Affordances for Capturing and Re-enacting Expert Performance with Wearables. Guest, W., Wild, F., Vovk, A., Fominykh, M., Limbu, B., Klemke, R., Sharma, P., Karjalainen, J., Smith, C., Rasool, J., Aswat, S., Helin, K., Di Mitri, D., & Schneider, J. In Lavoué, É., Drachsler, H., Verbert, K., Broisin, J., & Pérez-Sanagustín, M., editors, Data Driven Approaches in Digital Education, pages 403–409, Cham, 2017. Springer International Publishing. doi abstract bibtex 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.
@inproceedings{guest_affordances_2017,
address = {Cham},
title = {Affordances for {Capturing} and {Re}-enacting {Expert} {Performance} with {Wearables}},
isbn = {978-3-319-66610-5},
doi = {10.1007/978-3-319-66610-5_34},
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.},
language = {en},
booktitle = {Data {Driven} {Approaches} in {Digital} {Education}},
publisher = {Springer International Publishing},
author = {Guest, Will and Wild, Fridolin and Vovk, Alla and Fominykh, Mikhail and Limbu, Bibeg and Klemke, Roland and Sharma, Puneet and Karjalainen, Jaakko and Smith, Carl and Rasool, Jazz and Aswat, Soyeb and Helin, Kaj and Di Mitri, Daniele and Schneider, Jan},
editor = {Lavoué, Élise and Drachsler, Hendrik and Verbert, Katrien and Broisin, Julien and Pérez-Sanagustín, Mar},
year = {2017},
pages = {403--409},
}
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