通过ARX残余建模和内核双样本测试对行走一致性进行量化
IEEE transactions on bio-medical engineering
|September 18, 2023
概括
使用新的AutoRegressive模型和假设测试量化步态一致性,揭示了健康个体与多发性硬化症 (MS) 患者之间的差异. 这种方法突出了不同的条件如何影响步态分析.
科学领域:
- 生物力学 生物力学
- 神经学 神经学
- 医疗技术 医疗技术 医学技术
背景情况:
- 步态分析对于理解神经肌肉疾病至关重要.
- 量化步态一致性有助于区分自然变化与疾病进展或治疗效应.
- 需要客观的方法来准确评估步态的一致性.
研究的目的:
- 提出一种新的客观方法来评估步态的一致性.
- 量化健康个体和患有多发性硬化症 (MS) 的人的步态一致性.
- 评估不同评估条件对步态一致性的影响.
主要方法:
- 使用自动回归与异源输入 (ARX) 模型,使用惯性传感器加速度计数据从和下背部.
- 采用模型残留物作为步态一致性监测的关键特征.
- 应用最大平均差异 (MMD) 假设测试来比较剩余分布.
主要成果:
- 多发性硬化症 (MS) 患者表现出减少的步态一致性,即使在受控条件下.
- 在健康人群和多发性硬化患者中,在一周后重新进行测试时,观察到走路不一致.
- 该研究确定了不同评估条件对步态一致性的不利影响.
结论:
- 成功量化了健康人和MS个体的步态一致性.
- 这种新方法有效地突出了MS的步态变化.
- 不同的评估条件可以掩盖步态模式的一致性,影响后续评估.
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