Internet of Things (IoT) Based Keyboard Learning Application Model For Preventing Carpal Tunnel Syndrome

Abstract

The keyboard is a computer hardware device used for typing. Generally, individuals who are not accustomed to typing tend to use one finger at a time to press the keys, resulting in repetitive and pressing movements of the fingers. This can be one of the contributing factors to carpal tunnel syndrome. Carpal tunnel syndrome is a condition that can affect the functionality of the hands and fingers, causing symptoms such as tingling, pain, numbness, and even finger weakness. This occurs due to the compression of the median nerve in the carpal tunnel. In keyboard learning, there is a technique that is commonly used to perform typing tasks more effectively and efficiently, known as the 10-finger typing technique. This technique involves placing each finger in a specific position to target certain keys, with each finger having a specific role in directing movements on the keyboard. By understanding the function of each finger, one can master and improve typing skills more quickly and efficiently. This research focuses on developing a sensor-based keyboard learning system capable of recording fingerprints to capture the typing patterns inputted into the application