Evidence map›Paper›PMID 37374807›Full record

ArticleMicromachines2023

Design and Optimization of Planar Spiral Coils for Powering Implantable Neural Recording Microsystem.

Jie Luo, Ruifeng Xue, Jiahao Cheong, Xuan Zhang, Lei Yao

Open access · goldAbstract read
In one paragraph

Article in Micromachines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Jie LuoSchool of Microelectronics, Shanghai University, Shanghai 201800, China.
Ruifeng XueShanghai Industrial Technology Research Institute, Shanghai 201899, China.ORCID 0009-0001-4676-5055
Jiahao CheongShanghai Industrial Technology Research Institute, Shanghai 201899, China.
Xuan ZhangShanghai Industrial Technology Research Institute, Shanghai 201899, China.
Lei YaoSchool of Microelectronics, Shanghai University, Shanghai 201800, China.
Shanghai Industrial Technology Institute · CNShanghai University · CN

Funding

National Key R&D Program of China 2021YFB3200600
6 · The paper itself

Abstract

This paper presents a design and optimization method utilizing inductive coupling coils for wireless power transfer in implantable neural recording microsystems, aiming at maximizing power transfer efficiency, which is essential for reducing externally transmitted power and ensuring biological tissue safety. The modeling of inductive coupling is simplified by combining semi-empirical formulations with theoretical models. By introducing the optimal resonant load transformation, the coil optimization is decoupled from an actual load impedance. The complete design optimization process of the coil parameters is given, which takes the maximum theoretical power transfer efficiency as the objective function. When the actual load changes, only the load transformation network needs to be updated instead of rerunning the entire optimization process. Planar spiral coils are designed to power neural recording implants given the challenges of limited implantable space, stringent low-profile restrictions, high-power transmission requirements and biocompatibility. The modeling calculation, electromagnetic simulation and measurement results are compared. The operating frequency of the designed inductive coupling is 13.56 MHz, the outer diameter of the implanted coil is 10 mm and the working distance between the external coil and the implanted coil is 10 mm. The measured power transfer efficiency is 70%, which is close to the maximum theoretical transfer efficiency of 71.9%, confirming the effectiveness of this method.

Indexed as

implantableinductive couplingneural recording microsystemplanar spiral coilresonant load transformationwireless power transfer

Identifiers

PMID37374807
PMCPMC10302922
OpenAlexW4380084217

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.