Yoon Sang Ho, Jun Hong Gul, Dan Byung Ju, Jo Byeong Rim, Min Byung Hoon
Convergence Laboratory, LG Electronics Inc., 221, Yanjae-Dong, Seoul 137-130, Korea.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:1940-3. doi: 10.1109/EMBC.2012.6346334.
Motion capture analysis of sit-to-stand task with assistive device is hard to achieve due to obstruction on reflective makers. Previously developed robotic system, Smart Mobile Walker, is used as an assistive device to perform motion capture analysis in sit-to-stand task. All lower limb markers except hip markers are invisible through whole session. The link-segment and regression method is applied to estimate the marker position during sit-to-stand. Applying a new method, the lost marker positions are restored and the biomechanical evaluation of the sit-to-stand movement with a Smart Mobile Walker could be carried out. The accuracy of the marker position estimation is verified with normal sit-to-stand data from more than 30 clinical trials. Moreover, further research on improving the link segment and regression method is addressed.
由于反光标记受到遮挡，使用辅助设备对从坐姿到站姿任务进行运动捕捉分析很难实现。先前开发的机器人系统“智能移动助行器”被用作辅助设备，以对从坐姿到站姿任务进行运动捕捉分析。在整个过程中，除了髋部标记外，所有下肢标记均不可见。采用连杆-节段和回归方法来估计从坐姿到站姿过程中的标记位置。应用一种新方法恢复了丢失的标记位置，并能够对使用智能移动助行器的从坐姿到站姿运动进行生物力学评估。标记位置估计的准确性通过30多项临床试验的正常从坐姿到站姿数据得到验证。此外，还讨论了对改进连杆-节段和回归方法的进一步研究。
