Pathology and Immunology, Department of Neuroscience, Program in Developmental Biology, Baylor College of Medicine, and Jan and Dan Duncan Neurological Research Institute of Texas Children’s Hospital, 1250 Moursund Street, Suite 1325, Houston Texas 77030, USA
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17
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Abstract
OBJECTIVE Electrical brain stimulation provides therapeutic benefits for patients with drug-resistant neurological disorders. It, however, has restricted access to cell-type selectivity which limits its treatment effectiveness. Optogenetics, in contrast, enables precise targeting of a specific cell type which can address the issue with electrical brain stimulation. It, nonetheless, disregards real-time brain responses in delivering optimized stimulation to target cells. Closed-loop optogenetics, on the other hand, senses the difference between normal and abnormal states of the brain, and modulates stimulation parameters to achieve the desired stimulation outcome. Current review articles on closed-loop optogenetics have focused on its theoretical aspects and potential benefits. A review of the recent progress in miniaturized closed-loop optogenetic stimulation devices is thus needed. APPROACH This paper presents a comprehensive study on the existing miniaturized closed-loop optogenetic stimulation devices and their internal components. MAIN RESULTS Hardware components of closed-loop optogenetic stimulation devices including electrode, light-guiding mechanism, optical source, neural recorder, and optical stimulator are discussed. Next, software modules of closed-loop optogenetic stimulation devices including feature extraction, classification, control, and stimulation parameter modulation are described. Then, the existing devices are categorized into open-loop and closed-loop groups, and the combined operation of their neural recorder, optical stimulator, and control approach is discussed. Finally, the challenges in the design and implementation of closed-loop optogenetic stimulation devices are presented, suggestions on how to tackle these challenges are given, and future directions for closed-loop optogenetics are stated. SIGNIFICANCE A generic architecture for closed-loop optogenetic stimulation devices involving both hardware and software perspectives is devised. A comprehensive investigation into the most current miniaturized and tetherless closed-loop optogenetic stimulation devices is given. A detailed comparison of the closed-loop optogenetic stimulation devices is presented.
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Affiliation(s)
- Epsy S Edward
- School of Engineering, Deakin University, Geelong, Victoria 3216, Australia
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18
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Thukral A, Ershad F, Enan N, Rao Z, Yu C. Soft Ultrathin Silicon Electronics for Soft Neural Interfaces: A Review of Recent Advances of Soft Neural Interfaces Based on Ultrathin Silicon. IEEE NANOTECHNOLOGY MAGAZINE 2018. [DOI: 10.1109/mnano.2017.2781290] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Anish Thukral
- Mechanical Engineering, University of Houston, Houston, Texas United States
| | - Faheem Ershad
- Biomedical Engineering, University of Houston, Houston, Texas United States
| | - Nada Enan
- Biomedical Engineering, University of Houston, Houston, Texas United States
| | - Zhoulyu Rao
- Materials Science and Engineering, University of Houston, Houston, Texas United States
| | - Cunjiang Yu
- Mechanical Engineering, University of Houston, Houston, Texas United States
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19
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Donoghue JP. Brain–Computer Interfaces. Neuromodulation 2018. [DOI: 10.1016/b978-0-12-805353-9.00025-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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20
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Reshetov IV, Polunin GV, Ananichuk AV, Ippolitov LI, Kovalenko AA. [The possibilities for the restoration of the laryngeal function: the current state-of-the-art]. Vestn Otorinolaringol 2017; 82:18-23. [PMID: 29260776 DOI: 10.17116/otorino201782618-23] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The restoration of the functional competence of the larynx following bilateral laryngeal nerve damage and vocal fold paralysis is a serious challenge for the surgeon that has thus far no satisfactory solution. Physiological re-innervation that occurs naturally with time is non-selective and, in the majority of the cases, leads to synkinesis. Laryngeal pacing achieved with the application of the implantable microchips appears to be a promising approach. The animal experiments have demonstrated the possibility of successful restoration of all the functions of the larynx by means of laryngeal pacing but simultaneously revealed a number of technical issues that have to be addressed if the further progress in this field is to be achieved including the choice of the proper materials for implantation, solution of problems pertaining to the neuromuscular mapping during pacer implantation, etc.). The results of the first prospective clinical trial involving the human patients gave evidence suggesting that the laryngeal electrostimulation technology is both safe and efficient. Nevertheless, further investigations and modification of the method are needed before it can be recommended for the wider application in the routine clinical practice.
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Affiliation(s)
- I V Reshetov
- I.M. Sechenov First Moscow State Medical University, Ministry of Health of the Russian Federation, Moscow, Russia, 119991
| | - G V Polunin
- I.M. Sechenov First Moscow State Medical University, Ministry of Health of the Russian Federation, Moscow, Russia, 119991
| | - A V Ananichuk
- I.M. Sechenov First Moscow State Medical University, Ministry of Health of the Russian Federation, Moscow, Russia, 119991
| | - L I Ippolitov
- I.M. Sechenov First Moscow State Medical University, Ministry of Health of the Russian Federation, Moscow, Russia, 119991
| | - A A Kovalenko
- I.M. Sechenov First Moscow State Medical University, Ministry of Health of the Russian Federation, Moscow, Russia, 119991
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21
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Bergmeister KD, Vujaklija I, Muceli S, Sturma A, Hruby LA, Prahm C, Riedl O, Salminger S, Manzano-Szalai K, Aman M, Russold MF, Hofer C, Principe J, Farina D, Aszmann OC. Broadband Prosthetic Interfaces: Combining Nerve Transfers and Implantable Multichannel EMG Technology to Decode Spinal Motor Neuron Activity. Front Neurosci 2017; 11:421. [PMID: 28769755 PMCID: PMC5515902 DOI: 10.3389/fnins.2017.00421] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2017] [Accepted: 07/05/2017] [Indexed: 01/09/2023] Open
Abstract
Modern robotic hands/upper limbs may replace multiple degrees of freedom of extremity function. However, their intuitive use requires a high number of control signals, which current man-machine interfaces do not provide. Here, we discuss a broadband control interface that combines targeted muscle reinnervation, implantable multichannel electromyographic sensors, and advanced decoding to address the increasing capabilities of modern robotic limbs. With targeted muscle reinnervation, nerves that have lost their targets due to an amputation are surgically transferred to residual stump muscles to increase the number of intuitive prosthetic control signals. This surgery re-establishes a nerve-muscle connection that is used for sensing nerve activity with myoelectric interfaces. Moreover, the nerve transfer determines neurophysiological effects, such as muscular hyper-reinnervation and cortical reafferentation that can be exploited by the myoelectric interface. Modern implantable multichannel EMG sensors provide signals from which it is possible to disentangle the behavior of single motor neurons. Recent studies have shown that the neural drive to muscles can be decoded from these signals and thereby the user's intention can be reliably estimated. By combining these concepts in chronic implants and embedded electronics, we believe that it is in principle possible to establish a broadband man-machine interface, with specific applications in prosthesis control. This perspective illustrates this concept, based on combining advanced surgical techniques with recording hardware and processing algorithms. Here we describe the scientific evidence for this concept, current state of investigations, challenges, and alternative approaches to improve current prosthetic interfaces.
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Affiliation(s)
- Konstantin D. Bergmeister
- CD-Laboratory for the Restoration of Extremity Function, Department of Surgery, Medical University of ViennaVienna, Austria
- Department of Hand, Plastic and Reconstructive Surgery, Burn Center, BG Trauma Center Ludwigshafen, Plastic and Hand Surgery, University of HeidelbergLudwigshafen, Germany
| | - Ivan Vujaklija
- Department of Bioengineering, Centre for Neurotechnology, Imperial College LondonLondon, United Kingdom
| | - Silvia Muceli
- Neurorehabilitation Systems Research Group, Clinic for Trauma Surgery, Orthopedics and Plastic Surgery, University Medical Center GöttingenGöttingen, Germany
| | - Agnes Sturma
- CD-Laboratory for the Restoration of Extremity Function, Department of Surgery, Medical University of ViennaVienna, Austria
- Health Assisting Engineering, University of Applied Sciences WienVienna, Austria
| | - Laura A. Hruby
- CD-Laboratory for the Restoration of Extremity Function, Department of Surgery, Medical University of ViennaVienna, Austria
| | - Cosima Prahm
- CD-Laboratory for the Restoration of Extremity Function, Department of Surgery, Medical University of ViennaVienna, Austria
| | - Otto Riedl
- CD-Laboratory for the Restoration of Extremity Function, Department of Surgery, Medical University of ViennaVienna, Austria
- Division of Plastic and Reconstructive Surgery, Department of Surgery, Medical University of ViennaVienna, Austria
| | - Stefan Salminger
- CD-Laboratory for the Restoration of Extremity Function, Department of Surgery, Medical University of ViennaVienna, Austria
- Division of Plastic and Reconstructive Surgery, Department of Surgery, Medical University of ViennaVienna, Austria
| | - Krisztina Manzano-Szalai
- CD-Laboratory for the Restoration of Extremity Function, Department of Surgery, Medical University of ViennaVienna, Austria
| | - Martin Aman
- CD-Laboratory for the Restoration of Extremity Function, Department of Surgery, Medical University of ViennaVienna, Austria
| | | | - Christian Hofer
- CD-Laboratory for the Restoration of Extremity Function, Department of Surgery, Medical University of ViennaVienna, Austria
- Otto Bock Healthcare Products GmbHVienna, Austria
| | - Jose Principe
- Department of Electrical and Computer Engineering, University of FloridaGainesville, FL, United States
| | - Dario Farina
- Department of Bioengineering, Centre for Neurotechnology, Imperial College LondonLondon, United Kingdom
| | - Oskar C. Aszmann
- CD-Laboratory for the Restoration of Extremity Function, Department of Surgery, Medical University of ViennaVienna, Austria
- Division of Plastic and Reconstructive Surgery, Department of Surgery, Medical University of ViennaVienna, Austria
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22
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Thakor NV, Greenwald E. Bidirectional peripheral nerve interface and applications. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2017; 2016:6327-6330. [PMID: 28269696 DOI: 10.1109/embc.2016.7592175] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Peripheral nerves, due to their small size and complex innervation to organs and complex physiology, pose particularly significant challenges towards interfacing electrodes and electronics to enable neuromodulation. Here, we present a review of the technology for building such interface, including recording and stimulating electrodes and low power electronics, as well as powering. Of particular advantage to building a miniature implanted device is a "bidirectional" system that both senses from the nerves or surrogate organs and stimulates the nerves to affect the organ function. This review and presentation will cover a range of electrodes, electronics, wireless power and data schemes and system integration, and will end with some examples and applications.
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23
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Behavioral Neuroscience: Who's Afraid of the C57BL/6 Mouse? Curr Biol 2016; 26:R1188-R1189. [PMID: 27875698 DOI: 10.1016/j.cub.2016.09.047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Behavioral paradigms in which laboratory rodents express behaviors that their wild counterparts presumably need every day are rare: a novel prey-capture model for laboratory mice has been developed for examining the neurophysiological underpinnings of prey capture in mice.
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24
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Weiergräber M, Papazoglou A, Broich K, Müller R. Sampling rate, signal bandwidth and related pitfalls in EEG analysis. J Neurosci Methods 2016; 268:53-5. [PMID: 27172844 DOI: 10.1016/j.jneumeth.2016.05.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2016] [Revised: 05/04/2016] [Accepted: 05/06/2016] [Indexed: 12/31/2022]
Abstract
This submission contains a commentary.
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Affiliation(s)
- Marco Weiergräber
- Department of Neuropsychopharmacology, Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, BfArM), Kurt-Georg-Kiesinger-Allee 3, 53175 Bonn, Germany.
| | - Anna Papazoglou
- Department of Neuropsychopharmacology, Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, BfArM), Kurt-Georg-Kiesinger-Allee 3, 53175 Bonn, Germany
| | - Karl Broich
- Department of Neuropsychopharmacology, Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, BfArM), Kurt-Georg-Kiesinger-Allee 3, 53175 Bonn, Germany
| | - Ralf Müller
- Department of Psychiatry and Psychotherapy, University of Cologne, Faculty of Medicine, Kerpener-Str. 62, Cologne, Germany
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25
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Implantable neurotechnologies: a review of micro- and nanoelectrodes for neural recording. Med Biol Eng Comput 2016; 54:23-44. [PMID: 26753777 DOI: 10.1007/s11517-015-1430-4] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2015] [Accepted: 12/10/2015] [Indexed: 12/22/2022]
Abstract
Electrodes serve as the first critical interface to the biological organ system. In neuroprosthetic applications, for example, electrodes interface to the tissue for either signal recording or tissue stimulation. In this review, we consider electrodes for recording neural activity. Recording electrodes serve as wiretaps into the neural tissues, providing readouts of electrical activity. These signals give us valuable insights into the organization and functioning of the nervous system. The recording interfaces have also shown promise in aiding treatment of motor and sensory disabilities caused by neurological disorders. Recent advances in fabrication technology have generated wide interest in creating tiny, high-density electrode interfaces for neural tissues. An ideal electrode should be small enough and be able to achieve reliable and conformal integration with the structures of the nervous system. As a result, the existing electrode designs are being shrunk and packed to form small form factor interfaces to tissue. Here, an overview of the historic and state-of-the-art electrode technologies for recording neural activity is presented first with a focus on their development road map. The fact that the dimensions of recording electrode sites are being scaled down from micron to submicron scale to enable dense interfaces is appreciated. The current trends in recording electrode technologies are then reviewed. Current and future considerations in electrode design, including the use of inorganic nanostructures and biologically inspired or biocomapatible materials are discussed, along with an overview of the applications of flexible materials and transistor transduction schemes. Finally, we detail the major technical challenges facing chronic use of reliable recording electrode technology.
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26
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Implantable neurotechnologies: electrical stimulation and applications. Med Biol Eng Comput 2016; 54:63-76. [PMID: 26753775 DOI: 10.1007/s11517-015-1442-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2015] [Accepted: 12/14/2015] [Indexed: 12/23/2022]
Abstract
Neural stimulation using injected electrical charge is widely used both in functional therapies and as an experimental tool for neuroscience applications. Electrical pulses can induce excitation of targeted neural pathways that aid in the treatment of neural disorders or dysfunction of the central and peripheral nervous system. In this review, we summarize the recent trends in the field of electrical stimulation for therapeutic interventions of nervous system disorders, such as for the restoration of brain, eye, ear, spinal cord, nerve and muscle function. Neural prosthetic applications are discussed, and functional electrical stimulation parameters for treating such disorders are reviewed. Important considerations for implantable packaging and enhancing device reliability are also discussed. Neural stimulators are expected to play a profound role in implantable neural devices that treat disorders and help restore functions in injured or disabled nervous system.
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27
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Greenwald E, Masters MR, Thakor NV. Erratum to: Implantable neurotechnologies: bidirectional neural interfaces--applications and VLSI circuit implementations. Med Biol Eng Comput 2016; 54:19-22. [PMID: 26924780 PMCID: PMC4955539 DOI: 10.1007/s11517-016-1452-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Affiliation(s)
- Elliot Greenwald
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
| | - Matthew R Masters
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Nitish V Thakor
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
- Singapore Institute for Neurotechnology (SINAPSE), National University of Singapore, Singapore, Singapore.
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28
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Greenwald E, Masters MR, Thakor NV. Implantable neurotechnologies: bidirectional neural interfaces--applications and VLSI circuit implementations. Med Biol Eng Comput 2016; 54:1-17. [PMID: 26753776 PMCID: PMC4839984 DOI: 10.1007/s11517-015-1429-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2015] [Accepted: 12/10/2015] [Indexed: 12/20/2022]
Abstract
A bidirectional neural interface is a device that transfers information into and out of the nervous system. This class of devices has potential to improve treatment and therapy in several patient populations. Progress in very large-scale integration has advanced the design of complex integrated circuits. System-on-chip devices are capable of recording neural electrical activity and altering natural activity with electrical stimulation. Often, these devices include wireless powering and telemetry functions. This review presents the state of the art of bidirectional circuits as applied to neuroprosthetic, neurorepair, and neurotherapeutic systems.
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Affiliation(s)
- Elliot Greenwald
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
| | - Matthew R Masters
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Nitish V Thakor
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
- Singapore Institute for Neurotechnology (SINAPSE), National University of Singapore, Singapore, Singapore.
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