SPEECH MOVEMENT CLASSIFICATION FOR ASSESSING AND TREATING ALS

用于评估和治疗 ALS 的言语运动分类

• 批准号: 8613983
• 负责人: JORDAN R GREEN
• 金额: $ 64.26万
• 依托单位: MGH INSTITUTE OF HEALTH PROFESSIONS
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-12-01 至 2018-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8613983
• 关键词: Address; Age; Algorithms; American; Amyotrophic Lateral Sclerosis; Cerebral Palsy; Classification; Clinical; Communication Aids for Disabled; Computers; Custom; Data; Data Set; Deglutition; Deterioration; Development; Device Designs; Diagnosis; Dimensions; Disease; Disease Progression; Dysarthria; Early Diagnosis; Electromagnetics; Equilibrium; Family; Future; Gender; General Population; Goals; Gulf War; Health; Health Professional; Human; Impairment; Incidence; Individual; Jaw; Language; Life; Lip structure; Machine Learning; Malignant neoplasm of larynx; Maps; Measures; Modeling; Monitor; Motor; Motor Neuron Disease; Movement; Multiple Sclerosis; Muscle; National Institute of Neurological Disorders and Stroke; Neurologist; Neurology; Oral; Outcome Measure; Parkinson Disease; Participant; Pathologist; Pathway interactions; Patients; Performance; Persons; Pharmaceutical Preparations; Positioning Attribute; Production; Quality of life; Research; Severities; Speech; Speech Disorders; Speech Intelligibility; Speech Synthesizers; Speech-Language Pathology; Staging; Stroke; System; Technology; Time; Tongue; Traumatic Brain Injury; Validation; Veterans; Wit; Work; base; clinical decision-making; clinical practice; data mining; diagnostic accuracy; digital; forging; improved; innovation; jaw movement; motor impairment; novel; novel strategies; oral communication; orofacial; prognostic; public health relevance; research study; socioeconomics; statistics; tool

DESCRIPTION (provided by applicant): The purpose of this project is advance the assessment and treatment of speech motor impairments due to ALS using novel computer-based approaches. Recently developed speech movement tracking technology will be used to record movements of tongue, lips, and jaw in 50 persons with ALS and 50 healthy control participants. The speech movement data will be analyzed using custom machine learning algorithms to address three important translational needs in person with ALS: improved early detection of speech motor involvement, improved progress monitoring of speech motor decline, and improved options for maintaining oral communication. The established interdisciplinary team with expertise in data mining, speech- language pathology, clinical neurology, and spatial statistics are well positioned to conduct this research. If successful, the specific aims have the potential to transform clinical practice for speech-language pathologists, neurologists, and other related health care professionals. The propose research will enhance human health by making an impact on individuals with speech motor impairment due to ALS and potentially to a broad range of other speech motor due to stroke, traumatic brain injury, multiple sclerosis, Parkinson's disease, cerebral palsy, traumatic brain injury, and orofacial or laryngeal cancer.

描述（由申请人提供）：该项目的目的是使用基于计算机的新型方法推进对 ALS 引起的言语运动障碍的评估和治疗。最近开发的言语运动跟踪技术将用于记录 50 名 ALS 患者和 50 名健康对照参与者的舌头、嘴唇和下巴的运动。将使用定制机器学习算法对言语运动数据进行分析，以满足 ALS 患者的三个重要翻译需求：改进言语运动参与的早期检测、改进对言语运动衰退的进展监控以及改进维持口头交流的选项。已建立的跨学科团队拥有数据挖掘、言语病理学、临​​床神经学和空间统计学方面的专业知识，非常有能力开展这项研究。如果成功，这些具体目标有可能改变言语病理学家、神经学家和其他相关医疗保健专业人员的临床实践。这项拟议的研究将通过对因 ALS 以及可能因中风、创伤性脑损伤、多发性硬化症、帕金森病、脑瘫、创伤性脑损伤以及口面癌或喉癌引起的其他言语运动障碍的个体产生影响来改善人类健康。