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6 articles for “EMG”
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Develop a System to Control a Prosthetic Hand by Using EMG
Abstract: An EMG-controlled prosthetic hand is a type of artificial hand that users can control through muscle signals. When a person with a missing hand tries to move their "phantom" hand, the muscles in the remaining part of the arm still produce electrical signals. Small sensors placed on the skin detect these signals, which are then translated into movements of the prosthetic hand, like opening, closing, or gripping objects. This technology …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 3, 2025 · pp. 01–06 Read article
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Smart Bionic Hand: Combining Hardware and AI For Adaptive Prosthetic Functionality
Abstract: This research paper presents the development and integration of a bionic arm that leverages both hardware components and artificial intelligence (AI) models for enhanced functionality and user interaction. The hardware design includes key components such as servo motors, an Arduino UNO microcontroller, electromyography (EMG) sensors, and a lithium-ion battery. The EMG sensors detect muscle signals, which serve as inputs for controlling the arm's movements, while the servo motors are responsible …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 1–7 Read article
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Muscle Computer Interface for Recovering People
Abstract: The muscle-computer interface (MCI) has emerged as a promising technology for enhancing the recovery process of individuals with paralyzed limbs or disabilities. This paper explores the application of MCI in the context of recovering people and addresses the challenges faced by such individuals. Traditional rehabilitation methods often have limitations in terms of engagement, feedback, and real-time interaction, which hinder the recovery progress. In response to these challenges, the proposed MCI …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 3, 2024 · pp. 8–15 Read article
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Autonomous Calibration of Medical Devices Using Synthetic Biosignals and Adaptive Learning
Abstract: The accuracy and reliability of modern biomedical diagnostic devices are critically dependent on effective calibration mechanisms capable of handling dynamic physiological and environmental variations. Conventional calibration approaches, which rely on static reference signals and manual adjustments, are inadequate in addressing challenges such as sensor drift, noise interference, motion artifacts, and long-term performance degradation. To overcome these limitations, this research proposes an innovative AI-driven adaptive biosignal simulation and calibration architecture for …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 2, 2026 Read article
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AI-Powered Face Detection and Recognition Using Machine Learning
Abstract: These days, one of the biggest computer vision technologies is facial recognition. Face identification in computer vision, lighting position, and facial expression is always an extremely challenging issue. In real-time video pictures captured by a video camera, face recognition tracks specific objects. Put simply, it is a system tool that uses a still picture or video frame to automatically identify a person. In this research paper we use different different …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 1–12 Read article
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Epilert: Epilepsy Tracker and Detector
Abstract: Epilepsy, affecting over 50 million individuals worldwide, necessitates innovative solutions for effective monitoring and intervention. Current systems face challenges such as inaccuracy, limited accessibility, and discomfort, leaving patients and caregivers vulnerable. Epilert, a wearable device, addresses these gaps by employing advanced sensors and machine-learning algorithms for real-time epilepsy detection and monitoring. The device integrates electromyography (EMG) and motion sensors to capture and analyze physiological and movement data. Preprocessing techniques ensure …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 1–8 Read article