Department of Sport and Health Science, Technische Universität München, Connollystraße 32, 80809 Munich, Germany.
Exp Brain Res. 2011 Jul;212(1):19-31. doi: 10.1007/s00221-011-2695-y. Epub 2011 May 4.
The ability to predict and anticipate the mechanical demands of the environment promotes smooth and skillful motor actions. Thus, the finger forces produced to grasp and lift an object are scaled to the physical properties such as weight. While grip force scaling is well established for neutral objects, only few studies analyzed objects known from daily routine and none studied grip forces. In the present study, eleven healthy subjects each lifted twelve objects of everyday life that encompassed a wide range of weights. The finger pads were covered with force sensors that enabled the measurement of grip force. A scale registered load forces. In a control experiment, the objects were wrapped into paper to prevent recognition by the subjects. Data from the first lift of each object confirmed that object weight was anticipated by adequately scaled forces. The maximum grip force rate during the force increase phase emerged as the most reliable measure to verify that weight was actually predicted and to characterize the precision of this prediction, while other force measures were scaled to object weight also when object identity was not known. Variability and linearity of the grip force-weight relationship improved for time points reached after liftoff, suggesting that sensory information refined the force adjustment. The same mechanism seemed to be involved with unrecognizable objects, though a lower precision was reached. Repeated lifting of the same object within a second and third presentation block did not improve the precision of the grip force scaling. Either practice was too variable or the motor system does not prioritize the optimization of the internal representation when objects are highly familiar.
预测和预估环境力学需求的能力可以促进运动的流畅和熟练性。因此，为了抓取和提起一个物体而产生的手指力与物体的物理特性（如重量）成比例。虽然对于中性物体的握力缩放已经得到很好的证实，但只有少数研究分析了日常生活中的物体，没有研究握力。在本研究中，11 名健康受试者每人举起 12 件日常生活用品，涵盖了广泛的重量范围。手指垫上覆盖着力传感器，能够测量握力。一个秤记录负载力。在对照实验中，物体被包裹在纸中，以防止被受试者识别。每个物体第一次提起的数据证实，物体的重量是通过适当的力缩放来预测的。在力增加阶段，最大握力率是验证实际预测和描述预测精度的最可靠指标，而当不知道物体身份时，其他力测量也与物体重量成比例。提起后，握力-重量关系的可变性和线性得到了改善，这表明感官信息优化了力的调整。相同的机制似乎也适用于无法识别的物体，尽管精度较低。在第二次和第三次演示块中重复举起同一个物体并没有提高握力缩放的精度。要么是练习太可变，要么是当物体非常熟悉时，运动系统不会优先优化内部表示。
