SPEECH MOVEMENT CLASSIFICATION FOR ASSESSING AND TREATING ALS

描述（由申请人提供）：本项目的目的是利用新颖的基于计算机的方法来评估和治疗ALS引起的语言运动障碍。最近开发的语言运动跟踪技术将用于记录50名ALS患者和50名健康对照者的舌头、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，以解决ALS患者本人的三个重要翻译需求：改进对言语运动参与的早期检测，改进对言语运动衰退的进展监测，以及改进维持口头交流的选择。我们在数据挖掘、语言病理学、临床神经学和空间统计学等领域建立了跨学科的专业团队，为开展这项研究做好了准备。如果成功的话，具体的目标有可能改变语言病理学家、神经学家和其他相关卫生保健专业人员的临床实践。这项拟议的研究将通过对因ALS而患有语言运动障碍的个体产生影响，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、口面癌或喉癌等其他广泛的语言运动产生影响，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.