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@article{189542,
        author = {Akash A and A Abhinav and Meghana B N and Bharath V Reddy and Dr Manasa Charitha},
        title = {Digital interface: An EOG Signal Processing for ALS And Paralysis Patients},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {5777-5781},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=189542},
        abstract = {The proposed paper presents a low-cost Electrooculography (EOG)-based cursor control system developed to assist ALS and paralyzed patients in interacting with computers using eye movements. Surface electrodes are used to acquire eye-movement signals, which are amplified and conditioned using an AD8232 biopotential amplifier. An ESP32 microcontroller performs real-time signal acquisition and processing, and the detected commands are transmitted to a computer through wired serial communication. A Python-based interface converts these commands into cursor movements. The system is independent of lighting conditions, requires minimal calibration, and demonstrates reliable performance. The proposed solution offers a simple, economical, and effective approach for hands-free human–computer interaction.},
        keywords = {Electrooculography (EOG), Assistive Technology, Human–Computer Interface (HCI), Cursor Control, ALS, Paralysis, ESP32, AD8232 Biopotential Amplifier},
        month = {December},
        }