ArticlemHealth2022
Assessment of shoulder range of motion using a commercially available wearable sensor-a validation study.
Article in mHealth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled 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.
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
16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 20 citations in OpenAlex.
- Monitoring Scapular Kinematics through Wearable Magneto-Inertial Measurement Units: State of the Art and New Frontiers.Sensors (Basel, Switzerland) · 2023Pooled it
- Conversion of Upper-Limb Inertial Measurement Unit Data to Joint Angles: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- Implementation and Evaluation of an AI-Assisted Telerehabilitation System for Postdischarge Continuation of Rehabilitative Care: Protocol for a Randomized Controlled Trial.JMIR research protocols · 2026Article
- Tele-Rehabilitation and Tele-Diagnostics in Shoulder Disorders: Current Evidence, Challenges, and Future Directions-A Narrative Review.Journal of clinical medicine · 2026Review
- Detection of Feigned Impairment of the Shoulder Due to External Incentives: A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2026Review
- Validation of a Multimodal Wearable Device Integrating EMG and IMU Sensors for Monitoring Upper Limb Function During Tooth Brushing Activities of Daily Living.Sensors (Basel, Switzerland) · 2026Article
- Feasibility and usability of a wearable sensor-based telerehabilitation program for home-based exercise in patients with lower limb amputation: a pilot study.Frontiers in rehabilitation sciences · 2026Article
- Quantification of 3D Kinematic Measurements for Knee Flexion and Tibial Rotation Using an IMU-Based Sensor and Ultrasound Imaging System: A Cadaveric Study.Sensors (Basel, Switzerland) · 2025Article
- Artificial intelligence in shoulder arthroplasty: how smart is it?JSES international · 2025Article
- Multi-Planar Cervical Motion Dataset: IMU Measurements and Goniometer.Scientific data · 2025Article
- Using a wearable system combining inertial and force sensing for simultaneous detection of limb motion and grasping actions in the workplace.Wearable technologies · 2025Article
- Trends and Innovations in Wearable Technology for Motor Rehabilitation, Prediction, and Monitoring: A Comprehensive Review.Sensors (Basel, Switzerland) · 2024Review
- Assessing the Validity of the Ergotex IMU in Joint Angle Measurement: A Comparative Study with Optical Tracking Systems.Sensors (Basel, Switzerland) · 2024Observational
- Wearables for Monitoring and Postural Feedback in the Work Context: A Scoping Review.Sensors (Basel, Switzerland) · 2024Article
- Concurrent validity of inertial measurement units in range of motion measurements of upper extremity: A systematic review and meta-analysis.Wearable technologies · 2024Review
- Shoulder Range of Motion Measurement Using Inertial Measurement Unit-Concurrent Validity and Reliability.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Our study aims to validate a commercially available inertial measurement unit (IMU) system against a standard laboratory-based optical motion capture (OMC) system for shoulder measurements in a clinical context. Methods: The validation analyses were conducted on 19 healthy male volunteers. Twelve reflective markers were placed on each participant's trunk, scapula and across the arm and one IMU was attached via a self-adhesive strap on the forearm. A single tester simultaneously collected shoulder kinematic data for four shoulder movements: flexion, extension, external rotation, and abduction. Agreement between OMC system and IMU measurements was assessed with Bland-Altman analyses. Secondary analysis included mean biases, root mean square error (RMSE) analysis and Welch's Results: Bland-Altman limits of agreement (LoA) exceeded the acceptable range of mean difference for 95% of the population (-22.27°, 11.31°). The mean bias showed high levels of agreement within 8° for all four movements. More than 60% of participants demonstrated mean bias less than 10° between methods. Statistically significant differences were found between measurements for abduction (P<0.001) and flexion (P=0.027) but not for extension and external rotation (P≥0.05). Conclusions: Our study shows preliminary evidence for acceptable accuracy of a commercially available IMU against an OMC system for assessment of shoulder movements by a single tester. The IMU also exhibits similar whole degree of error compared to a standard goniometer with potential for application in remote rehabilitation.
Indexed as
Identifiers
What OpenQuestion holds
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.