Evidence map›Paper›PMID 29662766›Full record

ArticleJournal of orthopaedic translation2017

Clinical validation of a body-fixed 3D accelerometer and algorithm for activity monitoring in orthopaedic patients.

Matthijs Lipperts, Simon van Laarhoven, Rachel Senden, Ide Heyligers, Bernd Grimm

Open access · goldAbstract read
In one paragraph

Article in Journal of orthopaedic translation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
11.6field-weighted citation impact, top 2% 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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.

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  18. Electronically augmented gait abnormality assessment following lower extremity trauma.OTA international : the open access journal of orthopaedic trauma · 2019
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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 at 1 institution in 1 country.

Matthijs LippertsSchool for Medical Physics and Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
Simon van LaarhovenAtrium Medical Centre Heerlen Orthopaedic Research and Scientific Education, Department of Orthopaedics, Zuyderland Medical Center, Heerlen, The Netherlands.
Rachel SendenAtrium Medical Centre Heerlen Orthopaedic Research and Scientific Education, Department of Orthopaedics, Zuyderland Medical Center, Heerlen, The Netherlands.
Ide HeyligersAtrium Medical Centre Heerlen Orthopaedic Research and Scientific Education, Department of Orthopaedics, Zuyderland Medical Center, Heerlen, The Netherlands.
Bernd GrimmAtrium Medical Centre Heerlen Orthopaedic Research and Scientific Education, Department of Orthopaedics, Zuyderland Medical Center, Heerlen, The Netherlands.
Eindhoven University of Technology · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectiveActivity is increasingly being recognized as a highly relevant parameter in all areas of healthcare for diagnosis, treatment, or outcome assessment, especially in orthopaedics where the movement apparatus is directly affected. Therefore, the aim of this study was to develop, describe, and clinically validate a generic activity-monitoring algorithm, satisfying a combination of three criteria. The algorithm must be able to identify, count, and time a large set of relevant daily activities. It must be validated for orthopaedic patients as well as healthy individuals, and the validation must be in a setting that mimics free-living conditions.

methodsUsing various technical solutions, such as a dual-axis approach, dynamic inclinometry (hip flexion), and semiautomatic calibration (gait speed), the algorithms were designed to count and time the following postures, transfers, and activities of daily living: resting/sitting, standing, walking, ascending and descending stairs, sit-stand transitions, and cycling. In addition, the number of steps per walking bout was determined. Validation was performed with healthy individuals and patients who had undergone unilateral total joint arthroplasty, representing a wide spectrum of functional capacity. Video observation was used as the gold standard to count and time activities in a validation protocol approaching free-living conditions.

resultsIn total 992 and 390 events (activities or postures) were recorded in the healthy group and patient group, respectively. The mean error varied between 0% and 2.8% for the healthy group and between 0% and 7.5% for the patient group. The error expressed in percentage of time varied between 2.0% and 3.0% for both groups.

conclusionActivity monitoring of orthopaedic patients by counting and timing a large set of relevant daily life events is feasible in a user- and patient-friendly way and at high clinical validity using a generic three-dimensional accelerometer and algorithms based on empirical and physical methods. The algorithms performed well for healthy individuals as well as patients recovering after total joint replacement in a challenging validation set-up. With such a simple and transparent method real-life activity parameters can be collected in orthopaedic practice for diagnostics, treatments, outcome assessment, or biofeedback.

Indexed as

accelerometryactivity monitoringclinical outcome assessment

Identifiers

PMID29662766
PMCPMC5866408
OpenAlexW2594023583

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.