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独立分量分析(Independent component analysis,ICA)是一种有效的空域滤波方法,在脑-机接口领域具有很高的研究价值和应用潜力。论文围绕基于滑动窗的自适应ICA算法及其在脑-机接口中的应用开展研究,提出了一种基于ICA的信号包络在线检测新方法,并将该方法应用于运动想象诱发的mu节律包络检测,建立了相应的左右手运动想象分类识别算法。在此基础上,进行了离线和在线运动想象脑-机接口实验,取得了较好的识别效果。
Independent component analysis (ICA) is an effective spatial filtering method, which has high research value and potential application in the brain-computer interface. This dissertation focuses on the research of adaptive ICA algorithm based on sliding window and its application in brain-computer interface, proposes a new ICA-based online detection method of signal envelope, and applies this method to mu rhythm induced by motion imagination Envelope detection, the establishment of the corresponding left and right hand motion imaging classification and recognition algorithm. On this basis, experiments on brain-computer interface were carried out for offline and online sports, and better recognition results were achieved.