Clinical Recognition of Sensory Ataxia and Cerebellar Ataxia - Zhang, Qing; Zhou, Xihui; Li, Yajun; Yang, Xiaodong; Abbasi, Qammer H. (Frontiers in Human Neuroscience, 2021)
Ataxia is a kind of external characteristic that appears on human body harmoniously undesirable and balance obstacle, it often indicates that some parts of the body have effected from diseased. There are many internal factors leading to ataxia. Currently, doctors often observe the external characteristics of patients with naked eyes and judge the cause of ataxia by combining their own experience, as a result, sensory ataxia is often misdiagnosed as cerebellar ataxia, which makes patients unable to get accurate and effective treatment and cause of delayed recovery. However, using modern high-precision medical instruments for detection is mostly expensive, which increases the economic burden on patients. In this paper, wireless sensing technology is used to detect and distinguish sensory ataxia and cerebellar ataxia. Firstly, the data of patients in Romberg's test and gait detection are collected by a wireless sensing system composed of omnidirectional antennas, then the data is preprocessed, finally, three machine learning algorithms are used to train the model. The experimental results show that the prediction accuracy of most algorithms can reach above 96%, which proves that the technical scheme described in this paper is feasible and effective.