Evidence map›Paper›PMID 35692891›Full record

ReviewBiomedical engineering letters2022

Miniaturization for wearable EEG systems: recording hardware and data processing.

Minjae Kim, Seungjae Yoo, Chul Kim

Erratum issuedAbstract readReview
In one paragraph

Review in Biomedical engineering letters, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Minjae Kim *Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daehak-ro, Daejeon, 34141 Republic of Korea.
Seungjae Yoo *Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daehak-ro, Daejeon, 34141 Republic of Korea.
Chul KimDepartment of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daehak-ro, Daejeon, 34141 Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As more people desire at-home diagnosis and treatment for their health improvement, healthcare devices have become more wearable, comfortable, and easy to use. In that sense, the miniaturization of electroencephalography (EEG) systems is a major challenge for developing daily-life healthcare devices. Recently, because of the intertwined relationship between EEG recording and processing, co-research of EEG recording hardware and data processing has been emphasized for whole-in-one miniaturized EEG systems. This paper introduces miniaturization techniques in analog-front-end hardware and processing algorithms for such EEG systems. To miniaturize EEG recording hardware, various types of compact electrodes and mm-sized integrated circuits (IC) techniques including artifact rejection are studied to record accurate EEG signals in a much smaller manner. Active electrode and in-ear EEG technologies are also researched to make small-form-factor EEG measurement structures. Furthermore, miniaturization techniques for EEG processing are discussed including channel selection techniques that reduce the number of required electrode channel and hardware implementation of processing algorithms that simplify the EEG processing stage.

Indexed as

Active electrodeChannel selectionElectroencephalography (EEG)Field-programmable gate array (FPGA)Hardware implementationIn-ear EEGIntegrated circuits (IC)Miniaturization

Identifiers

PMID35692891
PMCPMC9168644

What OpenQuestion holds

Textmetadata
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.