Department of Physiological Genomics, Institute of Physiology, University of Munich, Pettenkoferstr. 12, 80336 Munich, Germany; E-Mails:
Sensors (Basel). 2009;9(8):6330-45. doi: 10.3390/s90806330. Epub 2009 Aug 12.
This study describes a technique for measuring human grip forces exerted on a cylindrical object via a sensor array. Standardised resistor-based pressure sensor arrays for industrial and medical applications have been available for some time. We used a special 20 mm diameter grip rod that subjects could either move actively with their fingers in the horizontal direction or exert reactive forces against opposing forces generated in the rod by a linear motor. The sensor array film was attached to the rod by adhesive tape and covered approximately 45 cm(2) of the rod surface. The sensor density was 4/cm(2) with each sensor having a force resolution of 0.1 N. A scan across all sensors resulted in a corresponding frame containing force values at a frame repetition rate of 150/s. The force value of a given sensor was interpreted as a pixel value resulting in a false-colour image. Based on remote sensed image analysis an algorithm was developed to distinguish significant force-representing pixels from those affected by noise. This allowed tracking of the position of identified fingers in subsequent frames such that spatio-temporal grip force profiles for individual fingers could be derived. Moreover, the algorithm allowed simultaneous measurement of forces exerted without any constraints on the number of fingers or on the position of the fingers. The system is thus well suited for basic and clinical research in human physiology as well as for studies in psychophysics.
本研究描述了一种通过传感器阵列测量人施加在圆柱形物体上的握力的技术。用于工业和医疗应用的标准化基于电阻的压力传感器阵列已经存在了一段时间。我们使用了一种特殊的 20 毫米直径的握力棒,受试者可以用手指在水平方向主动移动,也可以对抗线性电机在棒上产生的反向力施加反作用力。传感器阵列薄膜通过胶带粘贴在棒上,覆盖棒表面约 45 平方厘米。传感器密度为 4/cm(2),每个传感器的力分辨率为 0.1 N。对所有传感器进行扫描会产生一个相应的帧,其中包含以 150/s 的帧重复率的力值。给定传感器的力值被解释为一个像素值,从而产生一个假彩色图像。基于遥感图像分析,开发了一种算法来区分代表力的有效像素和受噪声影响的像素。这允许在后续帧中跟踪已识别手指的位置,从而可以得出各个手指的时空握力分布。此外,该算法允许在不限制手指数量或位置的情况下同时测量施加的力。因此,该系统非常适合人类生理学的基础和临床研究,以及心理物理学研究。