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GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
GymSkill - A Personal Trainer for Physical Exercises
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GymSkill - A Personal Trainer for Physical Exercises

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We present GymSkill, a personal trainer for ubiquitous monitoring and assessment of physical activity using standard fitness equipment. The system records and analyzes exercises using the sensors of a …

We present GymSkill, a personal trainer for ubiquitous monitoring and assessment of physical activity using standard fitness equipment. The system records and analyzes exercises using the sensors of a personal smartphone attached to the gym equipment. Novel fine-grained activity recognition techniques based on pyramidal Principal Component Breakdown Analysis (PCBA) provide a quantitative analysis of the quality of human movements. In addition to overall quality judgments, GymSkill identifies interesting portions of the recorded sensor data and provides
suggestions for improving the individual performance, thereby extending existing work. The system was evaluated in a case study where 6 participants performed a variety of exercises on balance boards. GymSkill successfully assessed the quality of the exercises, in agreement with the
professional judgment provided by a physician. User feedback suggests that GymSkill has the potential to serve as an effective tool for motivating
and supporting lay people to overcome sedentary, unhealthy lifestyles. GymSkill is available in the Android Market as "VMI Fit"

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  • 1. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität München GymSkill: A Personal Trainer for Physical Exercises Andreas Möller, Luis Roalter, Nils Hammerla, Patrick Olivier, Stefan Diewald, Johannes Scherr, Thomas Plötz Matthias Kranz Technische Universität München, Newcastle University, Germany United Kingdom March 22 PerCom 2012, Lugano, Switzerland
  • 2. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenOutline•  Motivation•  Automatic Assessment of Physical Exercises•  Case Study•  Conclusion04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 2
  • 3. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenMotivation•  Physical activity is required for healthy lifestyle•  Problem: people do not exercise enough –  Lack of knowledge of correct exercise execution for fast improvement –  High level of long-term motivation needed•  Advantages of a personal trainer: –  Continuous supervision and professional feedback –  Individualized advice and motivation –  Minimization of injury risk•  Disadvantages of a personal trainer: –  Expensive –  Privacy04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 3
  • 4. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenRelated Work•  Scientific focus on –  Activity recognition –  Wearable sensors•  Health and Fitness Systems –  Heart rate monitor, foot pod, GPS watch, … •  No skill assessment –  Fixed activity tracking (Wii balance board, Kinect) •  Gaming aspect •  Dedicated hardware04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 4
  • 5. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenGymSkill•  Smartphone-based personal trainer•  Monitoring and assessment of physical exercises –  Based on phone sensor data –  No need for additional sensors04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 5
  • 6. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenOutline•  Motivation•  Personal Health and Fitness Systems•  Automatic Assessment of Physical Exercises•  Case Study•  Conclusion04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 6
  • 7. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenGymSkill: Automatic Assessment of Physical Exercises•  We look at rocker board exercises•  Example use case for equipment-based training•  Defined quality criteria: tilt angles, speed, smoothness of movement, touching the ground…•  Phone is attached to the board•  During exercise: Basic situated feedback•  After exercise: Fine-grained analysis of exercise quality and reasons for quality differences move back and forth move left and right balance on the center04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 7
  • 8. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenSkill Assessment Principle Smartphone Server “Cloud“ Sensor Data Recording Log File Sensor Data Processing PCBA Analysis Simple Analysis Real-Time Feedback Skill Assessment HTTP Skill Level (Score) AJAX Detailed Skill Report Output Rendering User Feedback04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 8
  • 9. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenDirect Feedback While Training•  Repetition count•  Visual feedback of board movement•  Warning when tilted too far•  Optional acoustic feedback04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 9
  • 10. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenPost-Exercise Analysis•  Performed for each exercise run (e.g.: 10 repetitions of tilting back and forth)•  Global Analysis –  Smoothness and continuity of movement –  Global motion quality –  Usage of board‘s degrees of freedom•  Local Analysis –  Identify „interesting portions“ of sensor data –  What is „interesting“? In recurrent data, this means unusual data compared to the rest –  E.g. participant hesitates or gets stuck04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 10
  • 11. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenGlobal Analysis•  Estimation of motion axis (providing the dominant signal)•  Comparison of the empirical distribution to ideal distribution function („gold standard“)•  Usage of normalized and un-normalized functions to determine smoothness and utilization of board‘s degrees of freedom•  Transformation into a performance quality metric between 0 and 104.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 11
  • 12. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenLocal Analysis•  Assumption: sensor data of a movement shares (unknown) statistical properties•  Unusual portions of a sequence violate this assumption and can be identified•  Extension to PCA: Principal Component Breakdown Analysis•  PCA model is learned from local neighborhood (using sliding window technique)•  Frames are projected to lower-dimensional subspace using PCA•  Reconstruction errors used as a measure for motion quality•  Problem: ideal window size not known•  Solution: multi-scale comparison (iteratively growing window)04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 12
  • 13. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenUser Feedback     •  Visual feedback   –  PCA-based assessment diagram   (red and yellow parts contain irregularities)         •  Textual feedback –  Based on global and local metrics Try  to  be  more   –  Rule-based combination of aspects trigger continuous  in   textual cues your  motion!  •  “Thumb” feedback –  Overall assessment at a glance04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 13
  • 14. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenOutline•  Motivation•  Automatic Assessment of Physical Exercises•  Case Study•  Conclusion04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 14
  • 15. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenCase Study•  Set of 20 exercises developed by sports medicine specialist•  6 participants, 5 days of training (20 different exercises twice a day)•  1200 exercise records•  Goal 1: Collection of training data –  Identification of criteria and assessment by physician•  Goal 2: Qualitative evaluation of prototype –  Questionnaire study04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 15
  • 16. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München Case Study: Trial Assessment Example 1 PCBA: Continuity 5 10 15 20 Time [s] General motion Angle usage 0.2 0.25 Try to be more continuous in your motion! observed You touched the ground 3 times. ideal 0.2 0.15 Your movement is not ideal.frequency frequency 0.15 − Move back and forth in a continuous motion. 0.1 0.1 Try to move similarly to both sides of the board. 0.05 − You do not utilise the full range of angles! 0.05 − You lean towards the front! 0 0 −2 −1 0 1 2 −max 0 +max displacement [std] displacement [°] 04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 16
  • 17. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München Case Study: Trial Assessment Example 2 PCBA: Continuity 5 10 15 Time [s] General motion Angle usage 0.2 0.2 Your movement is continuous, nice! observed You did not touch the ground! 0.15 ideal 0.15 Overall you perform the movement nicely!frequency frequency Try to move similarly to both sides of the board. 0.1 0.1 − You do not utilise the full range of angles! 0.05 0.05 − You lean towards the front! 0 0 −2 −1 0 1 2 −max 0 +max displacement [std] displacement [°] 04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 17
  • 18. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München Qualitative FeedbackFully agreeNot agree at all 04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 18
  • 19. Fachgebiet Verteilte Multimodale Informationsverarbeitung Prof. Dr. Matthias Kranz Technische Universität München Qualitative Feedback •  Feature wishlist Fully agreeNot agree at all 04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 19
  • 20. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenOutline•  Motivation•  Automatic Assessment of Physical Exercises•  Case Study•  Conclusion04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 20
  • 21. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenSummary•  Mobile skill assessment of overall exercise quality•  Identification of typical exercising errors•  “Personal trainer”•  Participant feedback indicates potential for long-term exercising motivationFurther work:•  Long-term study on training progress•  Assessment and feedback entirely on mobile phone•  Generalization of assessment model04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 21
  • 22. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenGymSkill in Google Play04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 22
  • 23. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität München Thank you for your attention! Questions? ? ? andreas.moeller@tum.de www.vmi.ei.tum.de/team/andreas-moeller.html04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 23
  • 24. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenPaper Reference•  Please find the associated paper at: https://vmi.lmt.ei.tum.de/publications/2012/percom2012-preprint.pdf•  Please cite this work as follows:•  Andreas Möller, Luis Roalter, Stefan Diewald, Johannes Scherr, Matthias Kranz, Nils Hammerla, Patrick Olivier, Thomas Plötz GymSkill: A Personal Trainer for Physical Exercises In: 2012 IEEE International Conference on Pervasive Computing and Communications (PerCom2012), Lugano, Switzerland, March 2012, pp. 213-22004.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 24
  • 25. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenIf you use BibTex, please use the following entryto cite this work: @INPROCEEDINGS{6199869, author={M"{o}ller, Andreas and Roalter, Luis and Diewald, Stefan and Scherr, Johannes and Kranz, Matthias and Hammerla, Nils and Olivier, Patrick and Pl"{o}tz, Thomas}, booktitle={Pervasive Computing and Communications (PerCom), 2012 IEEE International Conference on}, title={GymSkill: A personal trainer for physical exercises}, year={2012}, month={march}, volume={}, number={}, pages={213 -220}, doi={10.1109/PerCom.2012.6199869}, ISSN={},}04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 25
  • 26. Fachgebiet Verteilte Multimodale InformationsverarbeitungProf. Dr. Matthias Kranz Technische Universität MünchenImage Sources•  Slide 5 –  gpsreview.net –  amazon.com –  spieleradar.de –  golem.de04.01.13 Andreas Möller et al. - GymSkill: A Personal Trainer for Physical Exercises 26

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