Quantitative Gait Assessment With Feature-Rich Diversity Using Two IMU Sensors

Quantitative Gait Assessment With Feature-Rich Diversity Using Two IMU Sensors
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DOI:
10.1109/tmrb.2020.3021132
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发表时间:
2020-11-01
期刊:
IEEE TRANSACTIONS ON MEDICAL ROBOTICS AND BIONICS
影响因子:
--
通讯作者:
Hayashibe, Mitsuhiro
Hayashibe, Mitsuhiro
中科院分区:
其他
文献类型:
--
作者:
Hutabarat, Yonatan;Owaki, Dai;Hayashibe, Mitsuhiro

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步态分析在医学应用中的重要性,例如在康复方面,已经被广泛研究。与黄金标准系统(即运动捕捉)相比,可穿戴传感器因其在灵活的环境中使用的便利性而广受欢迎,同时提供了准确性和可靠性。在这项研究中,我们提出了一种只使用两个惯性测量单元(IMU)传感器,同时提取最大数量特征的步态定量评估框架。传感器数量的减少对步态评估的性能有负面影响。然而,通过与运动捕获设置和以前的研究进行比较,我们验证了我们所提出的框架在为步态评估提供具有丰富特征多样性的紧凑传感系统方面的潜力和局限性。结果表明,时差为4.22+/-15.48ms(平均值+/-S.D.)和-8.31+/-21.02毫秒(平均值+/-S.D.)分别在最初的接触和脚尖离开项目中。此外,就空间特征而言,步长和脚跟垂直位移分别被高估了7.72 cm和2.22 cm。我们成功地从位于足部的两个IMU中提取了17个步态特征。我们还证明了对称性指数特征可以区分正常健康受试者和有近期下肢损伤病史的受试者,这对临床研究具有重要意义。
The importance of gait analysis in medical applications, such as in rehabilitation, has been widely studied. Wearable sensors have gained popularity owing to their convenience of use in a flexible environment, while providing accuracy and reliability, in comparison with the gold standard system, i.e., motion capture. In this study, we proposed a framework for quantitative gait assessment using only two inertial measurement unit (IMU) sensors, while extracting maximum number of features. Decreasing the number of sensors negatively affects the performance of gait assessment. However, through comparison with a motion capture setup and previous studies, we verified the potential and limitations of our proposed framework toward providing a compact sensing system with feature-rich diversity for gait assessment. The results revealed that the temporal differences were 4.22 +/- 15.48 ms (mean +/- S.D.) and -8.31 +/- 21.02 ms (mean +/- S.D.) in the initial contact and toe-off events, respectively. Additionally, with respect to the spatial features, the stride length and heel vertical displacement were overestimated by an average of 7.72 cm and 2.22 cm, respectively. We successfully extracted 17 gait features from two IMUs located on the foot. We have also demonstrated that symmetry index feature can distinguish normal healthy subjects and subject with recent history of lower-limb injury, which is important for clinical research.