Learning to play the piano with the Supernumerary Robotic 3rd Thumb
Author(s)
Shafti, Ali
Haar, Shlomi
Zaldivar, Renato Mio
Guilleminot, Pierre
Faisal, A Aldo
Type
Working Paper
Abstract
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.
Date Issued
2020-05-25
Citation
2020
Publisher
Cold Spring Harbor Laboratory
Copyright Statement
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
Sponsor
The Royal Society
Grant Number
NF170650