Passive Impedance Matching for Implanted Brain–Electrode Interfaces

Chen, Wei-Chuan; Guido, Katrina; Kiourti, Asimina

doi:10.1109/jerm.2019.2904024

Cited by 19 publications

(6 citation statements)

References 20 publications

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“…Note: Invasive electrode–brain electrode falls under the category of implanted electrode. Its interface layer stack and circuit model are similar to the layer stack and circuit model of the implanted electrode shown in Figure 6 A [ 62 ].…”

Section: Body–electrode Interfacementioning

confidence: 99%

Human Body–Electrode Interfaces for Wide-Frequency Sensing and Communication: A Review

et al. 2021

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Several on-body sensing and communication applications use electrodes in contact with the human body. Body–electrode interfaces in these cases act as a transducer, converting ionic current in the body to electronic current in the sensing and communication circuits and vice versa. An ideal body–electrode interface should have the characteristics of an electrical short, i.e., the transfer of ionic currents and electronic currents across the interface should happen without any hindrance. However, practical body–electrode interfaces often have definite impedances and potentials that hinder the free flow of currents, affecting the application’s performance. Minimizing the impact of body–electrode interfaces on the application’s performance requires one to understand the physics of such interfaces, how it distorts the signals passing through it, and how the interface-induced signal degradations affect the applications. Our work deals with reviewing these elements in the context of biopotential sensing and human body communication.

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Section: Body–electrode Interfacementioning

confidence: 99%

Human Body–Electrode Interfaces for Wide-Frequency Sensing and Communication: A Review

et al. 2021

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“…8. Diode not only acts as a DC bias for BJT but also as a mixer, while BJT converts high impedance coming from electrode-tissue interface into low impedance, resulting in recording low-potential brain signal [11]. However, small form factor with bare die NpN BJT and diode with embedded packaging are yet to be realized.…”

Section: Resultsmentioning

confidence: 99%

Miniaturized Fully-Passive Wireless Neural Recording with Heterogeneous Integration in Thin Packages

Sayeed¹,

Pulugartha²

2022

Preprint

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Wireless fully-passive neural recording systems are demonstrated with heterogeneous integration of sensing, mixing and communication components in flexible polymer dielectric films. The recording neurosensor has an antenna, antiparallel diode, and a by-pass capacitor to modulate an incoming carrier signal with the neuropotentials and backscatter the mixed signal to an external reader circuit. Planar antennas are realized on Liquid Crystal Polymer (LCP) flexible substrates with low dielectric constant. The designed antenna topology is realized with a single metal layer and eliminates the dependency on substrate thickness and leads to thinner sensors. This is a major advance compared to prior passive neural recording with rigid and thicker substrates and components. Approximately 80% thickness reduction and 20% volume reduction are achieved with similar performance compared to earlier studies. Our approach thus leads to low-cost and disposable wireless neurosensors on a flexible platform with heterogenous integration.

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“…Continuous variables were summarized with mean and standard deviation and categorical variables as proportions. For each subject, we computed the pairwise linear (Pearson) correlation coefficients between ROI, transformed to z-score, and input into the matrix-based-analysis (MBA) software for a Bayesian multilevel (BML) modeling approach to the statistical inference of matrix-based data (22). Briefly, the statistical analysis was performed at the population level MBA with all the ROIs incorporated in one Bayesian multilevel model.…”

Section: Discussionmentioning

confidence: 99%

Functional Neuroimaging During Asleep DBS Surgery: A Proof of Concept Study

et al. 2021

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Object: A real-time functional magnetic resonance imaging (fMRI) feedback during ventral intermediate nucleus (VIM) deep brain stimulation (DBS) under general anesthesia (or “asleep” DBS) does not exist. We hypothesized that it was feasible to acquire a reliable and responsive fMRI during asleep VIM DBS surgery.Methods: We prospectively enrolled 10 consecutive patients who underwent asleep DBS for the treatment of medication-refractory essential tremor. Under general anesthesia, we acquired resting-state functional MRI immediately before and after the cannula insertion. Reliability was determined by a temporal signal-to-noise-ratio >100. Responsiveness was determined based on the fMRI signal change upon insertion of the cannula to the VIM.Results: It was feasible to acquire reliable fMRI during asleep DBS surgery. The fMRI signal was responsive to the brain cannula insertion, revealing a reduction in the tremor network's functional connectivity, which did not reach statistical significance in the group analysis.Conclusions: It is feasible to acquire a reliable and responsive fMRI signal during asleep DBS. The acquisition steps and the preprocessing pipeline developed in these experiments will be useful for future investigations to develop fMRI-based feedback for asleep DBS surgery.

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Passive Impedance Matching for Implanted Brain–Electrode Interfaces

Cited by 19 publications

References 20 publications

Human Body–Electrode Interfaces for Wide-Frequency Sensing and Communication: A Review

Human Body–Electrode Interfaces for Wide-Frequency Sensing and Communication: A Review

Miniaturized Fully-Passive Wireless Neural Recording with Heterogeneous Integration in Thin Packages

Functional Neuroimaging During Asleep DBS Surgery: A Proof of Concept Study

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