Affordances for capturing and re-enacting expert performance with wearables

Will Guest; Fridolin Wild; Alla Vovk; Mikhail Fominykh; Bibeg Limbu; Roland Klemke; Puneet Sharma; Jaakko Karjalainen; Carl Smith; Jazz Rasool; Soyeb Aswat; Kaj Helin; Daniele Di Mitri; Jan Schneider

doi:10.1007/978-3-319-66610-5_34

Affordances for capturing and re-enacting expert performance with wearables

Will Guest, Fridolin Wild, Alla Vovk (Corresponding author), Mikhail Fominykh, Bibeg Limbu, Roland Klemke, Puneet Sharma, Jaakko Karjalainen, Carl Smith, Jazz Rasool, Soyeb Aswat, Kaj Helin, Daniele Di Mitri, Jan Schneider

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

8 Citations (Scopus)

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.

Original language	English
Title of host publication	Data Driven Approaches in Digital Education
Subtitle of host publication	12th European Conference on Technology Enhanced Learning, EC-TEL 2017
Editors	Julien Broisin, Elise Lavoue, Hendrik Drachsler, Katrien Verbert, Mar Perez-Sanagustin
Place of Publication	Cham
Publisher	Springer
Pages	403-409
ISBN (Electronic)	978-3-319-66610-5
ISBN (Print)	978-3-319-66609-9
DOIs	https://doi.org/10.1007/978-3-319-66610-5_34
Publication status	Published - 1 Jan 2017
MoE publication type	A4 Article in a conference publication
Event	European Conference on Technology Enhanced Learning, EC-TEL 2017 - Tallinn, Estonia Duration: 12 Sept 2017 → 15 Sept 2017

Publication series

Series	Lecture Notes in Computer Science
Volume	10474
ISSN	0302-9743

Conference

Conference	European Conference on Technology Enhanced Learning, EC-TEL 2017
Abbreviated title	EC-TEL 2017
Country/Territory	Estonia
City	Tallinn
Period	12/09/17 → 15/09/17

Keywords

affordances
augmented reality
wearable technologies
capturing expertise

Access to Document

10.1007/978-3-319-66610-5_34

Cite this

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. (2017). Affordances for capturing and re-enacting expert performance with wearables. In J. Broisin, E. Lavoue, H. Drachsler, K. Verbert, & M. Perez-Sanagustin (Eds.), Data Driven Approaches in Digital Education: 12th European Conference on Technology Enhanced Learning, EC-TEL 2017 (pp. 403-409). Springer. Lecture Notes in Computer Science Vol. 10474 https://doi.org/10.1007/978-3-319-66610-5_34

Guest, Will ; Wild, Fridolin ; Vovk, Alla et al. / Affordances for capturing and re-enacting expert performance with wearables. Data Driven Approaches in Digital Education: 12th European Conference on Technology Enhanced Learning, EC-TEL 2017. editor / Julien Broisin ; Elise Lavoue ; Hendrik Drachsler ; Katrien Verbert ; Mar Perez-Sanagustin. Cham : Springer, 2017. pp. 403-409 (Lecture Notes in Computer Science, Vol. 10474).

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title = "Affordances for capturing and re-enacting expert performance with wearables",

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.",

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author = "Will Guest and Fridolin Wild and Alla Vovk and Mikhail Fominykh and Bibeg Limbu and Roland Klemke and Puneet Sharma and Jaakko Karjalainen and Carl Smith and Jazz Rasool and Soyeb Aswat and Kaj Helin and {Di Mitri}, Daniele and Jan Schneider",

note = "Funding Information: This research was supported in part by Food Animal Health and Disease grants (AL-V-132 and AL-V-127) from the College of Veterinary Medicine and by the Alabama Agricultural Experiment Station. The authors thank R. Carnes, A. Ammons, and L. Park for technical assistance and B. Reed of the Research Data Analysis Section for assistance with the PULSAR analysis of the data. Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; European Conference on Technology Enhanced Learning, EC-TEL 2017, EC-TEL 2017 ; Conference date: 12-09-2017 Through 15-09-2017",

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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 2017, Affordances for capturing and re-enacting expert performance with wearables. in J Broisin, E Lavoue, H Drachsler, K Verbert & M Perez-Sanagustin (eds), Data Driven Approaches in Digital Education: 12th European Conference on Technology Enhanced Learning, EC-TEL 2017. Springer, Cham, Lecture Notes in Computer Science, vol. 10474, pp. 403-409, European Conference on Technology Enhanced Learning, EC-TEL 2017, Tallinn, Estonia, 12/09/17. https://doi.org/10.1007/978-3-319-66610-5_34

Affordances for capturing and re-enacting expert performance with wearables. / Guest, Will; Wild, Fridolin; Vovk, Alla (Corresponding author) et al.
Data Driven Approaches in Digital Education: 12th European Conference on Technology Enhanced Learning, EC-TEL 2017. ed. / Julien Broisin; Elise Lavoue; Hendrik Drachsler; Katrien Verbert; Mar Perez-Sanagustin. Cham: Springer, 2017. p. 403-409 (Lecture Notes in Computer Science, Vol. 10474).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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AU - Guest, Will

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AU - Klemke, Roland

AU - Sharma, Puneet

AU - Karjalainen, Jaakko

AU - Smith, Carl

AU - Rasool, Jazz

AU - Aswat, Soyeb

AU - Helin, Kaj

AU - Di Mitri, Daniele

AU - Schneider, Jan

N1 - Funding Information: This research was supported in part by Food Animal Health and Disease grants (AL-V-132 and AL-V-127) from the College of Veterinary Medicine and by the Alabama Agricultural Experiment Station. The authors thank R. Carnes, A. Ammons, and L. Park for technical assistance and B. Reed of the Research Data Analysis Section for assistance with the PULSAR analysis of the data. Publisher Copyright: © Springer International Publishing AG 2017.

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AB - 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.

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BT - Data Driven Approaches in Digital Education

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Guest W, Wild F, Vovk A, Fominykh M, Limbu B, Klemke R et al. Affordances for capturing and re-enacting expert performance with wearables. In Broisin J, Lavoue E, Drachsler H, Verbert K, Perez-Sanagustin M, editors, Data Driven Approaches in Digital Education: 12th European Conference on Technology Enhanced Learning, EC-TEL 2017. Cham: Springer. 2017. p. 403-409. (Lecture Notes in Computer Science, Vol. 10474). doi: 10.1007/978-3-319-66610-5_34

Affordances for capturing and re-enacting expert performance with wearables

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Keywords

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