Yorozu Ayanori, Nishiguchi Shu, Yamada Minoru, Aoyama Tomoki, Moriguchi Toshiki, Takahashi Masaki
School of Science for Open and Environmental Systems, Graduate School of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan.
Department of Physical Therapy, Human Health Sciences, Graduate School of Medicine, Kyoto University, 53 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.
Sensors (Basel). 2015 May 13;15(5):11151-68. doi: 10.3390/s150511151.
For the prevention of falling in the elderly, gait training has been proposed using tasks such as the multi-target stepping task (MTST), in which participants step on assigned colored targets. This study presents a gait measurement system using a laser range sensor for the MTST to evaluate the risk of falling. The system tracks both legs and measures general walking parameters such as stride length and walking speed. Additionally, it judges whether the participant steps on the assigned colored targets and detects cross steps to evaluate cognitive function. However, situations in which one leg is hidden from the sensor or the legs are close occur and are likely to lead to losing track of the legs or false tracking. To solve these problems, we propose a novel leg detection method with five observed leg patterns and global nearest neighbor-based data association with a variable validation region based on the state of each leg. In addition, methods to judge target steps and detect cross steps based on leg trajectory are proposed. From the experimental results with the elderly, it is confirmed that the proposed system can improve leg-tracking performance, judge target steps and detect cross steps with high accuracy.
为预防老年人跌倒，已提出使用多目标跨步任务（MTST）等任务进行步态训练，即参与者踩在指定的彩色目标上。本研究提出一种用于MTST的步态测量系统，该系统使用激光测距传感器来评估跌倒风险。该系统跟踪双腿并测量步长和步行速度等一般行走参数。此外，它判断参与者是否踩在指定的彩色目标上，并检测交叉步以评估认知功能。然而，存在一条腿被传感器遮挡或双腿靠近的情况，这可能会导致腿部跟踪丢失或错误跟踪。为了解决这些问题，我们提出了一种新颖的腿部检测方法，该方法具有五种观察到的腿部模式，并基于每条腿的状态，采用基于全局最近邻的数据关联和可变验证区域。此外，还提出了基于腿部轨迹判断目标步和检测交叉步的方法。通过对老年人的实验结果证实，所提出的系统可以提高腿部跟踪性能，高精度地判断目标步和检测交叉步。
