Intuitive control of supernumerary robotic limbs through a tactile-encoded neural interface

These authors contributed equally to this work . Abstract: Brain - computer interfaces (BCIs) promise to extend human movement capabilities by enabling direct neural control of supernumerary effectors, yet integrating augmented commands with multi ple degrees of freedom without disrupting natural movement remains a k ey challenge. Here, we propose a tactile - encoded BCI that leverages sensory afferents through a novel tactile - evoked P300 paradigm, allowing intuitive and reliable decoding of supernumerary motor intentions even when superimposed with voluntary actions. The interface was evaluated in a multi - day experiment comprising of a single motor recognition task to validate baseline BCI performance and a dual task paradigm to assess the potential influence between the BCI and natural human movement . T he brain interface achieved real - time and reliable decoding of four supernumerary degrees of freedom, with significant performance improvement s after only three days of training. Importantly, after training, performance did not differ significantly b etween the single - and dual - BCI task conditions, and natural movement remained unimpaired during concurrent supernumerary control . Lastly, the interface was deployed in a movement augmentation task, demonstrating its ability to command two supernumerary robotic arms for functional assistance during bimanual tasks. These results establish a new neural interface paradigm for movement augmentation through stimulation of sensory afferents, expanding motor degrees of fr eedom without impairing natural movement . One - Sentence Summary: T actile - encoded neural interface enables intuitive control of supernumerary limbs without compromising natural human movement Main Text: INTRODUCTION Humans interact with their surroundings with remarkable dexterity and efficiency. Recent advances in robotics and neural interfaces hold the potential to increase these capabilities, enhancing human movement beyond its natural limits. Movement augmentation aims to increase the mechanical degrees of freedom (DoFs) an individual can exert over their surroundings ( 1), allowing movement tasks to be performed more efficiently or enable actions otherwise impossible with natural limbs alone, such as trimanual manipulation with a third arm ( 2) . A central challenge, however, lies in achieving practical control of supernumerary effectors (SEs) without compromising natural movement. Current strategies for augmenting DoFs often rely on augmentation by transfer, in which control of SEs is derived from the function of an existing body part, typically one that is task - irrelevant ( 1, 3, 4) .