Development of brain-controlled robotic hand using non-invasive wearable EEG sensor

The research and development of robotic hands have been done rapidly in recent years. The growing interest was influenced by the potential of a robotic hand that could be applicable in such a large area; one example was the capability to be an active upper limb prosthesis. The robotic hand used for functional upper limb prostheses mostly uses an EMG sensor to detect electrical activity in human muscle, which is later used as an input signal to trigger the robotic hand’s movement. Current works aim to use EEG sensors instead of EMG sensors to provide input signals for robotic hands. EEG sensors can detect brainwaves such as alpha, beta, delta, gamma, and theta, which are values related to brain activity. Later, these values can be combined into a new form of signal that could describe the current brain’s state, such as attention level. The value of attention level is then used to initiate the movement of the robotic hand. This work also performed modifications on the servo to finger moving mechanism. Based on the result, the minimum value of attention levels required to initiate movement was set based on the most negligible deal of attention acquired from study participants who were instructed to focus. After the attention value passes the threshold, the robotic hand starts to perform flexion movement; on the contrary, when the value is lower than the threshold, the robotic hand returns to its normal position.