Dataglove measurement of joint angles in sign language handshapes.
Dataglove measurement of joint angles in sign language handshapes.
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DOI：
10.1075/sll.15.1.03ecc
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发表时间：
2012
影响因子：
0.8
通讯作者：
Scheidt RA
中科院分区：
文献类型：
--
作者：
Eccarius P;Bour R;Scheidt RA
在手语研究中，我们对发音因素的了解很少，这些因素与形成音素边界或手形之间可接受的语音变化的数量（和发音性质）有关。迄今为止，还没有基于手势制作过程中关节角度的定量测量来全面分析手形。我们的工作的目的是开发一种方法来收集和可视化定量的手形数据，试图更好地了解如何在语音水平上产生手形。在这种追求中，我们试图量化的屈曲和外展角度的手指关节使用商业数据手套（CyberGlove; Immersion公司）。我们提出了用于将原始手套信号转换为关节角度的校准程序。然后，我们实施这些程序，并评估其准确预测关节角度的能力。最后，我们提供的例子，我们的记录技术可能会通知当前的研究问题。
In sign language research, we understand little about articulatory factors involved in shaping phonemic boundaries or the amount (and articulatory nature) of acceptable phonetic variation between handshapes. To date, there exists no comprehensive analysis of handshape based on the quantitative measurement of joint angles during sign production. The purpose of our work is to develop a methodology for collecting and visualizing quantitative handshape data in an attempt to better understand how handshapes are produced at a phonetic level. In this pursuit, we seek to quantify the flexion and abduction angles of the finger joints using a commercial data glove (CyberGlove; Immersion Inc.). We present calibration procedures used to convert raw glove signals into joint angles. We then implement those procedures and evaluate their ability to accurately predict joint angle. Finally, we provide examples of how our recording techniques might inform current research questions.