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  5. The effect of acceleration signal processing for head impact numeric simulations
 
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The effect of acceleration signal processing for head impact numeric simulations

Author(s)
Post, Andrew  
Clark, J. Michio  
Robertson, D.G.E.  
Hoshizaki, Thomas Blaine  
Gilchrist, M. D.  
Uri
http://hdl.handle.net/10197/8681
Date Issued
2016-06
Date Available
2017-10-18T01:00:09Z
Abstract
Brain injury research in sport employs a variety of physical models equipped with accelerometers. These acceleration signals are commonly processed using filters. The purpose of this research was to determine the effect of applying filters with different cutoff frequencies to the acceleration signals used as input for finite element modelling of the brain. Signals were generated from reconstructions of concussion events from American football and ice hockey in the laboratory using a Hybrid III headform. The resulting acceleration signals were used as input for the University College Dublin Brain Trauma Model after being processed with filters. The results indicated that using a filter with a cutoff of 300 Hz or higher had little effect on the resulting strain measures. In some cases there was some effect of the filters on the peak linear (8¿30g) and rotational measures (1000¿4000 rad/s2), but little effect on the finite element strain result (approximately 2¿6 %). The short duration and high magnitude accelerations, such as the puck impact, were most affected by the cutoff frequency of different filters.
Type of Material
Journal Article
Publisher
Springer
Journal
Sports Engineering
Copyright (Published Version)
2016 International Sports Engineering Association
Subjects

Signal processing

Filtering

Concussion

mTBI

Biomechanics

Ice hockey

American football

DOI
10.1007/s12283-016-0219-5
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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Post_et_al._2016_-_Filtering_Effects_-_UCD_Repository.pdf

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646.76 KB

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47d09b2dba3ea201419ea893937d0171

Owning collection
Mechanical & Materials Engineering Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
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