SPEECH MOVEMENT CLASSIFICATION FOR ASSESSING AND TREATING ALS

描述(由申请者提供)：本项目的目的是利用新的基于计算机的方法促进对ALS所致言语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。语音运动数据将使用定制的机器学习算法进行分析，以满足ALS患者的三个重要翻译需求：改进的语音运动参与的早期检测，改进的语音运动下降的进度监控，以及改进的保持口头交流的选项。在数据挖掘、语音-语言病理学、临床神经学和空间统计学方面拥有专业知识的跨学科团队处于有利地位，可以进行这项研究。如果成功，这些特定的目标有可能改变言语语言病理学家、神经病学家和其他相关卫生保健专业人员的临床实践。这项拟议中的研究将对ALS导致的言语运动障碍患者以及可能因中风、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部或喉癌而导致的其他言语运动障碍患者产生影响，从而改善人类健康。

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.