Validation of a Step Detection Algorithm during Straight Walking and Turning in Patients with Parkinson's Disease and Older Adults Using an Inertial Measurement Unit at the Lower Back.
Validation of a Step Detection Algorithm during Straight Walking and Turning in Patients with Parkinson's Disease and Older Adults Using an Inertial Measurement Unit at the Lower Back.
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DOI：
10.3389/fneur.2017.00457
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发表时间：
2017
影响因子：
3.4
通讯作者：
Maetzler W
中科院分区：
文献类型：
--
作者：
Pham MH;Elshehabi M;Haertner L;Del Din S;Srulijes K;Heger T;Synofzik M;Hobert MA;Faber GS;Hansen C;Salkovic D;Ferreira JJ;Berg D;Sanchez-Ferro Á;van Dieën JH;Becker C;Rochester L;Schmidt G;Maetzler W
位于不同身体位置的惯性测量单元(IMU)即使在不受约束的条件下也可以进行详细的步态分析。从医学角度来看，对弱势群体的评估具有特别重要的意义，特别是在日常生活环境中。步态分析算法需要彻底的验证，因为许多慢性病显示出特定的甚至独特的步态模式。因此，这项研究的目的是验证基于加速的步长检测算法在实验室和家庭环境中都适用于帕金森氏病(PD)患者和老年人。在这项前瞻性观察研究中，数据采集自佩戴在下背部的单一6自由度IMU(APDM)(3自由度加速度计和3自由度陀螺仪)。在跑步机上检测脚后跟撞击(HS)和脚趾脱落(TO)是通过光电系统(VICON)进行验证的(11名PD患者和12名老年人)。在家庭式环境中进行的第二项独立验证研究针对视频观察(20名PD患者和12名老年人)，包括转弯和非转弯过程中的步数，用先前发表的算法定义。提出了一种基于连续小波变换(CWT)的阶跃检测算法，该算法与光电系统具有很高的一致性。帕金森病患者/老年人HS检测准确率分别达到99/99%。TO也有类似的结果(99/100%)。在HS检测中，Bland-Altman图显示算法与光电系统的平均差为0.002 S[95%可信区间(CI)−0.09至0.10]。Bland-Altman图对TO检测的平均差值为0.00 S(95%CI−为0.12~0.12)。在家庭式评估中，检测转身过程中台阶发生的算法达到了90%(帕金森病患者)/90%(老年人)的敏感性、83/88%的特异性和88/89%的准确性。检测非转向期台阶的敏感性为91/91%，特异性为90/90%，准确性为91/91%。这种基于CWT的下背部台阶检测算法与帕金森病患者和老年人的光电系统高度一致。因此，这种方法和算法可以为未来在这些弱势群体中进行基于家庭的步态分析提供一个有价值的工具。
Inertial measurement units (IMUs) positioned on various body locations allow detailed gait analysis even under unconstrained conditions. From a medical perspective, the assessment of vulnerable populations is of particular relevance, especially in the daily-life environment. Gait analysis algorithms need thorough validation, as many chronic diseases show specific and even unique gait patterns. The aim of this study was therefore to validate an acceleration-based step detection algorithm for patients with Parkinson’s disease (PD) and older adults in both a lab-based and home-like environment. In this prospective observational study, data were captured from a single 6-degrees of freedom IMU (APDM) (3DOF accelerometer and 3DOF gyroscope) worn on the lower back. Detection of heel strike (HS) and toe off (TO) on a treadmill was validated against an optoelectronic system (Vicon) (11 PD patients and 12 older adults). A second independent validation study in the home-like environment was performed against video observation (20 PD patients and 12 older adults) and included step counting during turning and non-turning, defined with a previously published algorithm. A continuous wavelet transform (cwt)-based algorithm was developed for step detection with very high agreement with the optoelectronic system. HS detection in PD patients/older adults, respectively, reached 99/99% accuracy. Similar results were obtained for TO (99/100%). In HS detection, Bland–Altman plots showed a mean difference of 0.002 s [95% confidence interval (CI) −0.09 to 0.10] between the algorithm and the optoelectronic system. The Bland–Altman plot for TO detection showed mean differences of 0.00 s (95% CI −0.12 to 0.12). In the home-like assessment, the algorithm for detection of occurrence of steps during turning reached 90% (PD patients)/90% (older adults) sensitivity, 83/88% specificity, and 88/89% accuracy. The detection of steps during non-turning phases reached 91/91% sensitivity, 90/90% specificity, and 91/91% accuracy. This cwt-based algorithm for step detection measured at the lower back is in high agreement with the optoelectronic system in both PD patients and older adults. This approach and algorithm thus could provide a valuable tool for future research on home-based gait analysis in these vulnerable cohorts.
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影响因子：
5.1
作者：
Doi, Takehiko;Hirata, Soichiro;Ando, Hiroshi
通讯作者：
Ando, Hiroshi
影响因子：
2.4
作者：
Crenna, P.;Carpinella, I.;Ferrarin, M.
通讯作者：
Ferrarin, M.
影响因子：
1.3
作者：
Ostensjo, Sigrid;Oien, Ingvil;Fallang, Bjorg
通讯作者：
Fallang, Bjorg
影响因子：
2.4
作者：
Gonzalez, Rafael C.;Lopez, Antonio M.;Alvarez, Juan C.
通讯作者：
Alvarez, Juan C.
影响因子：
48
作者：
Henderson, Emily J.;Lord, Stephen R.;Ben-Shlomo, Y.
通讯作者：
Ben-Shlomo, Y.