Zhang Ruisi, J Schwehr Trevor, J Abbott Jake
IEEE Trans Haptics. 2021 Apr-Jun;14(2):445-448. doi: 10.1109/TOH.2020.3043095. Epub 2021 Jun 17.
In our recent article, we found a general quadratic weighting function to predict how a six-dimensional (6D) vibrotactile stimulus rendered at the haptic interaction point (HIP) of a kinesthetic haptic interface, with the stylus held in a precision pen-hold grasp, is mapped to an equivalent one-dimensional (1D) stimulus that is normalized by the detection threshold. However, in that work we did not constrain the weighting function to be positive semidefinite, and as a result, the model will not generalize well to all future 6D inputs. In this addendum, we reconsider the original data set, incorporating the positive-semidefinite constraint. We find that as few as four independent parameters are required to describe the coupling, and the model has one fewer coupling term than originally proposed. We also describe the process of fitting a positive-semidefinite function to a new stylus at some specific excitation frequency.
在我们最近的文章中，我们发现了一个通用的二次加权函数，用于预测在运动触觉接口的触觉交互点（HIP）处呈现的六维（6D）振动触觉刺激如何被映射为一个等效的一维（1D）刺激，该刺激通过检测阈值进行了归一化，其中触控笔以精确的握笔法握持。然而，在那项工作中，我们没有将加权函数限制为半正定，结果，该模型不能很好地推广到所有未来的6D输入。在本附录中，我们重新考虑原始数据集，并纳入半正定约束。我们发现，描述这种耦合只需少至四个独立参数，并且该模型的耦合项比最初提出的少一个。我们还描述了在某个特定激励频率下将半正定函数拟合到新触控笔的过程。
