Observational studyJournal of rehabilitation medicine2022
Accurate Estimation of Upper Limb Orthosis Wear Time Using Miniature Temperature Loggers.
Observational study in Journal of rehabilitation medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Objective Methods of Monitoring Usage of Orthotic Devices for the Extremities: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- A Compact Orthosis Compliance Monitoring Device Using Pressure Sensors and Accelerometers: Design and Proof-of-Concept Testing.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo propose and validate a new method for estimating upper limb orthosis wear time using miniature temperature loggers attached to locations on the upper body.
designObservational study. SUBJECTS: Fifteen healthy participants.
methodsFour temperature loggers were attached to the arm and chest with straps. Participants were asked to remove and re-attach the straps at specified time-points. The labelled temperature data obtained were used to train a decision tree classification algorithm to estimate wear time. The final performance (mean error and 95% confidence interval) of the trained classifier and the wear time estimation were assessed with a hold-out data-set.
resultsThe trained algorithm can correctly classify unseen temperature data with a mean classification error between 1.1% and 3.1% for the arm, and between 1.8% and 4.0% for the chest, depending on the sampling time of the temperature logger. This resulted in mean wear time errors between 0.5% and 8.3% for the arm, and 0.13% and 13.0% for the chest.
conclusionThe proposed method based on a classifier can accurately estimate upper limb orthosis wear time. This method could enable healthcare professionals to gain insight into the wear time of any upper limb orthosis.
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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.