PDF(Pubmed)
Abstract：
The aim of this study was to assess the ability of multiscale sample entropy (MSE), refined composite multiscale entropy (RCMSE), and complexity index (CI) to characterize gait complexity through trunk acceleration patterns in subjects with Parkinson\'s disease (swPD) and healthy subjects, regardless of age or gait speed. The trunk acceleration patterns of 51 swPD and 50 healthy subjects (HS) were acquired using a lumbar-mounted magneto-inertial measurement unit during their walking. MSE, RCMSE, and CI were calculated on 2000 data points, using scale factors (τ) 1-6. Differences between swPD and HS were calculated at each τ, and the area under the receiver operating characteristics, optimal cutoff points, post-test probabilities, and diagnostic odds ratios were calculated. MSE, RCMSE, and CIs showed to differentiate swPD from HS. MSE in the anteroposterior direction at τ4 and τ5, and MSE in the ML direction at τ4 showed to characterize the gait disorders of swPD with the best trade-off between positive and negative posttest probabilities and correlated with the motor disability, pelvic kinematics, and stance phase. Using a time series of 2000 data points, a scale factor of 4 or 5 in the MSE procedure can yield the best trade-off in terms of post-test probabilities when compared to other scale factors for detecting gait variability and complexity in swPD.
摘要：
本研究的目的是评估多尺度样本熵(MSE)的能力，精细复合多尺度熵(RCMSE)，和复杂性指数（CI）通过躯干加速度模式来表征帕金森病（swPD）受试者和健康受试者的步态复杂性，无论年龄或步态速度。在行走过程中，使用腰部安装的磁惯性测量单元获取了51个swPD和50个健康受试者（HS）的躯干加速度模式。MSE,RCMSE,和CI是根据2000个数据点计算的，使用比例因子(τ)1-6。在每个τ计算swPD和HS之间的差异，以及接收机工作特性下的区域，最佳截止点，后验概率，并计算诊断比值比。MSE,RCMSE,和CI显示可区分swPD和HS。在τ4和τ5的前后方向上的MSE和在τ4的ML方向上的MSE表明，swPD的步态障碍具有阳性和阴性测试后概率之间的最佳权衡，并与运动障碍相关，骨盆运动学,和立场阶段。使用2000个数据点的时间序列，与用于检测swPD中的步态变异性和复杂性的其他比例因子相比,MSE程序中的比例因子4或5可以在测试后概率方面产生最佳权衡。
