Evidence map›Paper›PMID 35310106›Full record

ArticleFrontiers in neuroscience2022

Design and Evaluation of a Custom-Made Electromyographic Biofeedback System for Facial Rehabilitation.

Kathrin Machetanz, Florian Grimm, Ruth Schäfer, Leonidas Trakolis, Helene Hurth, Patrick Haas, Alireza Gharabaghi, Marcos Tatagiba, Georgios Naros

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroscience, 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
0.5field-weighted citation impact, top 36% 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, 5 citations in OpenAlex.

  1. Article
  2. 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

9 authors at 2 institutions in 1 country.

Kathrin MachetanzDepartment of Neurosurgery and Neurotechnology, Eberhard Karls University of Tübingen, Tübingen, Germany.
Florian GrimmDepartment of Neurosurgery and Neurotechnology, Eberhard Karls University of Tübingen, Tübingen, Germany.
Ruth SchäferDepartment of Hand, Plastic, Reconstructive and Burn Surgery, BG Clinic, Tübingen, Germany.
Leonidas TrakolisDepartment of Neurosurgery and Neurotechnology, Eberhard Karls University of Tübingen, Tübingen, Germany.
Helene HurthDepartment of Neurosurgery and Neurotechnology, Eberhard Karls University of Tübingen, Tübingen, Germany.
Patrick HaasDepartment of Neurosurgery and Neurotechnology, Eberhard Karls University of Tübingen, Tübingen, Germany.
Alireza GharabaghiInstitute for Neuromodulation and Neurotechnology, Eberhard Karls University of Tübingen, Tübingen, Germany.
Marcos TatagibaDepartment of Neurosurgery and Neurotechnology, Eberhard Karls University of Tübingen, Tübingen, Germany.
Georgios NarosDepartment of Neurosurgery and Neurotechnology, Eberhard Karls University of Tübingen, Tübingen, Germany.
University of Tübingen · DEBG Klinik Tübingen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In the rehabilitation of postoperative facial palsy, physical therapy is of paramount importance. However, in the early rehabilitation phase, voluntary movements are often limited, and thus, the motivation of patients is impacted. In these situations, biofeedback of facial electromyographic (EMG) signals enables the visual representation of the rehabilitation progress, even without apparent facial movements. In the present study, we designed and evaluated a custom-made EMG biofeedback system enabling cost-effective facial rehabilitation. Methods: This prospective study describes a custom-made EMG system, consisting of a microcontroller board and muscle sensors, which was used to record the EMG of Results: In healthy subjects, a good correlation was measured between the mean EMG amplitudes of the custom-made and commercial EMG device for both Conclusion: The present study demonstrates a good application potential of our custom-made EMG biofeedback device to detect facial EMG activity in healthy subjects as well as patients with facial palsies. There is a correlation between the electrophysiological measurements and the clinical outcome. Such a device might enable cost-efficient home-based facial EMG biofeedback. However, movement detection accuracy should be improved in future studies to reach ranges of commercial devices.

Indexed as

biofeedbackelectromyographyfacial nerve palsyphysical computing platformvestibular schwannoma

Identifiers

PMID35310106
PMCPMC8931662
OpenAlexW4214900506

What OpenQuestion holds

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LicenceCC BY
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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.