Intelligent bio robotic prosthetic arm system using HCI

We need hand-eye coordination to do many things in our daily lives. If you lose the ability to take care of yourself, you will lose a lot. People often can't fully use prosthetic hands' capabilities because they are usually hard to use. As a result, prosthetic hands don't work as well as they could. This study seeks to investigate the development of an intelligent bionic robotic hand that can detect the object it is grasping and autonomously modify its grip strength. The goal is to fix the problems that current prosthetic technologies have. This method uses residual muscle impulses as built-in input to power the prosthetic's motor. It can accurately predict the path of the user's hand movement because it knows how the user's muscles work. This is possible because of new technologies in machine learning and vision. The system can better do tasks like manipulating and grasping by watching objects in real time. This method is easier to learn because it is similar to how people naturally use their hands. This study is important because it shows that machines can get tactile feedback. This gives users a stronger feeling of control and emotional connection. This technology is much better than older prosthetics because it can find targets with 68% to 87% accuracy. The goal of the research is to lower costs by using cheap parts like electromyography (EMG) sensors, Raspberry Pi, Arduino, and 3D-printed prosthetic parts. The main goal of this research is to make prosthetics better, so they are easier to use and can be used by more people. This will make a big difference in the lives of people who need prosthetics.