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The development and validation of a novel tool for the assessment of bulbar dysfunction in ALS

评估 ALS 延髓功能障碍的新工具的开发和验证

基本信息

批准号：
10405152
负责人：
JORDAN R GREEN
金额：
$ 18.69万
依托单位：
SUNNYBROOK RESEARCH INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-07-20 至 2023-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10405152
关键词：
Acoustics Affect Amyotrophic Lateral Sclerosis Applications Grants Architecture Artificial Intelligence Aspiration Pneumonia Assessment tool Back COVID-19 pandemic Clinic Clinical Clinical Research Clinical Trials Clinical assessments Collaborations Collection Computer software Coupled Data Data Analytics Data Collection Data Scientist Deglutition Dehydration Development Dysarthria Engineering Evaluation Event Face Functional disorder Funding Opportunities Goals Guidelines Impairment Internet Interruption Intuition Length Malnutrition Measurement Measures Methodology Methods Modernization Monitor Motor Motor Neuron Disease Myography Needs Assessment Neurologic Outcome Measure Parkinson Disease Patients Performance Persons Process Quality of life Readiness Research Research Personnel Scientist Security Signal Transduction Software Design Software Engineering Software Tools Speech Standardization Technology Testing Time Training United States National Institutes of Health Update Validation Video Recording Work base clinical examination clinical practice cloud based cloud platform data management data sharing design electric impedance experience indexing interoperability kinematics motor disorder movement analysis multimodality nervous system disorder novel orofacial pandemic disease parent grant post stroke social software development technology development telehealth tool usability user centered design user-friendly virtual web services

项目摘要

Project Summary The overall aim of our “parent” grant proposal is to develop and validate a clinician-administered bulbar dysfunction assessment tool for Amyotrophic Lateral Sclerosis (ALS), called ALS-Index of Bulbar Dysfunction (ALS-IBD). Interrupted by the SARS-CoV-2 pandemic, clinical practices as well as clinical research have been forced to pivot, simultaneously providing an unprecedented opportunity for the development of new and expansion of existing remote assessment platforms, which can serve clinical and research assessment needs. As part of this pivoting effort, we recently created VirtualSLP, a software tool to support remote, online multi- modal - high quality video/kinematic and audio/acoustic – data collection, using a multi-platform compatible, web-browser based audio and video recordings. In parallel, we have designed a tool for automatic extraction of kinematic and acoustic metrics of neurological diseases, which provides clinically interpretable features/ measures that have been identified as important for detecting and tracking the onset and progression of oro- motor and speech (aka bulbar) impairments in neurological diseases. The next step in the progression of our technology development efforts is to incorporate the automatic metrics extraction software within VirtualSLP, creating a user-friendly and intuitive cloud-based platform for research and clinical assessment of bulbar dysfunction. To achieve rapid development and deployment of VirtualSLP, we will use modern engineering methodology and user-centered design to iterate through a number of steps in the software development cycle. The cycle will begin with the engagement of end users (e.g., researchers, clinicians and patients) in design sessions to document users' current and anticipated end-to-end experiences with the software, while performing the baseline analysis of the existing software components and determining and implementing necessary changes. The necessary components will be incorporated to create VirtualSLP on the Amazon Web Services (AWS) platform, to enhance its usability, interoperability, scalability, and security, as part of the NIH STRIDES initiative. Usability testing of Virtual SLP with end users will be performed throughout the development process and at the end of the development cycle. When completed, the work will result in an enhanced software tool for collection of audio and video data and corresponding AI-based analytics to be used in the context of clinical research. VirtualSLP will propel our specific work on developing a clinician- administered tool for bulbar ALS assessment and monitoring (ALS-IBD-Remote) by providing a novel cloud- based platform for its clinical validation. This work aims to exemplify the intent of the current funding opportunity by supporting collaborations between clinical speech scientists, data scientists, and software engineers to enhance the design, implementation, and "cloud-readiness" of research software.

项目总结