通过盒子和块测试的自动评估神经障碍的适应症

T. Lee, J. G. Lim, K. Leo, S. Sanei
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引用次数: 4

摘要

日益增长的全球老龄化人口的需求引起了全世界的关注。随之而来的人类神经系统老化是中风和许多其他神经系统疾病的主要危险因素。这些病理状况影响日常生活活动,给社会带来支持和资源负担。康复是一个长期的、资源密集的过程,即便如此,它在执行过程中也可能是主观的和不一致的。我们提出了一种新的系统,通过电子评分来指示神经障碍的水平,这是一种广泛使用的上肢康复评估。这是通过在评估中使用的物体中嵌入广泛可用的传感器来实现的。我们通过从这些传感器中获得的两个新特征来增强这一点,并使用数据驱动的方法处理其中一个特征。我们进行了一系列试点试验,以证明我们的方法的有效性,并取得了令人鼓舞的结果。
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Indications of Neural Disorder through Automated Assessment of the Box and Block Test
The needs of an ever growing global aging population are a cause of world wide concern. The consequent ageing of the human nervous system is a major risk factor for stroke and many other neurological disorders. These pathological conditions affect the activities of daily living and impose a support and resource burden on society. Rehabilitation is long term and resource intensive and even so, it can be subjective and inconsistent in execution. We propose a novel system to indicate the level of neurological disorder by electronically scoring a widely used rehabilitative assessment for the upper limb. This is done by embedding widely available sensors into the objects used in this assessment. We enhance this with a two new features derived from these sensors and process one of them using a data driven approachA set of pilot trials were conducted to demonstrate the effectiveness of our approach with promising results.
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