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A multimodal approach to capture post-stroke temporal dynamics of recovery.
Journal of Neural Engineering ( IF 3.7 ) Pub Date : 2020-07-09 , DOI: 10.1088/1741-2552/ab9ada
Camilla Pierella 1 , Elvira Pirondini , Nawal Kinany , Martina Coscia , Christian Giang , Jenifer Miehlbradt , Cécile Magnin , Pierre Nicolo , Stefania Dalise , Giada Sgherri , Carmelo Chisari , Dimitri Van De Ville , Adrian Guggisberg , Silvestro Micera
Affiliation  

Objective. Several training programs have been developed in the past to restore motor functions after stroke. Their efficacy strongly relies on the possibility to assess individual levels of impairment and recovery rate. However, commonly used clinical scales rely mainly on subjective functional assessments and are not able to provide a complete description of patients’ neuro-biomechanical status. Therefore, current clinical tests should be integrated with specific physiological measurements, i.e. kinematic, muscular, and brain activities, to obtain a deep understanding of patients’ condition and of its evolution through time and rehabilitative intervention. Approach. We proposed a multivariate approach for motor control assessment that simultaneously measures kinematic, muscle and brain activity and combines the main physiological variables extracted from these signals using principal component analysis (PCA). We tested it in a group of six sub-acute stroke subje...

中文翻译:

捕获卒中后时间动态恢复的多模式方法。

目的。过去已经开发了几种训练程序来恢复中风后的运动功能。它们的功效在很大程度上取决于评估个体损伤程度和恢复率的可能性。但是,常用的临床量表主要依靠主观功能评估,不能完全描述患者的神经生物力学状态。因此,当前的临床测试应与特定的生理测量(即运动,肌肉和脑部活动)相结合,以通过时间和康复干预深入了解患者的状况及其演变。方法。我们提出了一种用于运动控制评估的多元方法,该方法可以同时测量运动学,肌肉和大脑活动,并使用主成分分析(PCA)结合从这些信号中提取的主要生理变量。我们在六个亚急性中风受试者中进行了测试。
更新日期:2020-07-10
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