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主要解剖平面中上身运动的自动区分。

Automatic distinction of upper body motions in the main anatomical planes.

作者信息

Consmüller Tobias, Rohlmann Antonius, Weinland Daniel, Schmidt Hendrik, Zippelius Timo, Duda Georg N, Taylor William R

机构信息

Epionics Medical GmbH, Beyerstrasse 1, 14469 Potsdam, Germany.

Julius Wolff Institute, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany.

出版信息

Med Eng Phys. 2014 Apr;36(4):516-21. doi: 10.1016/j.medengphy.2013.10.014. Epub 2013 Nov 11.

Abstract

The assessment of spinal mobility and function is gaining clinical importance for the diagnosis and monitoring of low back pain, but its measurement and evaluation remains difficult. As a critical step towards non-supervised assessment of spinal functional, the aim of this study was to assess the efficacy of symmetrical sensors fixed to the sides of the spinal column to distinguish between different upper body movements in the main anatomical planes. 429 healthy volunteers underwent a defined choreography including repeated upper body flexion, extension, lateral bending and axial rotation exercises. The movements were assessed using the Epionics SPINE sensor system. Two pattern recognition models were developed and applied to distinguish between the different movements in a frame-by-frame manner, as well as for whole motion sequences. On average, it was possible to differentiate between different upper body movements with a sensitivity of over 96% for both modelling approaches. The largest type II error was the incorrect identification of extension, possibly due to deviations from the reference standing posture during measurements and small changes in the lordotic angle during extension. The use of two sagittal sensors attached symmetrically to the back therefore seems to allow the distinction of upper body movements in a robust manner, and therefore opens perspectives for the unsupervised recognition of movements and functional activity over extended periods.

摘要

脊柱活动度和功能的评估对于腰痛的诊断和监测在临床上日益重要,但其测量和评估仍然困难。作为脊柱功能非监督评估的关键一步,本研究的目的是评估固定在脊柱两侧的对称传感器区分主要解剖平面中不同上身运动的功效。429名健康志愿者进行了一套规定动作,包括重复的上身前屈、后伸、侧屈和轴向旋转练习。使用Epionics SPINE传感器系统对这些动作进行评估。开发了两种模式识别模型,并逐帧以及对整个运动序列应用这些模型来区分不同的动作。平均而言,两种建模方法区分不同上身运动的灵敏度均超过96%。最大的II型错误是将后伸错误识别,这可能是由于测量期间与参考站立姿势存在偏差以及后伸期间脊柱前凸角度的微小变化所致。因此,在背部对称附着两个矢状面传感器似乎能够可靠地区分上身运动,从而为长时间无监督识别运动和功能活动开辟了前景。

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