Unsupervised Learning and Adaptive Classification of Neuromorphic Tactile Encoding of Textures
Unsupervised Learning and Adaptive Classification of Neuromorphic Tactile Encoding of Textures
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DOI：
10.1109/biocas.2018.8584702
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发表时间：
2018-10
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通讯作者：
Mark M. Iskarous;Harrison H. Nguyen;Luke E. Osborn;Joseph L. Betthauser;N. Thakor
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文献类型：
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作者：
Mark M. Iskarous;Harrison H. Nguyen;Luke E. Osborn;Joseph L. Betthauser;N. Thakor
在这项工作中，我们研究了分类的纹理神经形态触觉编码和无监督学习方法。此外，我们开发了一种自适应分类算法来检测和表征新的纹理数据的存在。多层触觉传感器对纹理的神经形态触觉编码是基于人无毛皮肤机械感受器的物理结构和传入锋电位信号。我们探索了不同的神经形态尖峰模式指标和降维技术，以最大限度地提高分类精度，同时提高计算效率。使用由3个纹理组成的数据集，我们表明，神经形态触觉编码数据的无监督学习具有较高的分类准确率（平均值= 86.46%，标准差=5。44%）。此外，自适应分类算法成功地确定了训练数据集中有3个底层纹理。在这项工作中，触觉信息被转换成神经形态尖峰活动，可以用作刺激模式，以引起假肢用户的纹理感觉。此外，我们提供了识别新的纹理自适应的基础，可用于主动修改刺激模式，以提高用户的纹理歧视。
In this work, we investigated the classification of texture by neuromorphic tactile encoding and an unsupervised learning method. Additionally, we developed an adaptive classification algorithm to detect and characterize the presence of new texture data. The neuromorphic tactile encoding of textures from a multilayer tactile sensor was based on the physical structure and afferent spike signaling of human glabrous skin mechanoreceptors. We explored different neuromorphic spike pattern metrics and dimensionality reduction techniques in order to maximize classification accuracy while improving computational efficiency. Using a dataset composed of 3 textures, we showed that unsupervised learning of the neuromorphic tactile encoding data had high classification accuracy (mean=86.46%, sd=5. 44%). Moreover, the adaptive classification algorithm was successful at determining that there were 3 underlying textures in the training dataset. In this work, tactile information is transformed into neuromorphic spiking activity that can be used as a stimulation pattern to elicit texture sensation for prosthesis users. Furthermore, we provide the basis for identifying new textures adaptively which can be used to actively modify stimulation patterns to improve texture discrimination for the user.