Evidence map›Paper›PMID 29706712›Full record

ArticleJournal of physical therapy science2018

The best body spot to detect the vital capacity from the respiratory movement data obtained by the wearable strain sensor.

Haijuan Liu, Shaopeng Guo, Huilin Liu, Hao Zhang, Sujie Chen, Tsugumi Kuramoto-Ahuja, Tamae Sato, Junichiro Kaneko, Ko Onoda, Hitoshi Maruyama

Open access · diamondAbstract read
In one paragraph

Article in Journal of physical therapy science, 2018. 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
0.6field-weighted citation impact, top 36% 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

0 citing papers in PubMed, 5 citations in OpenAlex.

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

10 authors at 3 institutions in 2 countries.

Haijuan LiuDepartment of Physical Therapy, International University of Health and Welfare: 2600-1 Kitakanemaru, Ohtawara City, Tochigi 324-8501, Japan.
Shaopeng GuoChina Rehabilitation Research Center, China.
Huilin LiuChina Rehabilitation Research Center, China.
Hao ZhangChina Rehabilitation Research Center, China.
Sujie ChenShanghai Jiao Tong University, China.
Tsugumi Kuramoto-AhujaDepartment of Physical Therapy, International University of Health and Welfare: 2600-1 Kitakanemaru, Ohtawara City, Tochigi 324-8501, Japan.
Tamae SatoDepartment of Physical Therapy, International University of Health and Welfare: 2600-1 Kitakanemaru, Ohtawara City, Tochigi 324-8501, Japan.
Junichiro KanekoDepartment of Physical Therapy, International University of Health and Welfare: 2600-1 Kitakanemaru, Ohtawara City, Tochigi 324-8501, Japan.
Ko OnodaDepartment of Physical Therapy, International University of Health and Welfare: 2600-1 Kitakanemaru, Ohtawara City, Tochigi 324-8501, Japan.
Hitoshi MaruyamaDepartment of Physical Therapy, International University of Health and Welfare: 2600-1 Kitakanemaru, Ohtawara City, Tochigi 324-8501, Japan.
International University of Health and Welfare · JPChina Rehabilitation Research Center · CNShanghai Jiao Tong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

[Purpose] The purpose of this study is to find the best body spots on the chest and abdomen wall to obtain the correlated indicators to the vital capacity. [Subjects and Methods] Thirty healthy male staff of the center served as the participants were advised to conduct a breathing movement using spirometer and a wearable strain sensor (WSS) respectively, which was the measured at four spots on chest and abdomen wall from maximal end of inspiration to maximal end of expiration. The Pearson's correlation analysis was conducted to find the correlation of the data obtained respectively by the WSS and spirometer. [Results] The correlation of the mobility data at the four body spots to the vital capacity data were calculated for each level by means of Pearson's correlation coefficient, which showed that the values at each body spot were positive significant correlations and the highest value was at the 10th rib. [Conclusion] There was a correlation between the mobility data of the chest and abdomen obtained by the WSS and the vital capacity data obtained by the spirometer, for which, the 10th rib is the best body spot to detect the positive significant correlation.

Indexed as

CorrelationMeasuring respiratory movementWearable strain sensor

Identifiers

PMID29706712
PMCPMC5909008
OpenAlexW2801073346

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.