论文标题
检测由神经系统疾病引起的步态异常
Detection of Gait Abnormalities caused by Neurological Disorders
论文作者
论文摘要
在本文中，我们利用步态有潜在地检测一些重要的神经系统疾病，即帕金森氏病，dipergia，偏瘫和亨廷顿的唱片。患有这些神经系统疾病的人通常步态非常异常，这激发了我们针对步态的潜在检测。某些异常涉及腿部，向前弯曲，非自愿运动等，以检测步态中的这种异常，我们从人类姿势的关键点中发展步态特征，即肩膀，肘部，臀部，膝盖，膝盖，踝等等。考虑到很难找到足够数量的患有这些疾病的人，他们模仿了这种疾病的人的步态。我们将其命名\ textit {neurosyngait}视频数据集。实验表明，我们的步态特征确实成功地检测了这些异常。
In this paper, we leverage gait to potentially detect some of the important neurological disorders, namely Parkinson's disease, Diplegia, Hemiplegia, and Huntington's Chorea. Persons with these neurological disorders often have a very abnormal gait, which motivates us to target gait for their potential detection. Some of the abnormalities involve the circumduction of legs, forward-bending, involuntary movements, etc. To detect such abnormalities in gait, we develop gait features from the key-points of the human pose, namely shoulders, elbows, hips, knees, ankles, etc. To evaluate the effectiveness of our gait features in detecting the abnormalities related to these diseases, we build a synthetic video dataset of persons mimicking the gait of persons with such disorders, considering the difficulty in finding a sufficient number of people with these disorders. We name it \textit{NeuroSynGait} video dataset. Experiments demonstrated that our gait features were indeed successful in detecting these abnormalities.
