Estimation of Gait Parameters From Trunk Movement Measured by Doppler Radar
Estimation of Gait Parameters From Trunk Movement Measured by Doppler Radar
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DOI：
10.1109/jerm.2022.3198814
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发表时间：
2022-08-23
影响因子：
3.2
通讯作者：
Fujimoto, Masahiro
中科院分区：
文献类型：
--
作者：
Saho, Kenshi;Shioiri, Keitaro;Fujimoto, Masahiro
本研究提出了一种利用与躯干运动相对应的单基地连续波多普勒雷达数据来估计生物力学步态参数的新方法；与基于腿部运动的传统方法相比，躯干运动的使用导致稳定的步态参数估计，因为躯干回波的接收功率比腿部的接收功率更大且更稳定。所提出的步态参数估计方法采用从雷达频谱图中提取的躯干加速度。通过与参考运动捕捉数据进行比较，评估了使用所提出的方法估计的步态参数（例如步长、摆动时间和站立时间）的准确性。我们通过实验证明，所提出的基于躯干的方法估计步态参数的精度与传统的基于腿部的方法相似。此外，所提出的基于躯干的方法能够估计摆动和站立时间，而基于腿部的方法由于脚踝回波的不稳定而无法估计它们。此外，躯干和脚趾数据的组合方法在摆动和站立时间的估计方面取得了更好的准确性。这项研究首次利用雷达使用躯干运动（而非腿部运动）数据进行时间步态参数估计，并证明了其在临床和日常步态评估中的现实情况下的实用性，以掌握个人的健康状况，例如未来跌倒的风险和认知障碍。
This study proposes a novel method to estimate biomechanical gait parameters using the monostatic continuous wave Doppler radar data corresponding to trunk movement; the use of trunk movement leads to stable gait parameter estimations when compared to the conventional method which is based on leg movements because the received powers of the trunk echoes are larger and more stable than those of the legs. The proposed gait parameter estimation method employs trunk accelerations extracted from radar spectrograms. The accuracies of the gait parameters, such as the step length, swing time, and stance time, estimated using the proposed methods were evaluated by comparing them with the reference motion capture data. We experimentally demonstrated that the proposed trunk-based method estimated gait parameters with accuracy similar to that of the conventional leg-based method. Additionally, the proposed trunk-based method was able to estimate the swing and stance times, whereas the leg-based method failed to estimate them owing to instability of the ankle echoes. Furthermore, the combined method of the trunk and toe data achieved better accuracy in the estimation of swing and stance times. This study is the first to use data on trunk movements (not leg movements) for temporal gait parameter estimation using radar and demonstrated its practicality for realistic situations in clinical and daily gait assessment to grasp the health status of individuals such as risks of future falls and cognitive impairments.