Evidence map›Paper›PMID 31817164›Full record

ArticleSensors (Basel, Switzerland)2019

Optimization and Validation of an Adjustable Activity Classification Algorithm for Assessment of Physical Behavior in Elderly.

Wouter Bijnens, Jos Aarts, An Stevens, Darcy Ummels, Kenneth Meijer

Registry-linked trialAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05931068 (Pre- and Postoperative Energy Expenditure in Major Liver Resection), which is not on this map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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.

NCT05931068 recruitingnot on this mapstarted 2023, after this paper: background citation

Pre- and Postoperative Energy Expenditure in Major Liver Resection: What do we Ask From a Patient?

TypeobservationalSponsorAcademisch Ziekenhuis MaastrichtRan2023 to 2025Enrolled20ConditionsCancer, Liver Diseases, Liver NeoplasmsArmsPre- and postoperative assessment
3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

  1. Trial
  2. Article
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  4. Physical Activity and Fear Avoidance Over Time in Patients With Acute/Subacute Versus Chronic Unilateral Vestibulopathy: A Prospective Study.Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology · 2026
    Article
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  15. Observational
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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

5 authors.

Wouter BijnensInstrument Development, Engineering and Evaluation, Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands.
Jos AartsInstrument Development, Engineering and Evaluation, Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands.
An StevensInstrument Development, Engineering and Evaluation, Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands.
Darcy UmmelsResearch Centre for Autonomy and Participation of Persons with a Chronic Illness, Zuyd University of Applied Sciences, PO Box 550, 6419 DJ Heerlen, The Netherlands.
Kenneth MeijerDepartment of Nutrition and Movement Sciences, Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands.

Funding

Provincie Limburg SAS-2016-00701
6 · The paper itself

Abstract

Due to a lack of transparency in both algorithm and validation methodology, it is difficult for researchers and clinicians to select the appropriate tracker for their application. The aim of this work is to transparently present an adjustable physical activity classification algorithm that discriminates between dynamic, standing, and sedentary behavior. By means of easily adjustable parameters, the algorithm performance can be optimized for applications using different target populations and locations for tracker wear. Concerning an elderly target population with a tracker worn on the upper leg, the algorithm is optimized and validated under simulated free-living conditions. The fixed activity protocol (FAP) is performed by 20 participants; the simulated free-living protocol (SFP) involves another 20. Data segmentation window size and amount of physical activity threshold are optimized. The sensor orientation threshold does not vary. The validation of the algorithm is performed on 10 participants who perform the FAP and on 10 participants who perform the SFP. Percentage error (PE) and absolute percentage error (APE) are used to assess the algorithm performance. Standing and sedentary behavior are classified within acceptable limits (±10% error) both under fixed and simulated free-living conditions. Dynamic behavior is within acceptable limits under fixed conditions but has some limitations under simulated free-living conditions. We propose that this approach should be adopted by developers of activity trackers to facilitate the activity tracker selection process for researchers and clinicians. Furthermore, we are convinced that the adjustable algorithm potentially could contribute to the fast realization of new applications.

Indexed as

AlgorithmsAccelerometryActivities of Daily LivingAgedFemaleFitness TrackersHumansMaleSedentary BehaviorWearable Electronic Devicesaccelerometersalgorithmelderlyphysical activitysedentary behaviorvalidation

Identifiers

PMID31817164
PMCPMC6961012

What OpenQuestion holds

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Registered trials

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.