Paper Title
GESTURE RECOGNITION

Abstract
Abstract - Effective communication is important for lowering anxiety and stress levels, but it can be difficult for individuals who are deaf or mute to communicate with others due to the limited use of sign language. The concept of gesture recognition gloves is proposed as a potential solution to this issue. The article discusses two different methods for recognizing hand gestures; one based on deep learning and the other using sensors, and highlights the advantages and disadvantages of each. The authors propose a sensor-based methodology with an audio amplifier inside the glove to convey the message's content orally. The flex sensor and MPU6050 are identified as key components for recognizing gestures, and an LCD monitor and audio amplifier are used to display the output. Overall, careful planning and testing are emphasized to ensure that the system is accurate, reliable, and cost-effective. Keywords - STM 32 NUCLEO F401RE, Gestures, Flex Sensor, MPU6050