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4 articles for “Sensor-Based Rehabilitation”
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Development Of Ai-Driven Systems for Real-Time Joint Movement Detection and Correction in Frozen Shoulder Therapy Using Sensor-Based Shoulder Rehabilitation Devices
Abstract: Frozen shoulder, or adhesive capsulitis, is a common musculoskeletal disorder characterized by progressive pain, stiffness, and restricted range of motion that significantly impairs functional ability and quality of life. Recent advancements in artificial intelligence and sensor-based technologies have enabled the development of intelligent rehabilitation systems capable of real-time joint movement detection and correction. Wearable sensors such as inertial measurement units, electromyography sensors, and flexible strain sensors capture continuous biomechanical data …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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Development of an Arduino-based Robotic Arm for Automated Tasks
Abstract: A versatile robotic arm that can perform a variety of tasks in a variety of environments is the goal of this project, which will involve designing the arm's mechanical structure, choosing and integrating appropriate motors, and programming the control system, which will be based on a microcontroller that will receive input from the potentiometer and translate it into movement commands for the arm. In the current scenario, machines and robots …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 1, 2025 · pp. 24–33 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Advancements in Humanoid Robot Locomotion: A Review of Control Strategies and Kinematic Models
Abstract: Humanoid robot locomotion has significantly improved over the past few decades, driven by improvements in control strategies and kinematic models. Researchers aim to develop robots that can walk, run, and navigate complex terrains with efficiency and stability. This review explores recent developments in humanoid locomotion, highlighting control strategies such as model predictive control, reinforcement learning, and central pattern generators. Additionally, it examines kinematic models, including inverted pendulum models and zero …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 24–30 Read article