Evidence map›Paper›PMID 30453605›Full record

ArticleSensors (Basel, Switzerland)2018

Measuring Sedentary Behavior by Means of Muscular Activity and Accelerometry.

Roman P Kuster, Mirco Huber, Silas Hirschi, Walter Siegl, Daniel Baumgartner, Maria Hagströmer, Wim Grooten

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. 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

7 authors.

Roman P KusterDivision of Physiotherapy, Department of Neurobiology, Care Science and Society, Karolinska Institutet, 141 83 Stockholm, Sweden. roman.kuster@alumni.ethz.ch.ORCID 0000-0002-4189-2071
Mirco HuberInstitute of Energy Systems and Fluid Engineering, School of Engineering, ZHAW Zurich University of Applied Sciences, 8401 Winterthur, Switzerland. hubermir@students.zhaw.ch.
Silas HirschiInstitute of Energy Systems and Fluid Engineering, School of Engineering, ZHAW Zurich University of Applied Sciences, 8401 Winterthur, Switzerland. silas.hirschi@hotmail.com.
Walter SieglInstitute of Energy Systems and Fluid Engineering, School of Engineering, ZHAW Zurich University of Applied Sciences, 8401 Winterthur, Switzerland. siew@zhaw.ch.
Daniel BaumgartnerInstitute of Mechanical Systems, School of Engineering, ZHAW Zurich University of Applied Sciences, 8401 Winterthur, Switzerland. baud@zhaw.ch.
Maria HagströmerDivision of Physiotherapy, Department of Neurobiology, Care Science and Society, Karolinska Institutet, 141 83 Stockholm, Sweden. maria.hagstromer@ki.se.ORCID 0000-0002-4607-8677
Wim GrootenDivision of Physiotherapy, Department of Neurobiology, Care Science and Society, Karolinska Institutet, 141 83 Stockholm, Sweden. wim.grooten@ki.se.ORCID 0000-0002-1697-9781

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sedentary Behavior (SB) is among the most frequent human behaviors and is associated with a plethora of serious chronic lifestyle diseases as well as premature death. Office workers in particular are at an increased risk due to their extensive amounts of occupational SB. However, we still lack an objective method to measure SB consistent with its definition. We have therefore developed a new measurement system based on muscular activity and accelerometry. The primary aim of the present study was to calibrate the new-developed 8-CH-EMG+ for measuring occupational SB against an indirect calorimeter during typical desk-based office work activities. In total, 25 volunteers performed nine office tasks at three typical workplaces. Minute-by-minute posture and activity classification was performed using subsequent decision trees developed with artificial intelligence data processing techniques. The 8-CH-EMG+ successfully identified all sitting episodes (AUC = 1.0). Furthermore, depending on the number of electromyography channels included, the device has a sensitivity of 83⁻98% and 74⁻98% to detect SB and active sitting (AUC = 0.85⁻0.91). The 8-CH-EMG+ advances the field of objective SB measurements by combining accelerometry with muscular activity. Future field studies should consider the use of EMG sensors to record SB in line with its definition.

Indexed as

Sedentary BehaviorAccelerometryAdultElectromyographyFemaleHumansMaleMiddle AgedPostureWalkingWorkplaceYoung Adultactive sitting and standingartificial intelligencecalibration studydecision treeelectromyographyinactive sitting and standingindirect calorimetryobjective measurementoccupational physical activity and sedentary behavior monitorsensitivity and specificity

Identifiers

PMID30453605
PMCPMC6263709

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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.