Evidence map›Paper›PMID 32095759›Full record

ArticleDigital biomarkers

Continuous Monitoring of Patient Mobility for 18 Months Using Inertial Sensors following Traumatic Knee Injury: A Case Study.

Arne Mueller, Holger Hoefling, Timur Nuritdinow, Nicholas Holway, Matthias Schieker, Martin Daumer, Ieuan Clay

Open access · goldAbstract readCase Reports
In one paragraph

Article in Digital biomarkers. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 21% 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

6 citing papers in PubMed, 17 citations in OpenAlex.

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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

7 authors at 2 institutions in 2 countries.

Arne MuellerTranslational Medicine, Novartis Institutes for Biomedical Research, Forum 1, Novartis Campus, Basel, Switzerland.
Holger HoeflingNIBR Informatics, Novartis Institutes for Biomedical Research, Forum 1, Novartis Campus, Basel, Switzerland.
Timur NuritdinowSylvia Lawry Centre eV, The Human Motion Institute, Munich, Germany.
Nicholas HolwayNIBR Informatics, Novartis Institutes for Biomedical Research, Forum 1, Novartis Campus, Basel, Switzerland.
Matthias SchiekerTranslational Medicine, Novartis Institutes for Biomedical Research, Forum 1, Novartis Campus, Basel, Switzerland.
Martin DaumerTRIUM Online Analysis GmbH, Munich, Germany.
Ieuan ClayTranslational Medicine, Novartis Institutes for Biomedical Research, Forum 1, Novartis Campus, Basel, Switzerland.
Novartis (Switzerland) · CHSylvia Lawry Centre for Multiple Sclerosis Research · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Continuous patient activity monitoring during rehabilitation, enabled by digital technologies, will allow the objective capture of real-world mobility and aligning treatment to each individual's recovery trajectory in real time. To explore the feasibility and added value of such approaches, we present a case study of a 36-year-old male participant monitored continuously for activity levels and gait parameters using a waist-worn inertial sensor following a tibial plateau fracture on the right side, sustained as a result of a high-energy trauma during a sporting accident. During rehabilitation, data were collected for a period of 553 days, with > 80% daytime compliance, until the participant returned to near full mobility. The participant completed a daily diary with the annotation of major events (falls, near falls, cycling periods, or physiotherapy sessions) and key dates in the patient's recovery, including medical interventions, transitioning off crutches, and returning to work. We demonstrate the feasibility of collecting, storing, and mining of continuous digital mobility data and show that such data can detect changes in mobility and provide insights into long-term rehabilitation. We make both raw data and annotations available as a resource with the aspiration that further methods and insights will be built on this initial exploration of added value and continue to demonstrate that continuous monitoring can be deployed to aid rehabilitation.

Indexed as

Activity monitorsAlgorithmsDataMobilityWearable physical activity monitoringWearable sensors

Identifiers

PMID32095759
PMCPMC7015374
OpenAlexW2886283099

What OpenQuestion holds

Textmetadata
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.