论文信息 - Explaining machine learning models for age classification in human gait analysis - 字舞流文

Explaining machine learning models for age classification in human gait analysis

S. Lapuschkin | W. Samek | W. Schöllhorn | C. Breiteneder | M. Zeppelzauer | B. Horsak | D. Slijepcevic | F. Horst | Anna-Maria Raberger | Marvin Simak

[1] T. Hortobágyi,et al. The detection of age groups by dynamic gait outcomes using machine learning approaches , 2020, Scientific Reports.

[2] Madalina Fiterau,et al. Machine learning in human movement biomechanics: Best practices, common pitfalls, and new opportunities. , 2018, Journal of biomechanics.

[3] J. Banks,et al. Systematic review and meta-analysis of gait mechanics in young and older adults , 2017, Experimental Gerontology.

[4] Alexander Binder,et al. On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation , 2015, PloS one.

[5] Akinori Nagano,et al. Age and gender differences in the control of vertical ground reaction force by the hip, knee and ankle joints , 2015, Journal of physical therapy science.

[6] Benno M Nigg,et al. Marker-based classification of young–elderly gait pattern differences via direct PCA feature extraction and SVMs , 2013, Computer methods in biomechanics and biomedical engineering.

[7] Thomas P Andriacchi,et al. The role of physical activity in changes in walking mechanics with age. , 2012, Gait & posture.

[8] R Begg,et al. A machine learning approach for automated recognition of movement patterns using basic, kinetic and kinematic gait data. , 2005, Journal of biomechanics.