Evidence map›Paper›PMID 39597097›Full record

ArticleMicromachines2024

A Wireless Bi-Directional Brain-Computer Interface Supporting Both Bluetooth and Wi-Fi Transmission.

Wei Ji, Haoyang Su, Shuang Jin, Ye Tian, Gen Li, Yingkang Yang, Jiazhi Li, Zhitao Zhou, Xiaoling Wei, Tiger H Tao and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Micromachines, 2024. 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
–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

3 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 · 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

13 authors.

Wei JiCollege of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai 201306, China.
Haoyang Su2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China.
Shuang Jin2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China.
Ye Tian2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China.
Gen Li2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China.
Yingkang Yang2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China.
Jiazhi Li2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China.
Zhitao ZhouSchool of Graduate Study, University of Chinese Academy of Sciences, Beijing 100049, China.
Xiaoling WeiSchool of Graduate Study, University of Chinese Academy of Sciences, Beijing 100049, China.ORCID 0000-0002-0099-2260
Tiger H Tao2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China.
Lunming QinCollege of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai 201306, China.
Yifei Ye2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China.
Liuyang Sun2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China.ORCID 0009-0006-4421-1952

Funding

Fund for Central Government in Guidance of Local Science and Technology Development 20201ZDE04013Jiangxi Province 03 Special Project and 5G Project 20212ABC03W07Key Research Program of Frontier Sciences, CAS ZDBS-LY-JSC024National Key R & D Program of China 2019YFA0905200National Key R & D Program of China 2021YFC2501500National Key R & D Program of China 2021YFF1200700National Key R & D Program of China 2021ZD0201600National Key R & D Program of China 2022YFF0706500National Key R & D Program of China 2022ZD0209300National Key R & D Program of China 2022ZD0212300National Natural Science Foundation of China 61974154Science and Technology Commission Foundation of Shanghai 21142200300Science and Technology Commission Foundation of Shanghai 21JM0010200Shanghai Municipal Science and Technology Major Project 2021SHZDZXShanghai Pilot Program for Basic Research-Chinese Academy of Science, Shanghai Branch JCYJ-SHFY-2022-01Shanghai Pujiang Program 19PJ1410900Shanghai Pujiang Program 21PJ1415100Shanghai Rising-Star Program 22QA1410900Shanghai Sailing Program 22YF1454700Special Fund Project for Science and Technology Innovation Strategy of Guangdong Province 2021B0909050004Special Fund Project for Science and Technology Innovation Strategy of Guangdong Province 2021B0909060002
6 · The paper itself

Abstract

Wireless neural signal transmission is essential for both neuroscience research and neural disorder therapies. However, conventional wireless systems are often constrained by low sampling rates, limited channel counts, and their support of only a single transmission mode. Here, we developed a wireless bi-directional brain-computer interface system featuring dual transmission modes. This system supports both low-power Bluetooth transmission and high-sampling-rate Wi-Fi transmission, providing flexibility for various application scenarios. The Bluetooth mode, with a maximum sampling rate of 14.4 kS/s, is well suited for detecting low-frequency signals, as demonstrated by both in vitro recordings of signals from 10 to 50 Hz and in vivo recordings of 16-channel local field potentials in mice. More importantly, the Wi-Fi mode, offering a maximum sampling rate of 56.8 kS/s, is optimized for recording high-frequency signals. This capability was validated through in vitro recordings of signals from 500 to 2000 Hz and in vivo recordings of single-neuron spike firings with amplitudes reaching hundreds of microvolts and high signal-to-noise ratios. Additionally, the system incorporates a wireless stimulation function capable of delivering current pulses up to 2.55 mA, with adjustable pulse width and polarity. Overall, this dual-mode system provides an efficient and flexible solution for both neural recording and stimulation applications.

Indexed as

Bluetoothbrain–computer interfaceWi-Fiwireless transmission

Identifiers

PMID39597097
PMCPMC11596061

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.