PT - JOURNAL ARTICLE AU - Shafti, Ali AU - Haar, Shlomi AU - Zaldivar, Renato Mio AU - Guilleminot, Pierre AU - Faisal, A. Aldo TI - Learning to play the piano with the Supernumerary Robotic 3<sup>rd</sup> Thumb AID - 10.1101/2020.05.21.108407 DP - 2020 Jan 01 TA - bioRxiv PG - 2020.05.21.108407 4099 - http://biorxiv.org/content/early/2020/05/25/2020.05.21.108407.short 4100 - http://biorxiv.org/content/early/2020/05/25/2020.05.21.108407.full AB - We wanted to study the ability of our brains and bodies to be augmented by supernumerary robot limbs, here extra fingers. We developed a mechanically highly functional supernumerary robotic 3rd thumb actuator, the SR3T, and interfaced it with human users enabling them to play the piano with 11 fingers. We devised a set of measurement protocols and behavioural “biomarkers”, the Human Augmentation Motor Coordination Assessment (HAMCA), which allowed us a priori to predict how well each individual human user could, after training, play the piano with a two-thumbs-hand. To evaluate augmented music playing ability we devised a simple musical score, as well as metrics for assessing the accuracy of playing the score. We evaluated the SR3T (supernumerary robotic 3rd thumb) on 12 human subjects including 6 naïve and 6 experienced piano players. We demonstrated that humans can learn to play the piano with a 6-fingered hand within one hour of training. For each subject we could predict individually, based solely on their HAMCA performance before training, how well they were able to perform with the extra robotic thumb, after training (training end-point performance). Our work demonstrates the feasibility of robotic human augmentation with supernumerary robotic limbs within short time scales. We show how linking the neuroscience of motor learning with dexterous robotics and human-robot interfacing can be used to inform a priori how far individual motor impaired patients or healthy manual workers could benefit from robotic augmentation solutions.Competing Interest StatementAS, SH, RM and PG declare no competing financial interests. AAF has consulted for Airbus, Averner Films and Celestial Group. AAF has received within the domain of this paper research funding and donations from Microsoft and NVIDIA.