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Inertial Sensors to Assess Gait Quality in Patients with Neurological Disorders: A Systematic Review of Technical and Analytical Challenges

机译:惯性传感器评估神经系统疾病患者的步态质量:对技术和分析挑战的系统评价

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摘要

Gait disorders are major causes of falls in patients with neurological diseases. Understanding these disorders allows prevention and better insights into underlying diseases. InertiaLocoGraphy (ILG) –the quantification of gait by using inertial measurement units (IMUs) –shows great potential to address this public health challenge, but protocols vary widely and normative values of gait parameters are still unavailable. This systematic review critically compares ILG protocols, questions features extracted from inertial signals and proposes a semeiological analysis of clinimetric characteristics for use in neurological clinical routine. For this systematic review, PubMed, Cochrane and EMBASE were searched for articles assessing gait quality by using IMUs that were published from January 1, 2014 to August 31, 2016. ILG was used to assess gait in a wide range of neurological disorders – including Parkinson disease, mild cognitive impairment, Alzheimer disease, cerebral palsy, and cerebellar atrophy – as well as in the faller or frail older population and in people presenting rheumatological pathologies. However, results have not yet been driving changes in clinical practice. One reason could be that studies mainly aimed at comparing pathological gait to healthy gait, but there is stronger need for semiological descriptions of gait perturbation, severity or prognostic assessment. Furthermore, protocols used to assess gait using IMUs are too many. Likely, outcomes are highly heterogeneous and difficult to compare across large panels of studies. Therefore, homogenization is needed to foster the use of ILG to assess gait quality in neurological routine practice. The pros and cons of each protocol are emphasized so that a compromise can be reached. As well, analysis of seven complementary clinical criteria (springiness, sturdiness, smoothness, steadiness, stability, symmetry, synchronization) is advocated.
机译:步态障碍是神经系统疾病患者跌倒的主要原因。了解这些疾病可以预防并更好地了解潜在疾病。通过使用惯性测量单位(IMU)对步态进行量化的惯性运动描记法(ILG)显示出解决这一公共卫生挑战的巨大潜力,但是协议变化很大,步态参数的规范值仍然不可用。这项系统的审查批判性地比较了ILG协议,对从惯性信号中提取的特征提出质疑,并提出了用于神经系统临床常规的临床特征的符号学分析。在本系统评价中,检索了PubMed,Cochrane和EMBASE,以使用2014年1月1日至2016年8月31日出版的IMU评估步态质量的文章。ILG用于评估多种神经系统疾病的步态,包括帕金森病疾病,轻度认知障碍,阿尔茨海默氏病,脑瘫和小脑萎缩-以及下降的或脆弱的老年人群以及风湿病患者。但是,结果尚未推动临床实践的变化。原因之一可能是研究主要旨在比较病理性步态与健康的步态,但对步态摄动,严重性或预后评估的符号学描述更加需要。此外,用于使用IMU评估步态的协议太多。结果可能是高度异类的,并且很难在大批研究中进行比较。因此,需要同质化以促进在神经常规实践中使用ILG评估步态质量。强调每种协议的优缺点,以便达成折衷方案。同样,提倡分析七个互补的临床标准(弹性,坚固性,光滑度,稳定性,稳定性,对称性,同步性)。

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