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arXiv · 1912.08914

On the Metrics and Adaptation Methods for Domain Divergences of sEMG-based Gesture Recognition

István Ketykó·Ferenc Kovács
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Abstract

We propose a new metric to measure domain divergence and a new domain adaptation method for time-series classification. The metric belongs to the class of probability distributions-based metrics, is transductive, and does not assume the presence of source data samples. The 2-stage method utilizes an improved autoregressive, RNN-based architecture with deep/non-linear transformation. We assess our metric and the performance of our model in the context of sEMG/EMG-based gesture recognition under inter-session and inter-subject domain shifts.

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István Ketykó, Ferenc Kovács. 2019-12-18. On the Metrics and Adaptation Methods for Domain Divergences of sEMG-based Gesture Recognition. https://arxiv.org/abs/1912.08914

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