Human motion tracking system based on skeleton and surface integration model using pressure sensors distribution bed

Proposes a human motion tracking system based on a full-body model and a pressure-sensor distribution bed. The full-body model consists of a skeleton and a surface model. BVH files are used as the skeleton model that describes a hierarchy of joints and links. Wavefront object files are used as the surface model that describes the geometry of the surface. The bed has 210 pressure sensors that are under the mattress. It can measure the pressure distribution image of a lying person. The lying person's motion is tracked by considering potential energy, momentum and the difference between the measured pressure distribution image and the pressure distribution image that is calculated by the full-body model. Experimental results reveal that the realized system can track not only horizontal motions such as opening and closing legs but also vertical motions such as raising the upper body.

[1]  T Togawa,et al.  A system for monitoring temperature distribution in bed and its application to the assessment of body movement. , 1993, Physiological measurement.

[2]  Tomomasa Sato,et al.  Infant behavior recognition system based on pressure distribution image , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[3]  D. L. Jaffe,et al.  Development of a second generation wearable accelerometric motion analysis system , 1999, Proceedings of the First Joint BMES/EMBS Conference. 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society (Cat. N.

[4]  Alex Pentland,et al.  Understanding purposeful human motion , 1999, Proceedings IEEE International Workshop on Modelling People. MPeople'99.

[5]  Tomomasa Sato,et al.  Body parts positions and posture estimation system based on pressure distribution image , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[6]  Hiroshi Mizoguchi,et al.  Monitoring patient respiration and posture using human symbiosis system , 1997, Proceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Innovative Robotics for Real-World Applications. IROS '97.

[7]  J. Alihanka,et al.  A new method for long-term monitoring of the ballistocardiogram, heart rate, and respiration. , 1981, The American journal of physiology.

[8]  Takeo Kanade,et al.  Visual Tracking of High DOF Articulated Structures: an Application to Human Hand Tracking , 1994, ECCV.

[9]  J. O'Rourke,et al.  Model-based image analysis of human motion using constraint propagation , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.