Evidence map›Paper›PMID 36005009›Full record

ArticleBiosensors2022

An Ultra-Low-Noise, Low Power and Miniaturized Dual-Channel Wireless Neural Recording Microsystem.

Haochuan Wang, Qian Ma, Keming Chen, Hanqing Zhang, Yinyan Yang, Nenggan Zheng, Hui Hong

Abstract read
In one paragraph

Article in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Article
  2. Full-Stack Architectures for Intelligent Brain-Computer Interfaces.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  3. Article
  4. Article
  5. Article
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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

7 authors.

Haochuan WangKey Laboratory of Radio Frequency Circuit and System, Hangzhou Dianzi University, Hangzhou 310018, China.ORCID 0000-0003-2764-4730
Qian MaQiushi Academy for Advanced Studies, Zhejiang University, Hangzhou 310027, China.ORCID 0000-0002-6594-813X
Keming ChenKey Laboratory of Radio Frequency Circuit and System, Hangzhou Dianzi University, Hangzhou 310018, China.
Hanqing ZhangKey Laboratory of Radio Frequency Circuit and System, Hangzhou Dianzi University, Hangzhou 310018, China.
Yinyan YangKey Laboratory of Radio Frequency Circuit and System, Hangzhou Dianzi University, Hangzhou 310018, China.
Nenggan ZhengQiushi Academy for Advanced Studies, Zhejiang University, Hangzhou 310027, China.ORCID 0000-0002-0211-8817
Hui HongKey Laboratory of Radio Frequency Circuit and System, Hangzhou Dianzi University, Hangzhou 310018, China.ORCID 0000-0002-8807-7859

Funding

National Natural Science Foundation of China 62171169Natural Science Foundation of Zhejiang Province LR19F020005the "Pioneer" and "Leading Goose" R&D Program of Zhejiang 2022C01119
6 · The paper itself

Abstract

As the basic tools for neuroscience research, invasive neural recording devices can obtain high-resolution neuronal activity signals through electrodes connected to the subject's brain. Existing wireless neural recording devices are large in size or need external large-scale equipment for wireless power supply, which limits their application. Here, we developed an ultra-low-noise, low power and miniaturized dual-channel wireless neural recording microsystem. With the full-differential front-end structure of the dual operational amplifiers (op-amps), the noise level and power consumption are notably reduced. The hierarchical microassembly technology, which integrates wafer-level packaged op-amps and the miniaturized Bluetooth module, dramatically reduces the size of the wireless neural recording microsystem. The microsystem shows a less than 100 nV/Hz ultra-low noise level, about 10 mW low power consumption, and 9 × 7 × 5 mm3 small size. The neural recording ability was then demonstrated in saline and a chronic rat model. Because of its miniaturization, it can be applied to freely behaving small animals, such as rats. Its features of ultra-low noise and high bandwidth are conducive to low-amplitude neural signal recording, which may help advance neuroscientific discovery.

Indexed as

Amplifiers, ElectronicWireless TechnologyAnimalsBrainElectric Power SuppliesEquipment DesignRatsSignal Processing, Computer-Assistedfull-differential front-end structurehierarchical microassembly technologylow-power systemsystem miniaturizationultra-low noisewireless neural recording

Identifiers

PMID36005009
PMCPMC9405808

What OpenQuestion holds

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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.