Evidence map›Paper›PMID 34867760›Full record

ReviewFrontiers in neurology2021

Post-stroke Rehabilitation of Severe Upper Limb Paresis in Germany - Toward Long-Term Treatment With Brain-Computer Interfaces.

Cornelius Angerhöfer, Annalisa Colucci, Mareike Vermehren, Volker Hömberg, Surjo R Soekadar

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 3 pooled it
2.1field-weighted citation impact, top 13% 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

22 citing papers in PubMed, 3 syntheses or guidelines pooled it, 34 citations in OpenAlex.

  1. Pooled it
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  7. An integrated investigation of systemic and localized pathophysiological mechanisms of stroke and multimodal therapeutic strategies.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2026
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  16. Advanced rehabilitation in ischaemic stroke research.Stroke and vascular neurology · 2024
    Review
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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

5 authors at 2 institutions in 1 country.

Cornelius AngerhöferClinical Neurotechnology Lab, Department of Psychiatry and Neurosciences, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Annalisa ColucciClinical Neurotechnology Lab, Department of Psychiatry and Neurosciences, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Mareike VermehrenClinical Neurotechnology Lab, Department of Psychiatry and Neurosciences, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Volker HömbergDepartment of Neurology, SRH Gesundheitszentrum Bad Wimpfen GmbH, Bad Wimpfen, Germany.
Surjo R SoekadarClinical Neurotechnology Lab, Department of Psychiatry and Neurosciences, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Charité - Universitätsmedizin Berlin · DEPHV Dialysezentrum · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Severe upper limb paresis can represent an immense burden for stroke survivors. Given the rising prevalence of stroke, restoration of severe upper limb motor impairment remains a major challenge for rehabilitation medicine because effective treatment strategies are lacking. Commonly applied interventions in Germany, such as mirror therapy and impairment-oriented training, are limited in efficacy, demanding for new strategies to be found. By translating brain signals into control commands of external devices, brain-computer interfaces (BCIs) and brain-machine interfaces (BMIs) represent promising, neurotechnology-based alternatives for stroke patients with highly restricted arm and hand function. In this mini-review, we outline perspectives on how BCI-based therapy can be integrated into the different stages of neurorehabilitation in Germany to meet a long-term treatment approach: We found that it is most appropriate to start therapy with BCI-based neurofeedback immediately after early rehabilitation. BCI-driven functional electrical stimulation (FES) and BMI robotic therapy are well suited for subsequent post hospital curative treatment in the subacute stage. BCI-based hand exoskeleton training can be continued within outpatient occupational therapy to further improve hand function and address motivational issues in chronic stroke patients. Once the rehabilitation potential is exhausted, BCI technology can be used to drive assistive devices to compensate for impaired function. However, there are several challenges yet to overcome before such long-term treatment strategies can be implemented within broad clinical application: 1. developing reliable BCI systems with better usability; 2. conducting more research to improve BCI training paradigms and 3. establishing reliable methods to identify suitable patients.

Indexed as

brain-computer interfacelong-term treatmentneurorehabilitationneurotechnologysevere upper limb paresis

Identifiers

PMID34867760
PMCPMC8637332
OpenAlexW3212743916

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.