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首页> 外文期刊>Journal of healthcare engineering. >An Interactive Care System Based on a Depth Image and EEG for Aged Patients with Dementia
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An Interactive Care System Based on a Depth Image and EEG for Aged Patients with Dementia

机译:基于痴呆患者的深度图像和脑电图的互动护理系统

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摘要

Due to the limitations of the body movement and functional decline of the aged with dementia, they can hardly make an efficient communication with nurses by language and gesture language like a normal person. In order to improve the efficiency in the healthcare communication, an intelligent interactive care system is proposed in this paper based on a multimodal deep neural network (DNN). The input vector of the DNN includes motion and mental features and was extracted from a depth image and electroencephalogram that were acquired by Kinect and OpenBCI, respectively. Experimental results show that the proposed algorithm simplified the process of the recognition and achieved 96.5% and 96.4%, respectively, for the shuffled dataset and 90.9% and 92.6%, respectively, for the continuous dataset in terms of accuracy and recall rate.
机译:由于身体运动的局限性和痴呆症老化的功能下降,他们几乎无法通过像普通人那样通过语言和手势语言与护士进行有效的沟通。 为了提高医疗通信的效率,基于多模式深神经网络(DNN),本文提出了一种智能互动护理系统。 DNN的输入向量包括运动和心理特征,并从深度图像和脑电图中提取,分别由Kinect和OpenBCI获取。 实验结果表明,该算法在准确度和召回率方面,该算法分别为识别过程分别为持续的数据集和96.5%和96.4%,分别为连续数据集的96.5%和92.6%。

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