Evidence map›Paper›PMID 34630993›Full record

ArticleJournal of healthcare engineering2021

A Virtual Reality Algorithm for the Study of Clinical Efficacy of Sports Injury Rehabilitation Training.

Yang Han

RetractedAbstract readRetracted Publication
In one paragraph

Article in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Yang HanCollege of Humanities and Art, Henan Quality Polytechnic University, Pingdingshan, Henan 467000, China.ORCID 0000-0002-3214-8806

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper aims to explore the influence of virtual reality technology interactive rehabilitation training system and PT and OT operation therapy on the exercise function, daily life activity ability (ADL), and the quality of life in patients with a sports injury. In this context, this paper mainly designed three experiments to test the virtual rehabilitation system: two action experiments (experiment 1), two experiments with actions in 3 different positions (experiment 2), and five different actions (experiment 3), and the motion intention recognition rate, average total time, and task completion degree of the three experiments were calculated. The virtual scene and hardware equipment were kept stable, and the human-machine interaction effect was good. The effectiveness of the proposed virtual reality rehabilitation training system is demonstrated from other aspects. The results showed that the average completion time of 5 volunteers was 57.72 seconds, with an average offline accuracy of 89.03%. In experiment 2, the five volunteers averaged 54.98 seconds, with an average offline accuracy of 91.73%. The average recognition accuracy of the training system reached 90%, demonstrating the effectiveness of the virtual reality rehabilitation training system in terms of motor intention recognition rate, average total use time, and task completion.

Indexed as

Athletic InjuriesVirtual RealityAlgorithmsHumansQuality of LifeTreatment Outcome

Identifiers

PMID34630993
PMCPMC8500756

What OpenQuestion holds

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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.