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A multi-channel bioimpedance-based device for Vietnamese hand gesture recognition.
Sci Rep
December 2024
Department of Biomedical Engineering, Faculty of Applied Science, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet, District 10, Ho Chi Minh City, 700000, Vietnam.
This study addresses the growing importance of hand gesture recognition across diverse fields, such as industry, education, and healthcare, targeting the often-neglected needs of the deaf and dumb community. The primary objective is to improve communication between individuals, thereby enhancing the overall quality of life, particularly in the context of advanced healthcare. This paper presents a novel approach for real-time hand gesture recognition using bio-impedance techniques.
View Article and Find Full Text PDFAn efficient surface electromyography-based gesture recognition algorithm based on multiscale fusion convolution and channel attention.
Sci Rep
December 2024
School of Smart Health, Chongqing Polytechnic University of Electronic Technology, Chongqing, 401331, China.
In the field of rehabilitation, although deep learning have been widely used in multitype gesture recognition via surface electromyography (sEMG), their higher algorithmic complexity often leads to low computationally inefficient, which compromise their practicality. To achieve more efficient multitype recognition, We propose the Residual-Inception-Efficient (RIE) model, which integrates Inception and efficient channel attention (ECA). The Inception, which is a multiscale fusion convolutional module, is adopted to enhance the ability to extract sEMG features.
View Article and Find Full Text PDFMS-CLSTM: Myoelectric Manipulator Gesture Recognition Based on Multi-Scale Feature Fusion CNN-LSTM Network.
Biomimetics (Basel)
December 2024
School of Materials Science and Engineering, Central South University of Forestry and Technology, Changsha 410004, China.
Surface electromyography (sEMG) signals reflect the local electrical activity of muscle fibers and the synergistic action of the overall muscle group, making them useful for gesture control of myoelectric manipulators. In recent years, deep learning methods have increasingly been applied to sEMG gesture recognition due to their powerful automatic feature extraction capabilities. sEMG signals contain rich local details and global patterns, but single-scale convolutional networks are limited in their ability to capture both comprehensively, which restricts model performance.
View Article and Find Full Text PDFEnhancing Clinical Skills Through Virtual Reality: A Study on 12-Lead Electrocardiogram Placement in Medical Education.
Cureus
November 2024
Division of Institutional Technology, Nova Southeastern University Dr. Kiran C. Patel College of Osteopathic Medicine, Fort Lauderdale, USA.
Background Virtual reality (VR) is typically used for entertainment or gaming, but many studies have shown that the applications of VR can also extend to medical and clinical education. This is because VR can help health professionals learn complex subjects, improve memory, and increase interest in abstract concepts. In the context of medical education, the immersive nature of a VR setting allows students and clinicians in training to interact with virtual patients and anatomical structures in a three-dimensional environment or from a clinician's point of view.
View Article and Find Full Text PDFEvaluating the Feasibility and Preliminary Effectiveness of a Multi-Tiered Multimodal Narrative Intervention Program for Preschool Children.
Lang Speech Hear Serv Sch
January 2025
Department of Translation and Language Sciences, Universitat Pompeu Fabra, Barcelona, Spain.
Purpose: The present study aims to evaluate the feasibility and preliminary effectiveness of a novel multi-tiered narrative intervention program-the multimodal narrative (MMN) program-in Catalan that was co-created to boost preschool children's narrative and pragmatic skills.
Method: First, we describe here in detail the novel program, which consisted of a set of interventions oriented around the retelling of a narrative in a multimodal fashion, that is, with an abundant use of appropriate gesture and facial expression and careful attention to the pragmatic aspects of communication. We then describe the results of a self-reported feasibility study (Study 1) after this program was trial-implemented by 31 preschool teachers and speech-language therapists in their respective professional contexts.
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