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Playing the piano with a robotic third thumb : assessing constraints of human augmentation

Title data

Shafti, Ali ; Haar, Shlomi ; Mio, Renato ; Guilleminot, Pierre ; Faisal, A. Aldo:
Playing the piano with a robotic third thumb : assessing constraints of human augmentation.
In: Scientific Reports. Vol. 11 (2021) Issue 1 . - 21375.
ISSN 2045-2322
DOI: https://doi.org/10.1038/s41598-021-00376-6

Official URL: Volltext

Project information

Project financing: Andere

Abstract in another language

Contemporary robotics gives us mechatronic capabilities for augmenting human bodies with extra limbs. However, how our motor control capabilities pose limits on such augmentation is an open question. We developed a Supernumerary Robotic 3rd Thumbs (SR3T) with two degrees-of-freedom controlled by the user’s body to endow them with an extra contralateral thumb on the hand. We demonstrate that a pianist can learn to play the piano with 11 fingers within an hour. We then evaluate 6 naïve and 6 experienced piano players in their prior motor coordination and their capability in piano playing with the robotic augmentation. We show that individuals’ augmented performance with the SR3T could be explained by our new custom motor coordination assessment, the Human Augmentation Motor Coordination Assessment (HAMCA) performed pre-augmentation. Our work demonstrates how supernumerary robotics can augment humans in skilled tasks and that individual differences in their augmentation capability are explainable by their individual motor coordination abilities.

Further data

Item Type: Article in a journal
Refereed: Yes
Institutions of the University: Faculties > Faculty of Life Sciences: Food, Nutrition and Health > Lehrstuhl Digital Health mit Schwerpunkt Data Science in Lebenswissenschaften > Lehrstuhl Digital Health mit Schwerpunkt Data Science in Lebenswissenschaften - Univ.-Prof. Dr. Aldo Faisal
Faculties
Faculties > Faculty of Life Sciences: Food, Nutrition and Health
Faculties > Faculty of Life Sciences: Food, Nutrition and Health > Lehrstuhl Digital Health mit Schwerpunkt Data Science in Lebenswissenschaften
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
600 Technology, medicine, applied sciences > 600 Technology
600 Technology, medicine, applied sciences > 610 Medicine and health
Date Deposited: 02 Jun 2023 07:18
Last Modified: 17 Aug 2023 06:12
URI: https://eref.uni-bayreuth.de/id/eprint/81086