ArticleSensors (Basel, Switzerland)2025
3D-Printed Wearable Sensors for the Identification of Shoulder Movement Planes.
Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Tele-Rehabilitation and Tele-Diagnostics in Shoulder Disorders: Current Evidence, Challenges, and Future Directions-A Narrative Review.Journal of clinical medicine · 2026Review
- Digital Health and Smart Technologies in Shoulder Arthroplasty: Emerging Tools and Clinical Implications.Orthopedic research and reviews · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rotator cuff injuries are a leading cause of shoulder disability, directly impacting joint mobility and overall quality of life. Effective recovery in these patients depends not only on surgical intervention, when necessary, but also on accurate and continuous monitoring of joint movements during rehabilitation, especially across multiple anatomical planes. Traditional tools, such as clinical assessments or motion capture systems, are often subjective or expensive and impractical for routine use. In this context, wearable devices are emerging as a viable alternative, offering the ability to collect real-time, non-invasive, and repeatable data, both in clinical and home settings. This study presents innovative wearable sensors, developed through 3D printing and integrated with fiber Bragg grating technology, designed to detect the shoulder's planes of motion (sagittal, scapular, and frontal) during flexion-extension movements. Two wearable sensors made of thermoplastic polyurethane (TPU 85A and 95A) were fabricated and subjected to metrological characterization, including strain and temperature sensitivity, hysteresis error, and tear resistance, and tested on eight healthy volunteers. The results demonstrated high discriminative ability, with sensitivity values up to 0.76 nm/mε and low hysteresis errors. The proposed system represents a promising, cost-effective, and customizable solution for motion monitoring during shoulder rehabilitation.
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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.