Accelerating Skill Acquisition of Two-Handed Drumming using Pneumatic Artificial Muscles

Takashi Goto, Swagata Das, Katrin Wolf, Pedro Lopes, Yuichi Kurita, Kai Kunze

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

While computers excel at augmenting user's cognitive abilities, only recently we started utilizing their full potential to enhance our physical abilities. More and more wearable force-feedback devices have been developed based on exoskeletons, electrical muscle stimulation (EMS) or pneumatic actuators. The latter, pneumatic-based artificial muscles, are of particular interest since they strike an interesting balance: lighter than exoskeletons and more precise than EMS. However, the promise of using artificial muscles to actually support skill acquisition and training users is still lacking empirical validation. In this paper, we unveil how pneumatic artificial muscles impact skill acquisition, using two-handed drumming as an example use case. To understand this, we conducted a user study comparing participants' drumming performance after training with the audio or with our artificial-muscle setup. Our haptic system is comprised of four pneumatic muscles and is capable of actuating the user's forearm to drum accurately up to 80 bpm. We show that pneumatic muscles improve participants' correct recall of drumming patterns significantly when compared to auditory training.

Original languageEnglish
Title of host publicationProceedings of the Augmented Humans International Conference, AHs 2020
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450376037
DOIs
Publication statusPublished - 2020 Mar 16
Event2020 Augmented Humans International Conference, AHs 2020 - Kaiserslautern, Germany
Duration: 2020 Mar 162020 Mar 17

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2020 Augmented Humans International Conference, AHs 2020
CountryGermany
CityKaiserslautern
Period20/3/1620/3/17

Keywords

  • Force-feedback
  • motor learning
  • pneumatic artificial muscles (PAMs)

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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