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脑卒中偏瘫患者在跨越障碍物时所呈现出的步态时空特征，可作为评价其跌倒风险的重要参考依据。本研究比较有无跌倒史的脑卒中偏瘫患者在分别以患侧腿和健侧腿作为先行腿越障过程中的步态时空特征，确定评价患者跌倒风险的指标，并建立相应的回归模型。招募33名康复出院的患者，根据既往6个月是否有跌倒史分为跌倒组(n=17)和非跌倒组(n=16)。采用红外动作捕捉系统采集患者分别以患侧腿和健侧腿作为先行腿跨越4 cm高障碍物时的体表标志点坐标，并通过计算获得步态时空参数。通过独立样本t检验比较两组的步态时空参数，并使用Logistic回归分析确定评价跌倒风险的指标。最终纳入跌倒风险评估模型的参数为患侧先行时的障碍物-先行腿足跟距离以及健侧先行时的障碍后步宽(P<0.05),该模型的总体评估正确率为69.7%。因此，脑卒中偏瘫患者越障过程中的步态时空参数能够有效评估跌倒风险。本研究构建的跌倒风险评估模型，可为临床医生筛查跌倒高风险患者及制定预防和治疗方案提供重要依据。
Abstract：The gait spatio-temporal characteristics exhibited by hemiplegic stroke patients during obstacle crossing can serve as important references for evaluating their fall risk. In this study, we compared the gait spatial-temporal characteristics of hemiplegic stroke patients with and without a history of falls during obstacle crossing, with both the affected limbs and unaffected limbs used as the leading limb. We aimed to determine the indicators for evaluating fall risk and establish a regression model for this purpose. A total of 33 patients who had been discharged from rehabilitation were included in the study. These patients were categorized into the fall group(n=17) and the non-fall group(n=16) based on whether they had experienced a fall in the previous six months. A motion capture system was used to record the marker positions as the patients crossed a 4 cm high obstacle, with both the affected limbs and unaffected limbs serving as the leading limb, and gait spatio-temporal parameters were calculated and obtained. The parameters were compared between the two groups using an independent samples t-test, while Logistic regression analysis was used to determine the indicators for evaluating fall risk. Finally, the parameters included in the fall risk assessment model were the obstacle-heel distance of leading limb when the affected limb served as the leading limb and the post-obstacle step width when the unaffected limb served as the leading limb(P<0.05), and the overall accuracy of the model was 69.7%. Therefore, the gait spatio-temporal parameters during obstacle crossing in hemiplegic stroke patients can effectively assess fall risk. The fall risk assessment model developed in this study demonstrated excellent predictive performance, indicating its potential utility in clinical settings.
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基本信息:
DOI：10.13417/j.gab.044.000941
中图分类号:R743.3
引用信息:
[1]朱梓豪,金宗学,许峰,等.脑卒中偏瘫患者跨越障碍物步态时空特征与跌倒风险的关系[J].基因组学与应用生物学,2025,44(09):941-952.DOI:10.13417/j.gab.044.000941.
基金信息:
国家重点研发计划课题(2020YFC2007002); 中央高校基本科研业务费专项资金资助课题(2024TNJN008)共同资助
2025-02-07
2025-02-07
2025-02-07