Company Info

Jiku is an open-source software company specializing in the advanced statistical analysis of continuum data.

Jiku's core software has been in development for 18 years, supported by public and private research grants, representing hundreds of peer-reviewed scientific publications .

Our main products are Jiku Core and Jiku UI (both in development). Our first fully released app is Jiku Power1D.

Jiku is dedicated to developing, curating and maintaining open-source software tools for the advanced analysis of continuum data.

Key benefits:

• Analyze complex continuum data quickly, objectively and in a statistically robust manner.
• Increase research efficiency and maximize objectivity.

Contact

• Email: admin@jiku.pro
• Address: 2/44 Barnfield Road, Claremont. WA, Australia 6010

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Our Team

Technical Team

Over 80 years in academic and business experience.

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Corporate Team

Over 80 years in multinational corporate experience.

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Publications

The Jiku team has published over 100 peer-reviewed papers in international journals that span Jiku's core technology.

Over 3000 applications papers have been published by third-party researchers that use Jiku's core open-source software.

Below is a selection of key technical papers underlying Jiku Core.

Selected papers:

• Seydi MR, Pataky TC, Strandberg J, Schelin L (2026). Influence of noise and effect characteristics on statistical power in the analyses of one-dimensional biomechanical trajectories. Journal of Biomechanics 113281.
• Seydi MR, Pini A, Pataky TC, Schelin L (2024). Confidence sets for intraclass correlation coefficients in test-retest curve measurements. Journal of Biomechanics 173, 112232.
• Pataky TC, Rao G (2024). Trial- vs. cycle-level detrending in the analysis of cyclical biomechanical data. Journal of Biomechanics 167, 112064.
• Pataky TC (2022). Using Monte Carlo simulation to propagate processing parameter uncertainty to the statistical analyses of biomechanical trajectories. Motor Control 27(1): 112-122.
• Pataky TC, Robinson MA, Vanrenterghem J, Donnelly CJW (2022). Simultaneously assessing amplitude and temporal effects in biomechanical trajectories using nonlinear registration and statistical nonparametric mapping. Journal of Biomechanics 136: 111049.
  
• Pataky TC, K Abramowicz, D Liebl, A Pini, S Sjöstedt de Luna, L Schelin (2021). Simultaneous inference for functional data in sports biomechanics: comparing statistical parametric mapping with interval-wise testing. AStA Advances in Statistical Analysis 107(1): 369-392.
• Pataky TC, Yagi M, Ichihashi N, Cox P (2021). Landmark-free, parametric hypothesis tests regarding two-dimensional contour shapes using coherent point drift registration and statistical parametric mapping. PeerJ Comp Sci 7: e542.
• Robinson MA, Vanrenterghem J, Pataky TC (2021). Sample size estimation for biomechanical waveforms: Current practice, recommendations and a comparison to discrete power analysis. Journal of Biomechanics 122: 110451.
• Pataky TC, Challis JH (2020). Using directional statistics to test hypotheses regarding rigid body attitude: comparison to univariate and multivariate Cardan angle tests. Journal of Biomechanics 111: 109976.
• Schwartz M, Pataky TC, Donnelly CJ (2020). Seg1d: A Python package for Automated segmentation of one-dimensional (1D) data. Journal of Open Source Software 5(52): 2404.
• Pataky TC, Naouma H, Donnelly CJ (2019). Mwarp1d: manual one-dimensional data warping in Python and PyQt. Journal of Open Source Software, 4(44), 1870.
• Naouma H, Pataky TC (2019). A comparison of random-field-theory and false-discovery-rate inference results in the analysis of registered one-dimensional biomechanical datasets. PeerJ 7: e8189.
• Pataky TC, Vanrenterghem J, Robinson MA, Liebl D (2019). On the validity of statistical parametric mapping for nonuniformly and heterogeneously smooth one-dimensional biomechanical data. Journal of Biomechanics 91: 114–123.
• Pataky TC, Robinson MA, Vanrenterghem J (2018). A computational framework for estimating statistical power and planning hypothesis-driven experiments involving one-dimensional biomechanical continua. Journal of Biomechanics 66(3): 159–164.
  
• Pataky TC (2017). Power1d: a Python toolbox for numerical power estimates in experiments involving one-dimensional continua. PeerJ Computer Science, 3:e125.
• Donnelly CJ, Alexander C, Pataky TC, Stannage K, Reid S, Robinson MA (2017). Vector-field statistics for the analysis of time varying clinical gait data. Clinical Biomechanics 41: 87-91.
• Pataky TC, Koseki M, Cox PG (2016). Probabilistic biomechanical finite element simulations: whole-model classical hypothesis testing based on upcrossing geometry. PeerJ Computer Science 2: e96.
  
• Pataky TC, Vanrenterghem J, Robinson MA (2016). Region-of-interest analyses of one-dimensional biomechanical trajectories: bridging 0D and 1D methods, augmenting statistical power. PeerJ 4: e2652.
• Pataky TC, Vanrenterghem J, Robinson MA (2016). The probability of false positives in zero-dimensional analyses of one-dimensional kinematic, force and EMG trajectories. Journal of Biomechanics 49(9): 1468-1476.
• Pataky TC (2016). rft1d: Smooth one-dimensional random field upcrossing probabilities in Python., Journal of Statistical Software, 71(7: i07.
• Pataky TC, Vanrenterghem J, Robinson MA (2015). Zero- vs. one-dimensional, parametric vs. non-parametric, and confidence interval vs. hypothesis testing procedures in one-dimensional biomechanical trajectory analysis. Journal of Biomechanics 48 (7): 1277–1285.
• Pataky TC, Robinson MA, Vanrenterghem J (2013). Vector field statistical analysis of kinematic and force trajectories. Journal of Biomechanics 46 (14): 2394-2401.
• Pataky TC (2012) One-dimensional statistical parametric mapping in Python. Computer Methods in Biomechanics and Biomedical Engineering 15, 295-301.
• Pataky TC (2010). Generalized n-dimensional biomechanical field analysis using statistical parametric mapping. Journal of Biomechanics 43, 1976-1982.