Mirrored Motion: Augmenting Reality and Implementing Whole Body Gestural Control Using Pervasive Body Motion Capture Based on Wireless Sensors

Motion capture systems play an important role in health-care and sport-training systems. In particular, there exists a great demand on a mobile motion capture system that enables people to monitor their health condition and to practice sport postures anywhere at any time. The motion capture systems with infrared or vision cameras, however, require a special setting, which hinders their application to a mobile system. In this paper, a mobile three-dimensional motion capture system is developed based on inertial sensors and smart shoes. Sensor signals are measured and processed by a mobile computer; thus, the proposed system enables the analysis and diagnosis of postures during outdoor sports, as well as indoor activities. The measured signals are transformed into quaternion to avoid the Gimbal lock effect. In order to improve the precision of the proposed motion capture system in an open and outdoor space, a frequency-adaptive sensor fusion method and a kinematic model are utilized to construct the whole body motion in real-time. The reference point is continuously updated by smart shoes that measure the ground reaction forces.

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Correcting whole‐body motion capture data using rigid body transformation

European Journal of Neuroscience ◽

10.1111/ejn.15531 ◽

2021 ◽

Author(s):

Makoto Miyakoshi

Keyword(s):

Rigid Body ◽

Motion Capture ◽

Body Motion ◽

Whole Body ◽

Motion Capture Data ◽

Rigid Body Transformation

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WHOLE-BODY MOTION GENERATION OF ANDROID ROBOT USING MOTION CAPTURE AND NONLINEAR CONSTRAINED OPTIMIZATION

International Journal of Humanoid Robotics ◽

10.1142/s0219843613500035 ◽

2013 ◽

Vol 10 (02) ◽

pp. 1350003 ◽

Cited By ~ 2

Author(s):

JUNG-YUP KIM ◽

YOUNG-SEOG KIM

Keyword(s):

Constrained Optimization ◽

Motion Capture ◽

Optimization Technique ◽

Human Motion ◽

Body Motion ◽

Whole Body ◽

Motion Generation ◽

Nonlinear Constrained Optimization ◽

Gimbal Lock ◽

Android Robot

This paper describes a whole-body motion generation scheme for an android robot using motion capture and an optimization method. Android robots basically require human-like motions due to their human-like appearances. However, they have various limitations on joint angle, and joint velocity as well as different numbers of joints and dimensions compared to humans. Because of these limitations and differences, one appropriate approach is to use an optimization technique for the motion capture data. Another important issue in whole-body motion generation is the gimbal lock problem, where a degree of freedom at the three-DOF shoulder disappears. Since the gimbal lock causes two DOFs at the shoulder joint diverge, a simple and effective strategy is required to avoid the divergence. Therefore, we propose a novel algorithm using nonlinear constrained optimization with special cost functions to cope with the aforementioned problems. To verify our algorithm, we chose a fast boxing motion that has a large range of motion and frequent gimbal lock situations as well as dynamic stepping motions. We then successfully obtained a suitable boxing motion very similar to captured human motion and also derived a zero moment point (ZMP) trajectory that is realizable for a given android robot model. Finally, quantitative and qualitative evaluations in terms of kinematics and dynamics are carried out for the derived android boxing motion.

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Validation of a low-cost inertial motion capture system for whole-body motion analysis

Journal of Biomechanics ◽

10.1016/j.jbiomech.2019.109520 ◽

2020 ◽

Vol 99 ◽

pp. 109520 ◽

Cited By ~ 6

Author(s):

X. Robert-Lachaine ◽

H. Mecheri ◽

A. Muller ◽

C. Larue ◽

A. Plamondon

Keyword(s):

Motion Analysis ◽

Motion Capture ◽

Low Cost ◽

Body Motion ◽

Whole Body ◽

Motion Capture System ◽

Inertial Motion

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In situ sensor-to-segment calibration for whole body motion capture

2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN) ◽

10.1109/bsn.2015.7299412 ◽

2015 ◽

Cited By ~ 1

Author(s):

Krittameth Teachasrisaksakul ◽

Zhi-Qiang Zhang ◽

Guang-Zhong Yang

Keyword(s):

Motion Capture ◽

Body Motion ◽

Whole Body ◽

In Situ Sensor

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Interaction Preference Differences between Elderly and Younger Exergame Users

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph182312583 ◽

2021 ◽

Vol 18 (23) ◽

pp. 12583

Author(s):

Ying Wang ◽

Yuanyuan Huang ◽

Junjie Xu ◽

Defu Bao

Keyword(s):

Motion Capture ◽

Interaction Design ◽

The Body ◽

Body Motion ◽

Whole Body ◽

Heuristic Evaluation ◽

Four Dimensions ◽

Body Interaction ◽

Interactive Games ◽

Elderly Users

Existing motion capture technology can efficiently track whole-body motion and be applied to many areas of the body. This whole-body interaction design has gained the attention of many researchers. However, few scholars have studied its suitability for elderly users. We were interested in exercise-based whole-body interactive games, which can provide mental and physical exercise for elderly users. We used heuristic evaluation to measure participants’ actions during exergame tasks and analyzed preference differences between elderly and younger users through the distribution of actions in four dimensions. We found that age affected the actions performed by users in exergame tasks. We discuss the mental model of elderly users during the process of performing these tasks and put forward some suggestions for interactive actions. This model and these suggestions theoretically have guiding significance for the research and application of exergame design for elderly users and may help designers develop more effective exergames or other whole-body interaction interfaces suitable for elderly users.

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8B46 4D human body posture estimation based on whole-body motion capture data

The Proceedings of the Bioengineering Conference Annual Meeting of BED/JSME ◽

10.1299/jsmebio.2012.24.8b46 ◽

2012 ◽

Vol 2012.24 (0) ◽

pp. 8B46

Author(s):

Naoya YOSHIKAWA ◽

Yasuyuki SUZUKI ◽

Wataru OZAKI ◽

Tomohisa YAMAMOTO ◽

Taishin NOMURA

Keyword(s):

Motion Capture ◽

Human Body ◽

Body Posture ◽

Body Motion ◽

Whole Body ◽

Motion Capture Data ◽

Posture Estimation

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From human motion capture to humanoid locomotion imitation Application to the robots HRP-2 and HOAP-3

Robotica ◽

10.1017/s0263574710000172 ◽

2010 ◽

Vol 29 (2) ◽

pp. 325-334 ◽

Cited By ~ 14

Author(s):

Luc Boutin ◽

Antoine Eon ◽

Said Zeghloul ◽

Patrick Lacouture

Keyword(s):

Motion Capture ◽

Human Locomotion ◽

Inverse Kinematic ◽

Human Motion ◽

Simulation Software ◽

Body Motion ◽

Whole Body ◽

Human Gait ◽

Reference Trajectory ◽

Double Support

SUMMARYThis paper presents a method to generate humanoid gaits from a human locomotion pattern recorded by a motion capture system. Thirty seven reflective markers were fixed on the human subject skin in order to get the subject whole body motion. To reproduce the human gait, especially the toes and heel contacts, the front and back edges of the robot's feet are used as support at the start and the end of the double support phase. The balance of the robot is respected using the zero moment point (ZMP) criterion and confirmed by the simulation software OPENHRP (General Robotics, Inc®). First, the feet trajectory as well as the ZMP reference trajectory are defined from the motion of the robot controlled as a marionette with the measured human joint angles. Then a specific inverse kinematic (IK) algorithm is proposed to find the humanoid robot's joint trajectories respecting the constraints of balance, floor contacts, and joint limits. The studied motion presented in this paper is a human walking trajectory containing a start, a movement in a straight line, a stop, and a quarter turn. The method was developed to be easily used for human-like robots of different sizes, masses, and structures and has been tested on the robot HRP-2 (AIST, Kawada Industries, Inc®) and on the small-sized humanoid robot HOAP-3 (Fujitsu Automation Ltd®).

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