Abstract
The purpose of this study was to investigate the benefit of landmark registration when applied to waveform data. We compared the ability of data reduced from time-normalised and landmark registered vertical ground
reaction force (vGRF) waveforms captured during maximal countermovement jumps (CMJ) of 53 active male subjects to predict jump height. vGRF waveforms were landmark registered using different landmarks resulting in
four registration conditions: (i) end of the eccentric phase, (ii) adding maximum centre of mass (CoM) power, (iii) adding minimum CoM power, (iv) adding minimum vGRF. In addition to the four registration conditions, the
non-registered vGRF and concentric phase only were time-normalised and used in subsequent analysis. Analysis of characterising phases was performed to reduce the vGRF data to features that captured the behaviour of each waveform. These features were extracted from each condition’s vGRF waveform, time-domain (time taken to complete the movement), and warping functions (generated from landmark registration). The
identified features were used as predictor features to fit a step-wise multilinear regression to jump height. Features generated from the best performing registration condition were able to predict jump height to a similar
extent as the concentric phase (86–87%), while all registration conditions could explain jump height to a greater extent than time-normalisation alone (65%). This suggests waveform variability was reduced as phases of the
CMJ were aligned. However, findings suggest that over-registration can occur when applying landmark registration. Overall, landmark registration can improve prediction power to performance measures as waveform data
can be reduced to more appropriate performance related features.
© 2018, Elsevier. The attached document (embargoed until 03/08/2019) is an author produced version of a paper published in JOURNAL OF BIOMECHANICS uploaded in accordance with the publisher’s self- archiving policy. The final published version (version of record) is available online at the link below. Some minor differences between this version and the final published version may remain. We suggest you refer to the final published version should you wish to cite from it.
reaction force (vGRF) waveforms captured during maximal countermovement jumps (CMJ) of 53 active male subjects to predict jump height. vGRF waveforms were landmark registered using different landmarks resulting in
four registration conditions: (i) end of the eccentric phase, (ii) adding maximum centre of mass (CoM) power, (iii) adding minimum CoM power, (iv) adding minimum vGRF. In addition to the four registration conditions, the
non-registered vGRF and concentric phase only were time-normalised and used in subsequent analysis. Analysis of characterising phases was performed to reduce the vGRF data to features that captured the behaviour of each waveform. These features were extracted from each condition’s vGRF waveform, time-domain (time taken to complete the movement), and warping functions (generated from landmark registration). The
identified features were used as predictor features to fit a step-wise multilinear regression to jump height. Features generated from the best performing registration condition were able to predict jump height to a similar
extent as the concentric phase (86–87%), while all registration conditions could explain jump height to a greater extent than time-normalisation alone (65%). This suggests waveform variability was reduced as phases of the
CMJ were aligned. However, findings suggest that over-registration can occur when applying landmark registration. Overall, landmark registration can improve prediction power to performance measures as waveform data
can be reduced to more appropriate performance related features.
© 2018, Elsevier. The attached document (embargoed until 03/08/2019) is an author produced version of a paper published in JOURNAL OF BIOMECHANICS uploaded in accordance with the publisher’s self- archiving policy. The final published version (version of record) is available online at the link below. Some minor differences between this version and the final published version may remain. We suggest you refer to the final published version should you wish to cite from it.
| Original language | English |
|---|---|
| Pages (from-to) | 109-117 |
| Number of pages | 9 |
| Journal | Journal of Biomechanics |
| Volume | 78 |
| Early online date | 3 Aug 2018 |
| DOIs | |
| Publication status | Published - 10 Sept 2018 |
Keywords
- Journal Article
Profiles
-
Siobhan Strike
- School of Life and Health Sciences - Honorary Research Fellow
- Centre for Integrated Research in Life and Health Sciences - Honorary Research Fellow
Person