Ades, Craig

The sensation of touch is an integral part of using our hands. As different researchers work toward the restoration of afferent sensation in prosthetic hands, it becomes urgent to better understand how an artificial hand’s afferent inputs are affected by the efferent muscular outputs, and vice-versa. Current methods of neuroprosthetic research have many regulatory hurdles, time, cost, and associated risk to the patient. To circumvent these hurdles, we developed a non-invasive, closed-loop (CL) neuroprosthetic research platform, integrating artificial tactile signals from an artificial hand with biomimetically-stimulated biological neuronal networks (BNNs) cultured in a multielectrode array (MEA) chamber. These living embodied biological computers (EBCs) can provide a non-invasive alternative for investigating invasive neuroprosthetic interfaces. With them we can explore a variety of control techniques, tactile sensation encoding methods, and neural decoding methods to increase the rate of research in this area with minimal regulatory approval, greatly reduced cost and time, and no risk to the patients. In the first stage of this integration, our EBC was programmed to embody neuronal spiking from spontaneously active “efferent” receptive fields in cultured BNNs as intentional signals for movement. Bursts were transferred to a robotic hand and initiated a tapping motion of the index finger laid in proximity to a surface. Contact elicited artificial sensations, which were registered by a biotac tactile sensor array fit to the robotic fingertip.