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@article{175637,
        author = {Anshuman S. Modak and Shrinivas A. Khursade and Sonal S. Kukade and Siddharth B. Bhorge},
        title = {IoT-BASED PARALYSED PATIENT HAND ASSISTANT SYSTEM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {4166-4170},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175637},
        abstract = {The advent of the Internet of Things (IoT) has revolutionized healthcare, enabling real-time monitoring and assistance for patients with mobility challenges. This research presents the design and implementation of an IoT-based personalized patient assistant system using an MPU6050 gyroscope and accelerometer sensor and a NodeMCU microcontroller to track three-axis hand movements. The system is tailored for individuals with limited mobility or requiring motion-based assistance. The MPU6050 sensor captures precise hand movement data across three axes (X, Y, Z), which is processed by the NodeMCU and transmitted via Wi-Fi to the Blynk platform. Through the Blynk mobile application, caregivers or medical personnel receive real-time pop-up notifications whenever specific hand movements are detected, such as gestures indicating a need for assistance. The proposed system is cost-effective, scalable, and user-friendly, offering significant improvements in patient care and monitoring. Experimental results demonstrate the system's accuracy in detecting predefined hand gestures and its efficiency in delivering timely alerts, highlighting its potential for broader applications in personalized healthcare and assistive technologies.},
        keywords = {IoT, Patient Assistant System, MPU6050, NodeMCU, Three-Axis Movement Detection, Gesture Recognition, Blynk Platform, Real-Time Monitoring, Assistive Technology, Healthcare IoT, Motion Tracking, Remote Patient Care},
        month = {April},
        }