Numerical Analysis of Body Sway for Evaluation of 3D Sickness
Numerical Analysis of Body Sway for Evaluation of 3D Sickness
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DOI：
10.1109/iccse49874.2020.9201640
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发表时间：
2020-08
期刊：
影响因子：
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通讯作者：
Kohki Nakane;Rentaro Ono;Shota Yamamoto;Masumi Takada;Fumiya Kinoshita;A. Sugiura;Y. Matsuura;Kazuhiro Fujikake;H. Takada
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文献类型：
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作者：
Kohki Nakane;Rentaro Ono;Shota Yamamoto;Masumi Takada;Fumiya Kinoshita;A. Sugiura;Y. Matsuura;Kazuhiro Fujikake;H. Takada
根据非线性分析，我们将该人工智能系统应用于稳定图的数值模拟，稳定图的随机性明显大于其他生物信号的随机性。我们利用生成对抗网络（GANs）成功地发现了老年人身体摇摆的数学模型。试图可视化GAN中鉴别器层的内部状态，我们可以讨论人工智能如何捕捉在3D疾病期间记录的稳定图中的模式特征。特别是在三维疾病期间测量的稳定图中，可以提取尖峰模式，作为鉴别器输出的高贡献。
We have applied this artificial intelligence (AI) system to numerical simulations of the stabilogram whose randomness is remarkably greater than that of the other bio-signal in accordance with the nonlinear analysis. We have succeeded in findings of the mathematical models of the body sway in the elderly with use of the Generative Adversarial Networks (GANs). Trying to visualize internal state of the discriminator layer in our GAN, we can discuss how the AI captures the feature of patterns in the stabilograms recorded during the 3D sickness. Especially in the stabilograms measured during the 3D sickness, cusp patterns could be extracted as a high contribution to the output of the discriminator.