dc.contributor.author | Levine, Daniel S. | |
dc.contributor.author | Cheng, Alan | |
dc.contributor.author | Olaleye, David | |
dc.contributor.author | Leonardo, Kevin Alfonso | |
dc.contributor.author | Shifrin, Matthew | |
dc.contributor.author | Ishii, Hiroshi | |
dc.date.accessioned | 2022-01-07T15:18:23Z | |
dc.date.available | 2021-11-09T16:33:18Z | |
dc.date.available | 2022-01-07T15:18:23Z | |
dc.date.issued | 2019-05 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/137968.2 | |
dc.description.abstract | © 2019 Copyright held by the owner/author(s). How can people learn advanced motor skills such as front flips and tennis swings without starting from a young age? The answer, following the work of Masters et. al., we believe, is implicitly. Implicit learning is associated with higher retention and knowledge transfer, but that is unable to be explicitly articulated as a set of rules. To achieve implicit learning is difficult, but may be taught using obscured feedback - that is feedback that provides little enough information such that a user does not overfit a mental model of their target action. We have designed an auditory feedback system - AUFLIP - that describes high level properties of an advanced movement using a simplified and validated physics model of the flip. We further detail the implementation of a wearable system, optimized placement procedure, and takeoff capture strategy to realize this model. With an audio cue pattern that conveys this high-level, obscured objective, the system is integrated into a gymnastics-training environment with professional coaches teaching novice adults how to perform front flips. We perform a pilot user study training front flips, evaluating using a matched-pair comparison. | en_US |
dc.language.iso | en | |
dc.publisher | ACM | en_US |
dc.relation.isversionof | 10.1145/3290607.3312804 | en_US |
dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en_US |
dc.source | MIT web domain | en_US |
dc.title | AUFLIP - An Auditory Feedback System Towards Implicit Learning of Advanced Motor Skills | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Levine, Daniel, Cheng, Alan, Olaleye, David, Leonardo, Kevin, Shifrin, Matthew et al. 2019. "AUFLIP - An Auditory Feedback System Towards Implicit Learning of Advanced Motor Skills." | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Media Laboratory | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
dc.date.updated | 2019-07-23T13:56:00Z | |
dspace.date.submission | 2019-07-23T13:56:01Z | |
mit.metadata.status | Publication Information Needed | en_US |