Design and Prototyping of a Human Prosthetic Hand Using an EEG and Force Sensor Network with Arduino Microcontroller

Abstract This paper presents the design and development of a myoelectric prosthetic hand controlled by electroencephalographic (EEG) signals acquired from the prefrontal region of the scalp. The system architecture follows a Single Input, Multiple Output (SIMO) model, where a single EEG signal is interpreted to generate five different gestures: opening, closing, greeting, pistol, and zigzag. The acquisition is carried out using a modified AD8232 module, and the interpretation is executed in real-time using an Arduino Uno. The mechanical system comprises five MG996R servomotors controlled independently via an embedded algorithm. The hand structure is 3D printed in PLA and incorporates a passive return mechanism using springs and fishing wire-based pulley systems. A Java-based monitoring interface allows real-time signal tracking and control verification. The developed system offers an accessible and efficient alternative for individuals with upper limb amputations, bridging low-cost materials and advanced biosignal-based control.