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使用动作捕捉技术跟踪坐在轮椅上的人的全身质心。

Tracking the whole-body centre of mass of humans seated in a wheelchair using motion capture.

作者信息

Chénier Félix, Marquis Etienne, Fleury-Rousseau Maude

机构信息

Mobility and Adaptive Sports Research Lab, Department of Physical Activity Science, Université du Québec à Montréal (UQAM), Montreal, Canada; Centre for Interdisciplinary Research in Rehabilitation of Greater Montreal (CRIR), Montreal, Canada.

Mobility and Adaptive Sports Research Lab, Department of Physical Activity Science, Université du Québec à Montréal (UQAM), Montreal, Canada; Centre for Interdisciplinary Research in Rehabilitation of Greater Montreal (CRIR), Montreal, Canada.

出版信息

J Biomech. 2023 Jul;156:111675. doi: 10.1016/j.jbiomech.2023.111675. Epub 2023 Jun 9.

Abstract

Estimating the position of the whole-body centre of mass (CoM) based on skin markers and anthropometric tables requires tracking the pelvis and lower body, which is impossible for wheelchair users due to occlusion. In this work, we present a method to track the user's whole-body CoM using visible markers affixed to the user and wheelchair where the user remains seated in their wheelchair, by expressing the pelvis and lower body segments in wheelchair coordinates. The accuracy of this method was evaluated on the anterior-posterior (AP) and medial-lateral (ML) axes by comparing the projected CoM to the centre of pressure measured by four force plates, for 11 able-bodied participants adopting 9 static postures that include extreme reaching postures. The estimation accuracy was within 33 mm (AP) and 9 mm (ML), with a precision within 23 mm (AP) and 12 mm (ML). Tracking the whole-body CoM during wheelchair propulsion will allow researchers to better understand the dynamics of propulsion, which may help devise new approaches to increase the energy transfer from the arms to the ground and reduce the risks of developing musculoskeletal disorders.

摘要

基于皮肤标记点和人体测量表来估计全身质心(CoM)的位置,需要追踪骨盆和下半身,但由于遮挡问题,这对于轮椅使用者来说是不可能的。在这项工作中,我们提出了一种方法,通过在轮椅坐标系中表示骨盆和下半身节段,利用贴在使用者和轮椅上的可见标记点来追踪坐在轮椅上的使用者的全身质心。对于11名采用9种静态姿势(包括极限伸展姿势)的健全参与者,通过将预测的质心与四个测力板测量的压力中心进行比较,在前后(AP)轴和内外(ML)轴上评估了该方法的准确性。估计精度在33毫米(AP)和9毫米(ML)以内,精度在23毫米(AP)和12毫米(ML)以内。在轮椅推进过程中追踪全身质心将使研究人员能够更好地理解推进动力学,这可能有助于设计新的方法来增加从手臂到地面的能量传递,并降低发展肌肉骨骼疾病的风险。

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