Evidence map›Paper›PMID 35835448›Full record

ReviewSeminars in neurology2022

Brain-Computer Interfaces for Awareness Detection, Auxiliary Diagnosis, Prognosis, and Rehabilitation in Patients with Disorders of Consciousness.

Jiahui Pan, Jun Xiao, Jing Wang, Fei Wang, Jingcong Li, Lina Qiu, Haibo Di, Yuanqing Li

Open access · bronzeAbstract readReview
In one paragraph

Review in Seminars in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.2field-weighted citation impact, top 24% 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

2 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Covert consciousness.NeuroRehabilitation · 2024
    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

8 authors at 3 institutions in 1 country.

Jiahui PanPazhou Lab, Guangzhou, People's Republic of China.
Jun XiaoPazhou Lab, Guangzhou, People's Republic of China.
Jing WangInternational Unresponsive Wakefulness Syndrome and Consciousness Science Institute, Hangzhou Normal University, Hangzhou, People's Republic of China.
Fei WangPazhou Lab, Guangzhou, People's Republic of China.
Jingcong LiPazhou Lab, Guangzhou, People's Republic of China.
Lina QiuSchool of Software, South China Normal University, Guangzhou, People's Republic of China.
Haibo DiInternational Unresponsive Wakefulness Syndrome and Consciousness Science Institute, Hangzhou Normal University, Hangzhou, People's Republic of China.
Yuanqing LiPazhou Lab, Guangzhou, People's Republic of China.
South China Normal University · CNHangzhou Normal University · CNSouth China University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, neuroimaging studies have remarkably demonstrated the presence of cognitive motor dissociation in patients with disorders of consciousness (DoC). These findings accelerated the development of brain-computer interfaces (BCIs) as clinical tools for behaviorally unresponsive patients. This article reviews the recent progress of BCIs in patients with DoC and discusses the open challenges. In view of the practical application of BCIs in patients with DoC, four aspects of the relevant literature are introduced: consciousness detection, auxiliary diagnosis, prognosis, and rehabilitation. For each aspect, the paradigm design, brain signal processing methods, and experimental results of representative BCI systems are analyzed. Furthermore, this article provides guidance for BCI design for patients with DoC and discusses practical challenges for future research.

Indexed as

Brain-Computer InterfacesConsciousnessConsciousness DisordersElectroencephalographyHumansPrognosis

Identifiers

PMID35835448
PMCPMC9470379
OpenAlexW4285494860

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.