BCI Hand Prosthetic Device

Abstract

Brain-Computer interfaces (BCIs) have emerged as a promising technology for restoring motor function in individuals with upper limb amputations. By establishing a communication channel between the user’s brain and computer, EEG enables real-time decoding of motor intentions, offering promising prospects for restoring motor function in individuals with upper limb amputations. BCIs is a tool that establishes a communication channel between a computer and a human brain which converts the brain activity to control signals. The existing landscape of BCIs for hand prosthetics includes various techniques such as (Electromyography) EMG, (Electrocorticography) ECoG and Functional Magnetic Resonance Imaging (fMRI). A critical examination of these methods reveals inherent challenges, including limited spatial resolution and invasive procedures making it difficult for practical daily use. Along with all these limitations, one of their major drawback is their invasive approach which requires surgery, which makes them an unreliable and rsiky techniques. In response to the identifed limitations, this project advocates for an (Electroencephalography) EEG-based BCIs for hand prosthetics. EEG based BCIs systems are non-invasive and very reliable due to their light weight property as they are wearable and portable allowing users to move freely and engage in thier daily life activities even while using the BCIs. EEG offers non-invasiveness, cost-effectiveness and a high temporal resolution making it an ideal candidate for real-time decoding of motor intentions. The performance of this system is evaluated based on several metrices such as accuracy, task completion, practical viability, and user experience.