Evidence map›Paper›PMID 31992323›Full record

ArticleJournal of neuroengineering and rehabilitation2020

Age-specific differences in the time-frequency representation of surface electromyographic data recorded during a submaximal cyclic back extension exercise: a promising biomarker to detect early signs of sarcopenia.

R Habenicht, G Ebenbichler, P Bonato, J Kollmitzer, S Ziegelbecker, L Unterlerchner, P Mair, T Kienbacher

Open access · goldAbstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
0.9field-weighted citation impact, top 30% 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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 22 citations in OpenAlex.

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  4. Assessment of muscle fatigue in multiple sclerosis patients in electromyographic examinations.European journal of physical and rehabilitation medicine · 2023
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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

8 authors at 4 institutions in 2 countries.

R HabenichtKarl-Landsteiner-Institute of Outpatient Rehabilitation Research, Vienna, Austria.
G EbenbichlerKarl-Landsteiner-Institute of Outpatient Rehabilitation Research, Vienna, Austria. gerold.ebenbichler@meduniwien.ac.at.
P BonatoDepartment of Physical Medicine and Rehabilitation, Harvard Medical School, Spaulding Rehabilitation Hospital, Boston, MA, USA.
J KollmitzerTechnical School of Engineering, Vienna, Austria.
S ZiegelbeckerKarl-Landsteiner-Institute of Outpatient Rehabilitation Research, Vienna, Austria.
L UnterlerchnerKarl-Landsteiner-Institute of Outpatient Rehabilitation Research, Vienna, Austria.
P MairDepartment of Psychology, Harvard University, Cambridge, MA, USA.
T KienbacherKarl-Landsteiner-Institute of Outpatient Rehabilitation Research, Vienna, Austria.
Karl Landsteiner Society · ATHarvard University · USSpaulding Rehabilitation Hospital · USUniversity of Applied Sciences Technikum Wien · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeMotivated by the goal of developing new methods to detect early signs of sarcopenia, we investigated if surface electromyographic (SEMG) data recorded during the performance of cyclic, submaximal back extensions are marked by age-specific differences in their time and frequency characteristics. Furthermore, day-to-day retest reliability of the EMG measures was examined.

methodsA total of 86 healthy volunteers used a back dynamometer to perform a series of three maximal voluntary contractions (MVC) consisting of isometric back extensions, followed by an isometric back extension at 80% MVC, and finally 25 slow cyclic back extensions at 50% MVC. SEMG data was recorded bilaterally at L1, L2, and L5 from the iliocostalis lumborum, longissimus, and multifidus muscles, respectively. Tests were repeated two days and six weeks later. A linear mixed-effects model with fixed effects "age, sex, test number" and the random effect "person" was performed to investigate age-specific differences in both the initial value and the time-course (as defined by the slope of the regression line) of the root mean square (RMS-SEMG) values and instantaneous median frequency (IMDF-SEMG) values calculated separately for the shortening and lengthening phases of the exercise cycles. Generalizability Theory was used to examine reliability of the EMG measures.

resultsBack extensor strength was comparable in younger and older adults. The initial value of RMS-SEMG and IMDF-SEMG as well as the RMS-SEMG time-course did not significantly differ between the two age groups. Conversely, the IMDF-SEMG time-course showed more rapid changes in younger than in older individuals. Absolute and relative reliability of the SEMG time-frequency representations were comparable in older and younger individuals with good to excellent relative reliability but variable absolute reliability levels.

conclusionsThe IMDF-SEMG time-course derived from submaximal, cyclic back extension exercises performed at moderate effort showed significant differences in younger vs. older adults even though back extension strength was found to be comparable in the two age groups. We conclude that the SEMG method proposed in this study has great potential to be used as a biomarker to detect early signs of sarcopenic back muscle function.

Indexed as

Early DiagnosisAdolescentAdultAgedAged, 80 and overAgingAlgorithmsBack MusclesElectromyographyExerciseFemaleHealthy VolunteersHumansMaleMiddle AgedMuscle FatigueAgingConcentric exerciseEccentric exerciseMuscle fatigueMuscle functionSurface electromyography

Identifiers

PMID31992323
PMCPMC6986160
OpenAlexW3006344963

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.