Unlabelled: The aim of the present study was to perform a review of the literature on current quantitative clinical methods for the evaluation of upper limb movements in children and adolescents with Down syndrome, with a focus on describing the variables, protocols, motor function and motor control.
Methods: A survey of PubMed, Scielo, BVS Bireme and PEDro databases using the following key words: upper limb and EMG and Down syndrome; upper limb and kinematics and Down syndrome; upper limb and motion analysis and Down syndrome; movement and upper limb and Down syndrome; upper limb and Down syndrome; reach and Down syndrome.
Results: In all, 344 articles and five were selected to compose the present systematic review. No standardization was found among the studies analyzed with regard to data collection, data processing or procedures for the evaluation of the variables.
Conclusion: A kinematic evaluation is effective for the discussion of the results, but methodological differences among the studies and inconsistent results exert a negative influence on clinical interpretations and the possibility of reproducibility. The standardization of an upper limb movement evaluation protocol using kinematic analysis is important, as it would provide the basis for comparable, reproducible results and facilitate the planning of treatment interventions.
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http://dx.doi.org/10.1016/j.infbeh.2018.03.001 | DOI Listing |
Sci Rep
December 2024
Department of Orthopedic Surgery, Yonsei University College of Medicine, Seoul, South Korea.
The unique saddle articulation of the trapeziometacarpal joint allows for a wide range of motion necessary for routine function of the thumb. Inherently unstable characteristics of the joint can lead painful instability. In this study, we modified a surgical dorsal ligament reconstruction technique for restoring trapeziometacarpal joint stability.
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December 2024
Department of Upper Gastrointestinal and Bariatric Surgery, University Hospitals Sussex (St Richard's Hospital), Chichester, UK.
Introduction: Roux-en-Y gastric bypass (RYGB) reversal might be necessary to alleviate refractory surgical or nutritional complications, such as postprandial hypoglycemia, malnutrition, marginal ulceration, malabsorption, chronic diarrhea, nausea and vomiting, gastro-esophageal reflux disease, chronic pain, or excessive weight loss. The surgical technique of RYGB reversal is not standardized; potential strategies include the following: (1) gastro-gastrostomy: hand-sewn technique, linear stapler, circular stapler; (2) handling of the Roux limb: reconnection or resection (if remaining intestinal length ≥ 4 m).
Case Presentation: We demonstrate the surgical technique of a laparoscopic reversal of RYGB with hand-sewn gastro-gastrostomy and resection of the alimentary limb with the aim of improving the patient's quality of life.
Behav Res Methods
December 2024
Algoritmi Research Centre, University of Minho, Campus de Azurém, 4800-058, Guimarães, Portugal.
The vibration perception threshold (VPT) is the minimum amplitude required for conscious vibration perception. VPT assessments are essential in medical diagnostics, safety, and human-machine interaction technologies. However, factors like age, health conditions, and external variables affect VPTs.
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December 2024
Cancer Center, Department of Pulmonary and Critical Care Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310014, Zhejiang, China.
Hospital-acquired infection (HAI) and antimicrobial resistance (AMR) represent major challenges in healthcare system. Despite numerous studies have assessed environmental and patient samples, very few studies have explored the microbiome and resistome profiles of medical staff including nursing workers. This cross-sectional study was performed in a tertiary hospital in China and involved 25 nurses (NSs), 25 nursing workers (NWs), and 55 non-medical control (NC).
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December 2024
Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran.
Surface electromyography (sEMG) data has been extensively utilized in deep learning algorithms for hand movement classification. This paper aims to introduce a novel method for hand gesture classification using sEMG data, addressing accuracy challenges seen in previous studies. We propose a U-Net architecture incorporating a MobileNetV2 encoder, enhanced by a novel Bidirectional Long Short-Term Memory (BiLSTM) and metaheuristic optimization for spatial feature extraction in hand gesture and motion recognition.
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