Hodder Joanne N, La Delfa Nicholas J, Potvin Jim R
Department of Kinesiology, McMaster University, Hamilton, ON, Canada; School of Applied Health Sciences, Sheridan College, Brampton, ON, Canada.
Department of Kinesiology, McMaster University, Hamilton, ON, Canada.
J Electromyogr Kinesiol. 2016 Aug;29:50-4. doi: 10.1016/j.jelekin.2015.05.002. Epub 2015 Jun 11.
To predict shoulder strength, most current ergonomics software assume independence of the strengths about each of the orthopedic axes. Using this independent axis approach (IAA), the shoulder can be predicted to have strengths as high as the resultant of the maximum moment about any two or three axes. We propose that shoulder strength is not independent between axes, and propose an approach that calculates the weighted average (WAA) between the strengths of the axes involved in the demand. Fifteen female participants performed maximum isometric shoulder exertions with their right arm placed in a rigid adjustable brace affixed to a tri-axial load cell. Maximum exertions were performed in 24 directions, including four primary directions, horizontal flexion-extension, abduction-adduction, and at 15° increments in between those axes. Moments were computed and comparisons made between the experimentally collected strengths and those predicted by the IAA and WAA methods. The IAA over-predicted strength in 14 of 20 non-primary exertions directions, while the WAA underpredicted strength in only 2 of these directions. Therefore, it is not valid to assume that shoulder axes are independent when predicting shoulder strengths between two orthopedic axes, and the WAA is an improvement over current methods for the posture tested.
为预测肩部力量，当前大多数人体工程学软件假定各个骨科轴向上的力量相互独立。采用这种独立轴方法（IAA），预计肩部力量可达任意两个或三个轴向上最大力矩合力的水平。我们认为，肩部各轴向上的力量并非相互独立，并提出一种计算需求中涉及的各轴力量加权平均值（WAA）的方法。15名女性参与者将右臂置于固定在三轴测力传感器上的刚性可调支架中，进行最大等长肩部用力。在24个方向上进行最大用力，包括四个主要方向，即水平屈伸、外展内收，以及在这些轴之间以15°增量进行。计算力矩，并对实验收集的力量与IAA和WAA方法预测的力量进行比较。在20个非主要用力方向中的14个方向上，IAA高估了力量，而在这些方向中，WAA仅在2个方向上低估了力量。因此，在预测两个骨科轴之间的肩部力量时，假定肩部轴相互独立是无效的，对于所测试的姿势，WAA是对当前方法的一种改进。
