Evidence map›Paper›PMID 32364158›Full record

ArticleTechnology and health care : official journal of the European Society for Engineering and Medicine2020

Analysis of physiological data from long- term physical exercise: A basis for improving the health of rural residents of Korea.

Kyong Kim, Tae-Won Kim, Seong Hyun Kim

Open access · bronzeAbstract readCase Reports
In one paragraph

Article in Technology and health care : official journal of the European Society for Engineering and Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 33% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

3 authors at 1 institution in 1 country.

Kyong KimDepartment of Medical and Electronic Device, Chungbuk Provincial University, Okcheon-gun, Chungbuk, 29046, Korea.
Tae-Won KimDepartment of Fusion Design, Chungbuk Provincial University, Okcheon-gun, Chungbuk, 29046, Korea.
Seong Hyun KimDepartment of Medical and Electronic Device, Chungbuk Provincial University, Okcheon-gun, Chungbuk, 29046, Korea.
Chungbuk Provincial College · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAnalysis of the change pattern of a user's physiological signals collected over a long time and user health information prediction technology based on personal history data can provide the user with accurate health information.

objectiveIn this study, we analyzed the change pattern of health information that was altered by performing personal training (PT) at the beginning of the study and subsequently quitting exercise and only performing activities of daily living (ADL).

methodsThe subject performed PT for 75 days, and then consistently performed relatively simple ADL, such as standing, sitting, and walking, for 325 days that followed. After 400 days, the health information was analyzed through the change patterns of various physiological signals. Personal exercise information and heart rate data were collected through a smart watch (Apple watch Nike+, Apple Inc.) and the obesity parameters (i.e. information on the weight, body fat fate, and body muscle rate) were measured using a smart scale (PICOOC S1 Pro, EasySolar).

resultsWe found that the weight and body fat rate linearly decreased and the body muscle rate increased for the first 75 days when hard training was performed whereas they repeatedly increased or decreased when only ADL were performed. As the daily exercise distance increased, weight and body fat rate tended to decrease while body muscle rate tended to increase. There was no significant change in the weight, body fat rate, and body muscle rate while daily activities were performed, but continuous exercise is expected to improve cardiac function by increasing the cardiac output of the heart.

conclusionWe expected that the simple physiological data measured with smart watches and smart scales can be used for the health management of the elderly living in rural areas in the future.

Indexed as

Health StatusActivities of Daily LivingAdultBody CompositionBody Weights and MeasuresExerciseFitness TrackersHeart RateHumansLongitudinal StudiesObesityRepublic of Koreadaily activitiesHealth managementheart ratelong-term physiological signalspersonal health pattern

Identifiers

PMID32364158
PMCPMC7369064
OpenAlexW3023573642

What OpenQuestion holds

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LicenceCC BY-NC
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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.