Perturbation-based estimation of within-stride cycle metabolic cost

Table 2 Evaluation of perturbation-based method in human experiment dataset

Stride mean metabolic cost input	Selected mathematically derived combination of biomechanical time series	Estimated versus actual time series correlation ^┼
Beck et al., 2019	Hip angle – vastus medilias + gluteus maximus + vertical GRF	0.86
Kim and Roberts, 2015	(Positive portion of hip power)	0.41
Margaria, 1968 COM-based	(COM power positive portion) * soleus + vertical GRF	0.91
Margaria, 1968 joint-based	(COM power positive portion) * vastus medialis + vertical GRF	0.78
Minetti and Alexander, 1997	(COM power positive portion) * tibialis anterior + vertical GRF	0.83
\(\:\dot{V}{O}_{2}\) and \(\:\dot{V}C{O}_{2}\)	Hip angle – tibialis anterior + gastrocnemius + vertical GRF	N/A ^#
Mean Pearson correlation 0.80 (95% CI = 0.57–0.91)^*

┼ The final column lists correlations between model-based within-stride metabolic costs and estimations of these costs using the perturbation-based method (Fig. 4 FJ). The stride mean metabolic costs used as inputs for the perturbation-based estimation are named in the first column. The Pearson correlations serve as a measure of the estimation performance
* Mean Pearson correlation and confidence interval are calculated following Fisher Z transformation
# The final row shows the combination that was selected to plot the within-stride metabolic cost time series based on respiratory V̇O₂ and V̇CO₂ data. In this application, there was no reference to compare our estimation-performance against; hence no correlation is reported

ISSN: 1743-0003