The development of human-computer interaction (HCI) has advanced significantly with the integration of hand gesture recognition to enhance traditional input devices like the computer mouse. A gesture-based computer mouse leverages hand movements and gestures to control on-screen elements, offering an intuitive and contactless interface for users. By utilizing sensors such as cameras, accelerometers, or infrared detectors, this system interprets various hand positions and motions to emulate mouse functions, such as pointing, clicking, and scrolling. This paper explores the design and implementation of a gesture-based computer mouse, focusing on the use of computer vision, machine learning algorithms, and real-time data processing to accurately detect and classify hand gestures. The solution aims to provide an ergonomic and efficient alternative to conventional mice, reducing strain and improving accessibility for users with mobility limitations. Additionally, the system offers new possibilities for immersive experiences in virtual reality (VR) and gaming, where physical touch with a device is impractical. The study evaluates the performance, accuracy, and usability of the gesture-based mouse and discusses potential applications in various industries, from assistive technology to interactive media.
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