Evidence map›Paper›PMID 20225080›Full record

ArticleEuropean journal of applied physiology2010

Enhancing the weight training experience: a comparison of limb kinematics and EMG activity on three machines.

Yasushi Koyama, Hirofumi Kobayashi, Shuji Suzuki, Roger M Enoka

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in European journal of applied physiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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.

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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

4 authors.

Yasushi KoyamaGraduate School of Human Sciences, Waseda University, 2-579-15, Mikajima, Tokorozawa, 359-1192, Japan.
Hirofumi Kobayashi
Shuji Suzuki
Roger M Enoka

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of the study was to compare the kinematics and the timing and amount of electromyographic (EMG) activity during the lat-pull down exercise performed on machines that afforded one, two, or three degrees of freedom for the movement. Seven healthy men (age 29.4 +/- 5.6 years) participated in the study. The exercise was performed with a 30% 1-RM load. Three types of machines with varying degrees of freedom were used: Type 1, the conventional device that restricted the movement to a frontal plane; Type 2, the addition of forearm supination-pronation; Type 3, the addition of forearm supination-pronation and horizontal extension-flexion about the shoulder. All exercises involved a technique known as beginning movement load (BML) training in which light loads are lifted with a relaxation-lengthening-shortening sequence of muscle activation. The Type-3 machine showed: (1) the greatest vertical displacement of the wrist (p < 0.05); (2) the greatest abduction-adduction displacement about the shoulder (p < 0.01); (3) the least flexion-extension displacement about the elbow joint (p < 0.01); (4) a peak vertical velocity for the shoulder that preceded (p < 0.01) those for the elbow and then wrist during the pull-down phase; (5) a progressive proximal-to-distal sequence of EMG activation involving the serratus anterior, posterior deltoid, latissimus dorsi, and triceps brachii muscles; (6) a reversal of the roles for biceps and triceps brachii during the pull-down phase. These results suggest that BML exercises with greater degrees of freedom can enhance the association between training actions and functional activities.

Indexed as

Biomechanical PhenomenaElectromyographyAdultElbow JointHumansMaleMuscle, SkeletalRange of Motion, ArticularResistance Training

Identifiers

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.