In this project, a prototype bionic hand prosthesis, whose control is performed using EEG and EMG signals along with the weight perception of the objects, will be developed. The goal here is to decrease the physical and mental load faced by the patient while using a mechanical prosthesis with the help of our new system. The weight of the object that the patient wants to hold depends on the visual perception of the patient’s brain. If this object is heavy, an impulse will be sent to the prosthesis by activating preconditioning on the motors on the prosthesis. Thanks to this signal, the prosthesis will play an important role in carrying the heavy object rather than putting much pressure from the shoulder. Thus, the patients will feel the prosthesis like their own body part that will increase their motivation in using the prosthesis. In the system to be developed, real-time biomedical signal processing, conventional machine learning and deep learning approaches will be used.