Extraction of Nystagmus Patterns from Eye-Tracker Data with Convolutional Sparse Coding
Centre Borelli（博雷利中心）；CNRS（法国国家科学研究中心）；ENS Paris Saclay（巴黎-萨克雷高等师范学院）；Université de Paris（巴黎大学）；SSA（法国武装部队卫生服务局）；Hôpital Necker-Enfants Malades（内克尔-患病儿童医院）；AP-HP（巴黎公立医院集团）；Université Sorbonne Paris Nord（索邦巴黎北大学）；University Paris-Saclay（巴黎-萨克雷大学）；Inria（法国国家信息与自动化研究所）；CEA（法国原子能和替代能源委员会）
英文摘要：
The analysis of the Nystagmus waveforms from eye-tracking records is crucial for the clinicial interpretation of this pathological movement. A major issue to automatize this analysis is the presence of natural eye movements and eye blink artefacts that are mixed with the signal of interest. We propose a method based on Convolutional Dictionary Learning that is able to automaticcaly highlight the Nystagmus waveforms, separating the natural motion from the pathological movements. We show on simulated signals that our method can indeed improve the pattern recovery rate and provide clinical examples to illustrate how this algorithm performs.
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