Literature DB >> 32287092

Low-Pass Filter Effects on Metrics of Countermovement Vertical Jump Performance.

John R Harry1, Jarrod Blinch2, Leland A Barker3, John Krzyszkowski1, Luke Chowning1.   

Abstract

ABSTRACT: Harry, JR, Blinch, J, Barker, LA, Krzyszkowski, J, and Chowning, L. Low-pass filter effects on metrics of countermovement vertical jump performance. J Strength Cond Res 36(5): 1459-1467, 2022-Countermovement vertical jump (CMVJ) studies using ground reaction force (GRF) data analyze either unfiltered (i.e., raw) or filtered data while providing little-to-no justification for the selected filtering process. Inappropriate filter choices can lead to inaccurate study results and erroneous interpretations. We examined the effects of not filtering GRF data in comparison with filtering data with various objectively and subjectively selected cutoff frequencies. Twenty-one collegiate male basketball players completed 3 maximal-effort CMVJ trials while GRF data were obtained from 2 force platforms. Countermovement vertical jump performance, explosiveness, power output, and neuromuscular function variables were compared among the following methods using one-way repeated-measures analyses of variance (α = 0.05): no filtering (raw data), a standard 50-Hz cutoff (50 Hz), a visually determined cutoff frequency describing the frequency band containing the majority of the summed (visual inspection 1) or not-summed (visual inspection 2) GRF signal's frequency content, filtering the summed (99% signal power 1) or not-summed (99% signal power 2) GRF using a cutoff frequency retaining 99% of the signal power. The raw data method produced significantly shorter concentric phase times and significantly greater center of mass flight heights (∼3%), modified reactive strength indices (RSIMOD; ∼4%), power outputs (∼6%), and push-off distances (∼4%) than 99% signal power 1 and 2 (p < 0.05). Discrete GRF and phase-specific yank magnitudes were not different among methods (p ≥ 0.05). Importantly, no differences were detected between the raw data and 50 Hz methods for any variable (p > 0.05). Low-pass filtering is not necessary when analyzing GRF data from the CMVJ. However, a low-pass filter with a 50-Hz cutoff can remove noise without altering results when compared with raw data. Explicit methodological descriptions of filtering processes should always be provided to improve the integrity of future CMVJ analyses, comparisons among various studies' results, or both.
Copyright © 2020 National Strength and Conditioning Association.

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Year:  2020        PMID: 32287092     DOI: 10.1519/JSC.0000000000003611

Source DB:  PubMed          Journal:  J Strength Cond Res        ISSN: 1064-8011            Impact factor:   3.775


  2 in total

1.  Validity and Reliability of Strategy Metrics to Assess Countermovement Jump Performance using the Newly Developed My Jump Lab Smartphone Application.

Authors:  Chris Bishop; Paul Jarvis; Anthony Turner; Carlos Balsalobre-Fernandez
Journal:  J Hum Kinet       Date:  2022-09-08       Impact factor: 2.923

2.  Identifying and reporting position-specific countermovement jump outcome and phase characteristics within rugby league.

Authors:  John J McMahon; Jason P Lake; Paul Comfort
Journal:  PLoS One       Date:  2022-03-25       Impact factor: 3.240

  2 in total

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