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Affordances for capturing and re-enacting expert performance with wearables

Permanent link
https://hdl.handle.net/10037/12315
DOI
https://doi.org/10.1007/978-3-319-66610-5_34
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Date
2017-09-05
Type
Journal article
Tidsskriftartikkel
Peer reviewed

Author
Guest, Will; Wild, Fridolin; Vovk, Alla; Fominykh, Mikhail; Limbu, Bibeg; Klemke, Roland; Sharma, Puneet; Karjalainen, Jaakko; Smith, Carl; Rasool, Jazz; Aswat, Soyeb; Helin, Kaj; Di Mitri, Daniele; Schneider, Jan
Abstract
The WEKIT.one prototype is a platform for immersive procedural training with wearable sensors and Augmented Reality. Focusing on capture and re-enactment of human expertise, this work looks at the unique affordances of suitable hard- and software technologies. The practical challenges of interpreting expertise, using suitable sensors for its capture and specifying the means to describe and display to the novice are of central significance here. We link affordances with hardware devices, discussing their alternatives, including Microsoft Hololens, Thalmic Labs MYO, Alex Posture sensor, MyndPlay EEG headband, and a heart rate sensor. Following the selection of sensors, we describe integration and communication requirements for the prototype. We close with thoughts on the wider possibilities for implementation and next steps.
Description
OA accepted manuscript version. Copyright policy: http://www.springer.com/gp/computer-science/lncs/editor-guidelines-for-springer-proceedings Link to publishers version: https://link.springer.com/chapter/10.1007/978-3-319-66610-5_34
Publisher
Springer International Publishing
Series
Lecture Notes in Computer Science; 10474
Citation
Guest W, Wild F, Vovk A, Fominykh, Limbu B, Klemke R, Sharma P, Karjalainen J, Smith C, Rasool J, Aswat S, Helin K, Di Mitri D, Schneider J. Affordances for capturing and re-enacting expert performance with wearables. Lecture Notes in Computer Science. 2017;10474 LNCS:403-409
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