SPEECH MOVEMENT CLASSIFICATION FOR ASSESSING AND TREATING ALS

描述（由申请人提供）：本项目的目的是使用新的基于计算机的方法来推进ALS所致语言运动障碍的评估和治疗。最近开发的语音运动跟踪技术将被用来记录运动的舌头，嘴唇和下巴在50人与ALS和50名健康对照参与者。将使用自定义机器学习算法分析语音运动数据，以解决ALS患者的三个重要翻译需求：改善对语音运动参与的早期检测，改善对语音运动下降的进展监测，以及改善维持口头交流的选择。已建立的跨学科团队具有数据挖掘，语音语言病理学，临床神经学和空间统计学方面的专业知识，可以很好地进行这项研究。如果成功，这些具体目标有可能改变语言病理学家、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ALS导致的言语运动障碍个体产生影响来增强人类健康，并可能对中风、创伤性脑损伤、多发性硬化症、帕金森病、脑瘫、创伤性脑损伤和口面或喉癌导致的广泛的其他言语运动产生影响。

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.