Evidence map›Paper›PMID 35707198›Full record

ArticleComputational intelligence and neuroscience2022

Design of Sports Rehabilitation Training System Based on EEMD Algorithm.

Kaiwei Wang, Zhenghui Wang, Wu Ren, Chunsheng Yang

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Kaiwei WangSchool of Physical Education, Xinxiang Medical University, Xinxiang, Henan 453003, China.ORCID https://orcid.org/0000-0002-0895-1156
Zhenghui WangThe First Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan 453003, China.
Wu RenCollege of Medical Engineering, Xinxiang Medical University, Xinxiang, Henan 453003, China.ORCID https://orcid.org/0000-0002-6634-3159
Chunsheng YangRehabilitation Department, The Third Affilitated Hospital of Xinxiang Medical University, Xinxiang, Henan 453003, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motor function rehabilitation training is to restore the motor function of hand injury to the maximum extent and meet the needs of patients' daily behavior. At present, motor function evaluation and rehabilitation training work have disadvantages such as relying on the subjective experience of physicians, unable to quantitatively assess the loss of motor function, and single rehabilitation training method. Most of these methods only focus on the independent motion range of a single organ, lack of consideration of the constraint relationship between adjacent fingers, and do not build a visual model for it. To end this issue, for the purpose of sports rehabilitation, combined with the status and application of rehabilitation machines, this paper proposed a cycling rehabilitation training system based on physiological signal extraction of ensemble empirical mode decomposition (EEMD) algorithm. Results compared with the previous rehabilitation training, the muscle tension level of patients' upper limbs decreased, and the strength of some muscles also increased. With the progress of rehabilitation training, the contralateral dominance coefficient showed an upward trend, which further confirmed the role of the proposed method in sports rehabilitation, and also provided a new idea for the evaluation of rehabilitation training effect of patients in the future.

Indexed as

Exercise TherapyHand InjuriesAlgorithmsHumansUpper Extremity

Identifiers

PMID35707198
PMCPMC9192223

What OpenQuestion holds

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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.