Neural Networks Classification for Training of Five German Longsword Mastercuts - A Novel Application of Motion Capture: Analysis of Performance of Sword Fencing in the Historical European Martial Arts (HEMA) Domain

Klempous, R; Kluwak, K; Atsushi, I; Gorski, T; Nikodem, J; Bozejko, W; Chaczko, Z; Borowik, G; Rozenblit, J; Kulbacki, M

Neural Networks Classification for Training of Five German Longsword Mastercuts - A Novel Application of Motion Capture: Analysis of Performance of Sword Fencing in the Historical European Martial Arts (HEMA) Domain

Klempous, R Kluwak, K Atsushi, I Gorski, T Nikodem, J Bozejko, W Chaczko, Z

Borowik, G Rozenblit, J Kulbacki, M

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2021 IEEE 21st International Symposium on Computational Intelligence and Informatics (CINTI), 2022, 00, pp. 137-142
Issue Date:: 2022-01-12

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Field	Value	Language
dc.contributor.author	Klempous, R
dc.contributor.author	Kluwak, K
dc.contributor.author	Atsushi, I
dc.contributor.author	Gorski, T
dc.contributor.author	Nikodem, J
dc.contributor.author	Bozejko, W
dc.contributor.author	Chaczko, Z https://orcid.org/0000-0002-2816-7510
dc.contributor.author	Borowik, G
dc.contributor.author	Rozenblit, J
dc.contributor.author	Kulbacki, M
dc.contributor.editor	Szakal, A
dc.date	2021-11-18
dc.date.accessioned	2023-04-06T05:20:56Z
dc.date.available	2023-04-06T05:20:56Z
dc.date.issued	2022-01-12
dc.identifier.citation	2021 IEEE 21st International Symposium on Computational Intelligence and Informatics (CINTI), 2022, 00, pp. 137-142
dc.identifier.isbn	9781665426848
dc.identifier.issn	2380-8586
dc.identifier.issn	2471-9269
dc.identifier.uri	http://hdl.handle.net/10453/169351
dc.description.abstract	This paper discusses an application of motion capture in longsword fencing, a discipline experiencing rising popularity since the 1990s. Historical European Martial Arts alliance focuses on re-enacting the Late Middle Ages and Renaissance fighting styles. To popularize this art, novel research to automatically distinguish selected sword cutting techniques has been conducted. The fencing knowledge required for conducting this research was based on publications and consultation with experts in the field, and recordings. For this research, different movements from Masterstrikes such as Zornhau (Strike of Wrath), Schielhau (Squinting Strike), Zwerchhau (Cross Strike), Krumphau (Crooked Strike), Scheitelhau (Crown Strike) were selected. Motions performed by an adept fencer (acting expert) were used as patterns of correct strikes and compared with the movements of fencing amateurs. The main goal of this research was to measure the precision of movement while performing five different fencing strokes. Each movement was recorded with 39 unique full-body plug-in gait configurations initially designed for medical applications. During the exercise, 16 EMG electrodes configuration was used for the measurement of muscle activity.
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2021 IEEE 21st International Symposium on Computational Intelligence and Informatics (CINTI)
dc.relation.ispartof	2021 IEEE 21st International Symposium on Computational Intelligence and Informatics
dc.relation.ispartofseries	International Symposium on Computational Intelligence and Informatics
dc.relation.isbasedon	10.1109/cinti53070.2021.9668598
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Neural Networks Classification for Training of Five German Longsword Mastercuts - A Novel Application of Motion Capture: Analysis of Performance of Sword Fencing in the Historical European Martial Arts (HEMA) Domain
dc.type	Conference Proceeding
utslib.citation.volume	00
utslib.location.activity	Budapest, Hungary
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2023-04-06T05:20:55Z
pubs.finish-date	2021-11-20
pubs.publication-status	Published
pubs.start-date	2021-11-18
pubs.volume	00

Abstract:

This paper discusses an application of motion capture in longsword fencing, a discipline experiencing rising popularity since the 1990s. Historical European Martial Arts alliance focuses on re-enacting the Late Middle Ages and Renaissance fighting styles. To popularize this art, novel research to automatically distinguish selected sword cutting techniques has been conducted. The fencing knowledge required for conducting this research was based on publications and consultation with experts in the field, and recordings. For this research, different movements from Masterstrikes such as Zornhau (Strike of Wrath), Schielhau (Squinting Strike), Zwerchhau (Cross Strike), Krumphau (Crooked Strike), Scheitelhau (Crown Strike) were selected. Motions performed by an adept fencer (acting expert) were used as patterns of correct strikes and compared with the movements of fencing amateurs. The main goal of this research was to measure the precision of movement while performing five different fencing strokes. Each movement was recorded with 39 unique full-body plug-in gait configurations initially designed for medical applications. During the exercise, 16 EMG electrodes configuration was used for the measurement of muscle activity.

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http://hdl.handle.net/10453/169351