Evidence map›Paper›PMID 42351941›Full record

ArticleBioengineering (Basel, Switzerland)2026

Practicality of Using Pressure Sensors and Accelerometers to Quantify Hand Orthosis Compliance at Home.

Devi Baruni Devanand, Matthew D Gardiner, Angela E Kedgley

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Devi Baruni DevanandDepartment of Bioengineering, Imperial College London, London SW7 2AZ, UK.
Matthew D GardinerKennedy Institute of Rheumatology, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford, Oxford OX3 7FY, UK.ORCID 0000-0002-8058-4186
Angela E KedgleyDepartment of Bioengineering, Imperial College London, London SW7 2AZ, UK.ORCID 0000-0001-7282-6651

Funding

Engineering and Physical Sciences Research Council EP/S02249X/1Wellcome Trust 208858/Z/17/Z
6 · The paper itself

Abstract

Orthosis compliance monitoring provides insights into effective orthosis design and user wear time. Frequently, patient reports of orthosis use are subjective and often result in overestimation of compliance. Therefore, a tool to objectively observe whether patients wear their orthoses as instructed is vital. This study assessed the real-world practicality of using an objective compliance monitoring device with a hand orthosis. A device consisting of a pressure sensor and accelerometer was tested by ten healthy volunteers who wore a hand orthosis daily and completed a diary of their wear time and activities for a week. Sensor data obtained from the compliance monitoring device were analysed to discern each user's orthosis wear time. Differences between estimated wear time and actual wear time were insignificant. Pressure-based wear time estimations had a specificity of 99.3 ± 0.7% and a sensitivity of 80.3 ± 19.2%, whilst acceleration-derived estimations had a specificity of 94.5 ± 6.4% and a sensitivity of 73.2 ± 15.8%. This study demonstrated that orthosis compliance can be monitored outside the laboratory, and, furthermore, this device offers insights into the intensity and frequency of a user's activities and has the future potential to monitor orthosis fit and forces applied to affected joints using pressure.

Indexed as

accelerometeractivities of daily livingadherencecomplianceobjective compliance monitoringorthosispressure sensorupper limbwear time

Identifiers

PMID42351941
PMCPMC13296036

What OpenQuestion holds

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Registered trials

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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.