Background: Physical therapists routinely measure range of motion (ROM) of cervical spine. The reliability of the cervical range of motion (CROM) device has been demonstrated in several studies, but current evidence on the validity and reliability of the visual inspection is contradictory. The aim is to assess the validity and interexaminer reliability of the online visual inspection of active cervical ROM in physiotherapy students.
Methods: Flexion, extension, both lateral flexions and rotations of a single participant were measured using CROM. Online visual inspection of 18 physiotherapy students against CROM was registered.
Results: The validity, against CROM, of the online visual inspection of the active ROM ranged from good to excellent (Intraclass Correlation Coefficient (ICC) 0.83-0.97). Interexaminer reliability of the online visual inspection had favorable outcomes in all cervical movements in the three physiotherapy courses (ICC 0.70-0.96), with the visual inspection of the rotations being the most reliable (ICC 0.93-0.97). Interexaminer reliability of the classification of mobility was poor to good (Kappa 0.03-0.90).
Conclusions: The interexaminer reliability and validity of the quantification of active cervical movement during online visual inspection was shown to be good to excellent for flexion-extension and lateral flexions and excellent for rotations.
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http://dx.doi.org/10.3390/diagnostics12020546 | DOI Listing |
Pharmaceutics
January 2025
Department of Pharmacy-Pharmaceutical Sciences, University of Bari Aldo Moro, 70125 Bari, Italy.
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View Article and Find Full Text PDFPharmaceutics
January 2025
Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen (UMCG), 9713 GZ Groningen, The Netherlands.
Parenteral drug products manufactured under GMP conditions should be visually inspected for defects and particulate contamination by trained and qualified personnel. Although personnel qualification is required, no practical protocols or formal guidelines are available for the development of qualification test sets (QTSs) used for qualification procedures. The current practice is to either procure a standardized QTS from a commercial supplier or amass sufficient manufacturing rejects during visual inspection procedures to compile in-house QTSs.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Centre of Mechanical Technology and Automation (TEMA), Department of Mechanical Engineering, University of Aveiro, 3810-193 Aveiro, Portugal.
To automate the quality control of painted surfaces of heating devices, an automatic defect detection and classification system was developed by combining deflectometry and bright light-based illumination on the image acquisition, deep learning models for the classification of non-defective (OK) and defective (NOK) surfaces that fused dual-modal information at the decision level, and an online network for information dispatching and visualization. Three decision-making algorithms were tested for implementation: a new model built and trained from scratch and transfer learning of pre-trained networks (ResNet-50 and Inception V3). The results revealed that the two illumination modes employed widened the type of defects that could be identified with this system, while maintaining its lower computational complexity by performing multi-modal fusion at the decision level.
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January 2025
State Key Laboratory of Marine Resource Utilization in South China Sea, School of Chemistry and Chemical Engineering, Hainan University, Haikou 570228, China.
The detection of highly toxic chemicals such as phosgene is crucial for addressing the severe threats to human health and public safety posed by terrorist attacks and industrial mishaps. However, timely and precise monitoring of phosgene at a low cost remains a significant challenge. This work is the first to report a novel fluorescent system based on the Intramolecular Charge Transfer (ICT) effect, which can rapidly detect phosgene in both solution and gas phases with high sensitivity by integrating a benzo[1,2-b:6,5-b']dithiophene-4,5-diamine (BDTA) probe.
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January 2025
School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China.
The automated detection of yarn margins is crucial for ensuring the continuity and quality of production in textile workshops. Traditional methods rely on workers visually inspecting the yarn margin to determine the timing of replacement; these methods fail to provide real-time data and cannot meet the precise scheduling requirements of modern production. The complex environmental conditions in textile workshops, combined with the cylindrical shape and repetitive textural features of yarn bobbins, limit the application of traditional visual solutions.
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