Evidence map›Paper›PMID 36896022›Full record

ArticleInternational journal of exercise science2022

Muscle Activity During Immersive Virtual Reality Exergaming Incorporating an Adaptive Cable Resistance System.

David Gomez, Jonathan D Browne, Abdulrahman Almalouhi, Max Abundex, Jonathan Hu, Sally Nason, Nicholas Kull, Cade Mills, Quincy Harris, Richard Ku and 2 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of exercise science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Trial
  2. Trial
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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

12 authors at 2 institutions in 1 country.

David GomezAirway & Exercise Physiology Research Laboratory, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA.
Jonathan D BrowneAirway & Exercise Physiology Research Laboratory, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA.
Abdulrahman AlmalouhiAirway & Exercise Physiology Research Laboratory, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA.
Max AbundexAirway & Exercise Physiology Research Laboratory, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA.
Jonathan HuAirway & Exercise Physiology Research Laboratory, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA.
Sally NasonAirway & Exercise Physiology Research Laboratory, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA.
Nicholas KullAirway & Exercise Physiology Research Laboratory, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA.
Cade MillsAirway & Exercise Physiology Research Laboratory, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA.
Quincy HarrisAirway & Exercise Physiology Research Laboratory, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA.
Richard KuAirway & Exercise Physiology Research Laboratory, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA.
Eric V NeufeldAirway & Exercise Physiology Research Laboratory, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA.
Brett A DolezalAirway & Exercise Physiology Research Laboratory, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA.
University of California, Los Angeles · USHofstra University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this exploratory study was to characterize muscle activation via surface electromyography (sEMG), user-perceived exertion, and enjoyment during a 30-minute session of immersive virtual reality (IVR) cable resistance exergaming. Ten healthy, college-aged males completed a signature 30-minute exergaming session using an IVR adaptive cable resistance system that incorporated six traditional compound exercises. Muscle activation (sEMG) was captured during the session with a wearable sEMG system. Rated of Perceived Exertion (RPE) and Physical Activity Enjoyment Scale (PACES) were recorded following the session. Pectoralis major showed the highest activation during chest press, deltoids showed the highest activation on overhead press, latissimus dorsi showed the highest activation during lat pulldown and row exercises, hamstrings were the most activated muscles during Romanian deadlift, and glutes showed the highest activity during squats. RPE and PACES mean scores were 14 (1) and 4.27 (0.38), respectively. IVR exergaming with resistance cable training provides an enjoyable experience and distracts practitioners from exertion while exercising at a high intensity. Results from this study suggest similar muscle activation responses compared to traditional resistance exercises as demonstrated with prior evidence. This novel form of exercise might have important repercussions for improving health outcomes among those who find it challenging to adhere to and enjoy exercise routines, as well as with little knowledge on how to progress in their resistance training. Further investigations are needed to explore long-term adaptations and to assess if IVR exergaming has additional benefits compared to traditional resistance training.

Indexed as

adaptive resistanceAI resistanceelectromyographyexerciseGamificationresistance training

Identifiers

PMID36896022
PMCPMC9987444
OpenAlexW4323812836

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.