Classification of Changes in Speed

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Classification of Changes in Speed and
Inclination during Running

Bjoern Eskofier

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Classification of Changes in Speed

  1. 1. Classification of Changes in Speed and Inclination during Running Bjoern Eskofier, Dr. Benno Nigg Human Performances Lab (HPL) University of Calgary, Canada Martin Wagner Chair of Pattern Recognition University of Erlangen, Germany Mark Oleson, Ian Munson adidas innovation team, adidas AG A Digital Sports Embedded Classification Task September 24, 2009
  2. 2. Digital Revolution – Even In Sports The adidas_1: “the world‘s first intelligent shoe” Direct processing of sport- specific information Microprocessor adapts the shoe to the run situation Intelligence modeled by Pattern Recognition B. Eskofier Running Speed and Inclination Classification September 24, 2009 IACSS09, Canberra, Australia
  3. 3. Overview of the Talk Introduction Data collection Methods Results Discussion Acknowledgments B. Eskofier Running Speed and Inclination Classification September 24, 2009 IACSS09, Canberra, Australia
  4. 4. Introduction Runners need different cushioning Inclination, speed, …: changing demands adidas_1 developed for that Ideal cushioning: pattern recognition Embedded task: cheap computations B. Eskofier Running Speed and Inclination Classification September 24, 2009 IACSS09, Canberra, Australia
  5. 5. Introduction – adidas_1 3 adidas_1 main parts Cushioning element (01) with compression measurement Microcontroller (02) Motor for cushioning adaptation (03) B. Eskofier Running Speed and Inclination Classification September 24, 2009 IACSS09, Canberra, Australia
  6. 6. Introduction – Pattern Recognition Sensors Preprocessing Features Classification Online analysis Offline analysis Data Sample Learning Challenges: - Hardware environment - Real-time classification B. Eskofier Running Speed and Inclination Classification September 24, 2009 IACSS09, Canberra, Australia
  7. 7. Data Collection 84 runners (30 ♀, 54 ♂) - 56 usable Measurement device 1: Polar RS 800 Measurement device 2: Cell phone Eskofier et el., 2008 B. Eskofier Running Speed and Inclination Classification September 24, 2009 IACSS09, Canberra, Australia
  8. 8. Data Collection – adidas_1 Measurement device 3: adidas_1 Magnet at bottom, Hall sensor at top of cushioning element Measures compression of the heel B. Eskofier Running Speed and Inclination Classification September 24, 2009 IACSS09, Canberra, Australia
  9. 9. Methods – Features Eskofier et al., 2009 Step detection: linear filter 11 features + Mean {4,8,16} + SD {4,8,16} + Gradients {16} 88 features B. Eskofier Running Speed and Inclination Classification September 24, 2009 IACSS09, Canberra, Australia
  10. 10. Methods – Labels Definition of 3 inclination classes α < -3° -3° ≤ α ≤ 3° 3° < α Definition of 3 speed classes [m/s] 0 ≤ v < 2.5 2.5 ≤ v < 3.6 3.6 ≤ v B. Eskofier Running Speed and Inclination Classification September 24, 2009 IACSS09, Canberra, Australia
  11. 11. Methods – Classifiers Bayes Classifier (BC) Polynomial Classifier (PC) Linear Discriminant Analysis (LDA) Support Vector Machine (SVM) Multilayer Perceptron (MLP) B. Eskofier Running Speed and Inclination Classification September 24, 2009 IACSS09, Canberra, Australia
  12. 12. Methods – Classification 5 fold Cross-Validation 105 random vectors from each class Feature selection: dynamic programming with Mahalanobis distance G T Gk ,l = (µk − µ l ) Σ −1 (µk − µ l ) B. Eskofier Running Speed and Inclination Classification September 24, 2009 IACSS09, Canberra, Australia
  13. 13. Results – Inclination Classification B. Eskofier Running Speed and Inclination Classification September 24, 2009 IACSS09, Canberra, Australia
  14. 14. Results – Speed Classification B. Eskofier Running Speed and Inclination Classification September 24, 2009 IACSS09, Canberra, Australia
  15. 15. Discussion Inclination classifier not implemented Speed classifier implemented accuracy rise for 2 features (all methods) further accuracy rise: 4 features (BC, SVM, MLP) two feature approach (µ16(F1), µ16(F3)) SVM as classifier Microcontroller implementation successful B. Eskofier Running Speed and Inclination Classification September 24, 2009 IACSS09, Canberra, Australia
  16. 16. Acknowledgments Running study participants Colleagues and reviewers Pascal Kuehner (University of Landau) adidas innovation team ait. B. Eskofier Running Speed and Inclination Classification September 24, 2009 IACSS09, Canberra, Australia
  17. 17. B. Eskofier Running Speed and Inclination Classification September 24, 2009 IACSS09, Canberra, Australia

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