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Updated: Jun 14, 2025

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task
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探索联合角度和sEMG信号对联合扭矩预测准确性的贡献,使用基于LSTM的深度学习技术

Engin Kaya1, Hande Argunsah1

  • 1Faculty of Engineering and Natural Sciences, Department of Biomedical Engineering, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey.

Computer methods in biomechanics and biomedical engineering
|September 5, 2024
PubMed
概括

机器学习模型使用关节角度和表面电肌图 (sEMG) 信号准确预测下肢关节扭矩. 结果表明单个输入类型可能足以预测联合扭矩,优化生物力学分析.

关键词:
机器学习 机器学习计算步态分析计算步态分析长期短期记忆 神经网络 神经网络表面电心图 (电心图) 是一种表面电心图.扭矩预测 扭矩预测

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