临床步态分析使用智能鞋垫在中风后偏瘫患者:初步研究。
Clinometric Gait Analysis Using Smart Insoles in Patients With Hemiplegia After Stroke: Pilot Study.
机构信息
School of Medicine, Pusan National University, Busan, Republic of Korea.
Department of Rehabilitation Medicine, School of Medicine, Pusan National University, Busan, Republic of Korea.
出版信息
JMIR Mhealth Uhealth. 2020 Sep 10;8(9):e22208. doi: 10.2196/22208.
BACKGROUND
For effective rehabilitation after stroke, it is essential to conduct an objective assessment of the patient's functional status. Several stroke severity scales have been used for this purpose, but such scales have various limitations.
OBJECTIVE
Gait analysis using smart insole technology can be applied continuously, objectively, and quantitatively, thereby overcoming the shortcomings of other assessment tools.
METHODS
To confirm the reliability of gait analysis using smart insole technology, normal healthy controls wore insoles in their shoes during the Timed Up and Go (TUG) test. The gait parameters were compared with the manually collected data. To determine the gait characteristics of patients with hemiplegia due to stroke, they were asked to wear insoles and take the TUG test; gait parameters were calculated and compared with those of control subjects. To investigate whether the gait analysis accurately reflected the patients' clinical condition, we analyzed the relationships of 22 gait parameters on 4 stroke severity scales.
RESULTS
The smart insole gait parameter data were similar to those calculated manually. Among the 18 gait parameters tested, 14 were significantly effective at distinguishing patients from healthy controls. The smart insole data revealed that the stance duration on both sides was longer in patients than controls, which has proven difficult to show using other methods. Furthermore, the sound side in patients showed a markedly longer stance duration. Regarding swing duration, that of the sound side was shorter in patients than controls, whereas that of the hemiplegic side was longer. We identified 10 significantly correlated gait parameters on the stroke severity scales. Notably, the difference in stance duration between the sound and hemiplegic sides was significantly correlated with the Fugl-Meyer Assessment (FMA) lower extremity score.
CONCLUSIONS
This study confirmed the feasibility and applicability of the smart insole as a device to assess the gait of patients with hemiplegia due to stroke. In addition, we demonstrated that the FMA score was significantly correlated with the smart insole data. Providing an environment where stroke patients can easily measure walking ability helps to maintain chronic functions as well as acute rehabilitation.
TRIAL REGISTRATION
UMIN Clinical Trials Registry UMIN000041646, https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000047538.
背景
为了实现脑卒中后的有效康复，对患者的功能状态进行客观评估至关重要。为此目的已经使用了几种脑卒中严重程度量表，但这些量表存在各种局限性。
目的
智能鞋垫技术的步态分析可连续、客观和定量地进行，从而克服了其他评估工具的缺点。
方法
为了确认智能鞋垫技术步态分析的可靠性，让正常健康对照者在进行计时起立行走（TUG）测试时穿鞋内垫。将步态参数与手动收集的数据进行比较。为了确定脑卒中偏瘫患者的步态特征，让他们穿上鞋垫并进行 TUG 测试；计算步态参数并与对照组进行比较。为了研究步态分析是否准确反映患者的临床状况，我们分析了 22 个步态参数与 4 个脑卒中严重程度量表的关系。
结果
智能鞋垫步态参数数据与手动计算的数据相似。在测试的 18 个步态参数中，有 14 个参数在区分患者与健康对照组方面非常有效。智能鞋垫数据显示，患者双侧的站立时间均长于对照组，这一点用其他方法很难体现。此外，患者的健侧站立时间明显较长。至于摆动时间，患者的健侧短于对照组，而患侧长于对照组。我们在脑卒中严重程度量表上确定了 10 个具有显著相关性的步态参数。值得注意的是，健侧和患侧之间的站立时间差异与 Fugl-Meyer 评估（FMA）下肢评分显著相关。
结论
本研究证实了智能鞋垫作为评估脑卒中偏瘫患者步态的设备的可行性和适用性。此外，我们证明了 FMA 评分与智能鞋垫数据显著相关。为脑卒中患者提供一个方便测量步行能力的环境，有助于维持慢性功能和急性康复。
试验注册
UMIN 临床研究注册 UMIN000041646，https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000047538。
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