Paper Title
Brain and Voice Controlled Wheelchair

Abstract
In this project, Arduino microcontrollers, EMG sensors, and other physiological sensors are used to construct a brain and voice-controlled wheelchair system.Users with limited physical capabilities are intended to benefit from the wheelchair system's mobility aid features. The system's primary role is to analyze information from EMG sensors affixed to the user's eyebrow muscles. The device can precisely decipher the user's intents from the activity of their eyebrow muscles by analyzing the EMG data. With the use of this technology, users may effortlessly interact with the system by moving their eyebrows, improving accessibility and control. The accuracy of the EMG sensor data is crucial for converting weak muscle impulses into directives that the system can follow. Furthermore, to guarantee the user's safety while in use, the system incorporates sensors to track body temperature, blood oxygen saturation (SpO2), and heart rate. For increased accessibility, the user interface has both button operation and voice control through a Bluetooth-connected app. The wheelchair system attempts to provide a dependable and user-friendly mobility solution for people with physical disabilities through a combination of sensor integration, signal processing algorithms, and user interface design. Keywords - Electromyography (EMG) Sensor, MAX30100pulse Oximeter, Arduino,Contactless Temperature Sensor