An Effective and Automatic Method to Aid the Diagnosis of Amyotrophic Lateral Sclerosis Using One Minute of Gait Signal

机译：一种有效和自动的方法，可帮助使用一分钟信号诊断肌营养侧面硬化的诊断

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Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease that affects the nervous system responsible for muscle movement and eventually compromising one's ability to walk. Diagnosing ALS is a difficult task since no test can provide a definite diagnosis. In this sense, automatic methods that aid the diagnosis of ALS have an essential role in helping to reach a diagnose. However, most of the existing approaches that use gait dynamics are based on a 5-minute observation, which can be exhausting and demanding for a patient with ALS seeking the diagnosis. This paper proposes an automated method to aid the diagnosis of ALS using information obtained from one minute gait observation. The GaitNDD database, which provides gait data recorded for 5 minutes from people with ALS and from healthy subjects, was used to support and validate this study. Results are reported and evaluated for different machine learning classifiers. Features extracted from either 1-min or 5-min observations are evaluated. Our results show that 96.6% of accuracy was achieved for data derived from either the first or the 5-minute walking, with excellent sensitivity and specificity, thus showing that our method can help aid the diagnosis of ALS while reducing the time required for the walking experiment.

机译：肌萎缩的外侧硬化剂（ALS）是一种神经变性疾病，影响负责肌肉运动的神经系统，最终损害一个人的行走能力。诊断ALS是一项艰巨的任务，因为没有测试可以提供明确的诊断。从这个意义上讲，帮助诊断ALS的自动方法在帮助诊断方面具有重要作用。然而，使用步态动态的大多数现有方法基于5分钟的观察，这可能对寻求诊断的患者来说，这可能对患者进行耗尽和要求。本文提出了一种自动化方法，以帮助使用从一分钟步态观察获得的信息诊断ALS。 GAITNDD数据库提供从ALS和健康主题的人员录制5分钟的步态数据，用于支持和验证这项研究。报告并评估了不同机器学习分类器的结果。评估从1分钟或5分钟观察中提取的特征。我们的研究结果表明，从第一个或5分钟的步行源自源自敏感性和特异性，实现了96.6％的准确性，从而表明我们的方法可以帮助辅助ALS的诊断，同时减少行走所需的时间实验。

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《IEEE International Conference on Bioinformatics and Biomedicine》|2020年|2745-2751|共7页
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Juliana Paula Felix; Hugo Alexandre Dantas do Nascimento; Nilza Nascimento Guimarães; Eduardo Di Oliveira Pires; Gabriel da Silva Vieira; Wanderley de Souza Alencar;
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Time series analysis; Feature extraction; Diseases; Legged locomotion; Databases; Foot; Standards;

机译：时间序列分析;特征提取;疾病;腿运动;数据库;脚;标准;

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机译：肌萎缩性侧索硬化的步态节奏波动的计算机辅助分析。
2. A robust, cost-effective and non-invasive computer-aided method for diagnosis three types of neurodegenerative diseases with gait signal analysis [J] . Measurement . 2020,第期

机译：一种稳健，经济效益和无侵入性的计算机辅助计算机辅助方法，用于诊断具有步态信号分析的三种类型的神经变性疾病
3. Initial Identification of a Blood-Based Chromosome Conformation Signature for Aiding in the Diagnosis of Amyotrophic Lateral Sclerosis [J] . Matthew Salter, Emily Corfield, Aroul Ramadass, EBioMedicine . 2018,第11期

机译：基于血液的染色体构象签名的初步鉴定，可用于肌萎缩性侧索硬化症的诊断
4. Data Mining to Support the Discrimination of Amyotrophic Lateral Sclerosis Diseases Based on Gait Analysis [C] . Haya Alaskar, Abir Jaafar Hussain International conference on intelligent computing . 2018

机译：基于步态分析的数据挖掘支持肌萎缩性侧索硬化病的鉴别
5. The effects of the insulin signaling pathway on TDP-43 neurotoxicity in amyotrophic lateral sclerosis. [D] . Riffer, Michelle Kori. 2016

机译：胰岛素信号通路对肌萎缩性侧索硬化症中TDP-43神经毒性的影响。
6. Initial Identification of a Blood-Based Chromosome Conformation Signature for Aiding in the Diagnosis of Amyotrophic Lateral Sclerosis [O] . Matthew Salter, Emily Corfield, Aroul Ramadass, 2018

机译：基于血液的染色体构象签名的初步鉴定可用于肌萎缩性侧索硬化症的诊断
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8. Summary Report: Amyotrophic Lateral Sclerosis and Multiple Sclerosis Surveillance Annual Meeting, June 24-25, 2009: Issues Related to Developing a National Surveillance System and Registries for Amyotrophic Lateral Sclerosis and Multiple Sclerosis [R] . 2009

机译：摘要报告：肌萎缩侧索硬化症和多发性硬化症监测年会，2009年6月24日至25日：与建立肌萎缩侧索硬化症和多发性硬化症的国家监测系统和登记相关的问题

An Effective and Automatic Method to Aid the Diagnosis of Amyotrophic Lateral Sclerosis Using One Minute of Gait Signal

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