神经退行性疾病的诊断具有精细的Lempel-Ziv复杂性
Huan Zhao1, Junxiao Xie1, Yangquan Chen2
1Key Laboratory of Education Ministry for Modern Design and Rotor Bearing System, Xi'an Jiaotong University, 28 Xianning West Road, 710049 Xi'an, China.
Cognitive neurodynamics
|June 3, 2024
概括
调查步态差异对于诊断神经退行性疾病,如帕金森病至关重要. 精细的Lempel-Ziv复杂性与基本步态特征相结合,可以提高诊断准确度.
科学领域:
- 生物医学工程 生物医学工程
- 神经学 神经学
- 数据科学数据科学数据科学
背景情况:
- 步态分析对于诊断神经退行性疾病至关重要.
- 人类的步态很复杂,受到各种因素的影响,可能会掩盖疾病特异性的差异.
- 在帕金森病,肌缩侧面硬化症和亨廷顿病中区分行走模式是具有挑战性的.
研究的目的:
- 为了确定神经退行性疾病之间独特的步态差异.
- 在步态分析中评估精细的Lempel-Ziv复杂性的有效性.
- 通过步态特征分析,提高诊断神经退行性疾病的准确性.
主要方法:
- 从垂直地面反应力和时间间隔中提取各种步态特征.
- 应用精细的Lempel-Ziv复杂性,考虑基于中位数和四分位数的信号分布.
- 使用小提琴情节和克鲁斯卡尔-瓦利斯测试对基本,非线性动态和精细的伦佩尔-齐夫复杂性特征进行统计比较.
主要成果:
- 对比分析显示了神经退行性疾病的明显步态差异,使用基本和非线性动态特征.
- 精制的Lempel-Ziv复杂性证明了诊断准确性的强有力的提高.
- 随机森林分类结果证实,当将精细的Lempel-Ziv复杂性与基本特征相结合时,诊断能力得到了提高.
结论:
- 步行分析,结合精细的Lempel-Ziv复杂性,可以有效地区分神经退行性疾病.
- 拟议的方法为改善神经退行性疾病的临床诊断提供了一个有希望的方法.
- 精制的Lempel-Ziv复杂性是提高神经退行性疾病研究的诊断准确性的宝贵工具.
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