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A tablet- and mobile-based application for remote diagnosis and analysis of movement disorder symptoms

机译:基于平板电脑和手机的应用程序,用于运动障碍症状的远程诊断和分析

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One significant hindrance to effective diagnosis of movement disorders (MDs) and analysis of their progression is the requirement for patients to conduct tests in the presence of a clinician. Here is presented a pilot study for diagnosis of essential tremor (ET), the world’s most common MD, through analysis of a tablet- or mobile-based drawing task that may be selected at will, with the spiral- and line-drawing tasks of the Fahn-Tolosa-Marin tremor rating scale serving as our task in this work. This system replaces the need for pen-and-paper drawing tests while permitting advanced quantitative analysis of drawing smoothness, pressure applied, and other measures. Data is securely recorded and stored in the cloud, from which all analysis was conducted remotely. This will enable longitudinal analysis of patient disease progression without the need for excessive clinical visits. Several features were extracted and recursive feature elimination applied to rank the features’ individual contribution to our classifier. Maximum cross-validated classification accuracy on a preliminary sample set was 98.3%. Future work will involve collecting healthy subject data from an age-controlled population and extending this diagnostic application to additional conditions, as well as incorporating regression-based symptom severity analysis. This highly promising new technology has the potential to substantially alleviate the demands placed on both clinicians and patients by bringing MD treatment more into line with the era of personalized medicine.
机译:有效诊断运动障碍(MDs)和对其进展进行分析的一大障碍是要求患者在临床医生在场的情况下进行测试。通过分析可随意选择的基于平板电脑或移动设备的绘图任务,以及螺旋线和线描任务,在这里提出了一项用于诊断世界上最常见的MD的原发性震颤(ET)的试验性研究。 Fahn-Tolosa-Marin震级评定量表是我们在这项工作中的任务。该系统取代了纸笔绘图测试的需要,同时允许对绘图平滑度,施加的压力和其他措施进行高级定量分析。数据被安全地记录并存储在云中,所有分析都通过该云进行远程。这将能够对患者疾病进展进行纵向分析,而无需进行过多的临床就诊。提取了多个特征,并应用了递归特征消除,以对特征对我们分类器的贡献进行排名。初步样本集的最大交叉验证分类准确性为98.3%。未来的工作将包括从年龄受控的人群中收集健康的受试者数据,并将此诊断应用程序扩展到其他条件,以及纳入基于回归的症状严重性分析。通过使MD治疗更符合个性化医学的时代,这项极具前景的新技术有可能从根本上减轻对临床医生和患者的需求。

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