Details
| Original language | English |
|---|---|
| Title of host publication | Handbook of Human Motion |
| Publisher | Springer International Publishing AG |
| Pages | 267-292 |
| Number of pages | 26 |
| Volume | 1-3 |
| ISBN (electronic) | 9783319144184 |
| ISBN (print) | 9783319144177 |
| Publication status | Published - 4 Apr 2018 |
Abstract
This chapter deals with fundamental methods as well as current research on physics-based human gait analysis. We present valuable concepts that allow efficient modeling of the kinematics and the dynamics of the human body. The resulting physical model can be included in an optimization-based framework. In this context, we show how forward dynamics optimization can be used to determine the producing forces of gait patterns. To present a current subject of research, we provide a description of a 2D physics-based statistical model for human gait analysis that exploits parameter learning to estimate unobservable joint torques and external forces directly from motion input. The robustness of this algorithm with respect to occluded joint trajectories is shown in a short experiment. Furthermore, we present a method that uses the former techniques for video-based gait analysis by combining them with a nonrigid structure from motion approach. To examine the applicability of this method, a brief evaluation of the performance regarding joint torque and ground reaction force estimation is provided.
Keywords
- 3D motion reconstruction, Computer vision, Data-driven regression, Forward dynamics optimization, Human motion analysis, Physics-based simulation, Video-based force estimation
ASJC Scopus subject areas
- Engineering(all)
- General Engineering
- Medicine(all)
- General Medicine
- Computer Science(all)
- General Computer Science
Sustainable Development Goals
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Handbook of Human Motion. Vol. 1-3 Springer International Publishing AG, 2018. p. 267-292.
Research output: Chapter in book/report/conference proceeding › Contribution to book/anthology › Research › peer review
}
TY - CHAP
T1 - Physics-based models for human gait analysis
AU - Zell, Petrissa
AU - Wandt, Bastian
AU - Rosenhahn, Bodo
PY - 2018/4/4
Y1 - 2018/4/4
N2 - This chapter deals with fundamental methods as well as current research on physics-based human gait analysis. We present valuable concepts that allow efficient modeling of the kinematics and the dynamics of the human body. The resulting physical model can be included in an optimization-based framework. In this context, we show how forward dynamics optimization can be used to determine the producing forces of gait patterns. To present a current subject of research, we provide a description of a 2D physics-based statistical model for human gait analysis that exploits parameter learning to estimate unobservable joint torques and external forces directly from motion input. The robustness of this algorithm with respect to occluded joint trajectories is shown in a short experiment. Furthermore, we present a method that uses the former techniques for video-based gait analysis by combining them with a nonrigid structure from motion approach. To examine the applicability of this method, a brief evaluation of the performance regarding joint torque and ground reaction force estimation is provided.
AB - This chapter deals with fundamental methods as well as current research on physics-based human gait analysis. We present valuable concepts that allow efficient modeling of the kinematics and the dynamics of the human body. The resulting physical model can be included in an optimization-based framework. In this context, we show how forward dynamics optimization can be used to determine the producing forces of gait patterns. To present a current subject of research, we provide a description of a 2D physics-based statistical model for human gait analysis that exploits parameter learning to estimate unobservable joint torques and external forces directly from motion input. The robustness of this algorithm with respect to occluded joint trajectories is shown in a short experiment. Furthermore, we present a method that uses the former techniques for video-based gait analysis by combining them with a nonrigid structure from motion approach. To examine the applicability of this method, a brief evaluation of the performance regarding joint torque and ground reaction force estimation is provided.
KW - 3D motion reconstruction
KW - Computer vision
KW - Data-driven regression
KW - Forward dynamics optimization
KW - Human motion analysis
KW - Physics-based simulation
KW - Video-based force estimation
UR - http://www.scopus.com/inward/record.url?scp=85078714213&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-14418-4_164
DO - 10.1007/978-3-319-14418-4_164
M3 - Contribution to book/anthology
AN - SCOPUS:85078714213
SN - 9783319144177
VL - 1-3
SP - 267
EP - 292
BT - Handbook of Human Motion
PB - Springer International Publishing AG
ER -