A digital tool for monitoring speech decline in ALS

肌萎缩侧索硬化症(ALS)是一种致命的神经退行性疾病，导致肢体、躯干和头颈部(球)运动功能的进行性丧失，是最常见的成人起病运动神经元病。该病的特点是发病区域、模式和进展率在患者之间存在显著的异质性，使得早期和准确的诊断变得困难。大多数肌萎缩侧索硬化症患者最终会出现球症状，包括说话和吞咽。沟通障碍对肌萎缩侧索硬化症患者生活质量的社会和心理影响是显著的，而早期、准确和容易地发现这些变化的诊断工具仍未得到满足。此外，ALS迫切需要改进的语音测试工具，以(1)改进诊断测试和监测，以及(2)加快行为和药物干预的临床试验。尽管语音测试是许多神经评估组件的核心组成部分，但很少有商业数字语音监控工具被开发或科学验证，特别是针对ALS。本项目旨在开发和科学验证一个数字语音评估工具--通道数字语音监控工具(M-DSMT)--用于监控由于ALS引起的语音下降。M-DSMT是完全自动化的、在线的、客观的、可扩展的、可访问的，并且是实时使用的。该工具与操作系统和设备无关，可在市面上销售的笔记本电脑、平板电脑或智能手机上运行。因此，如果被证明是有效的，建议的工具可以迅速商业化并部署到ALS的标准护理和临床试验中。我们的具体目标是(1)优化用于自动测量的远程音频和视频记录的质量和产量，(2)确定M-DSMT的分析有效性，(3)确定M-DSMT的临床有效性，以及(4)确定M-DSMT的可用性。该项目的目标是提高对肌萎缩侧索硬化症患者的诊断，降低语音评估的成本，并允许旅行困难的患者继续获得定期语音评估。最终，我们的目标是提高肌萎缩侧索硬化症患者的护理质量，并通过开发这项创新技术，促进正在进行的发现这种致命疾病的治疗方法的努力。

PROJECT SUMMARY Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease resulting in the progressive loss of limb, trunk, and head and neck (bulbar) motor function and is the most common adult-onset motor neuron disease. The disease is characterized by significant across-patient heterogeneity in the onset region and in pattern and progression rate, making early and accurate diagnosis difficult. Most individuals with ALS will eventually acquire bulbar symptoms, including a loss of speech and swallowing. The social and psychological impact of communication loss on the quality of life of patients with ALS is significant and a diagnostic tool to detect these changes early, accurately, and easily remains unmet. Moreover, improved speech testing tools are critically needed in ALS to (1) improve diagnostic testing and monitoring, and (2) expediting clinical trials of behavioral and pharmacologic interventions. Although speech testing is a core component of many neurological assessment batteries, few commercial digital speech monitoring tools have been developed or scientifically validated, especially for ALS. This project aims to develop and scientifically validate a digital speech assessment tool – the Modality Digital Speech Monitoring Tool (M- DSMT) - for monitoring speech decline due to ALS. The M-DSMT is fully automated, online, objective, scalable, accessible, and is used in real-time. The tool is operating-system and device-agnostic, running on commercially available laptops, tablets, or smartphones. Therefore, if demonstrated to be effective, the proposed tool can be rapidly commercialized and deployed into standard care and clinical trials for ALS. Our specific aims are to (1) optimize the quality and yield of remote audio and video recordings for automated measurement, (2) determine the analytical validity of the M-DSMT, (3) determine the clinical validity of the M-DSMT, and (4) determine the usability of the M-DSMT. This project's objectives are to improve diagnosis for patients with ALS, decrease costs of speech assessment, and allow patients who have difficulty traveling to continue to have access to regular speech assessments. Ultimately, we aim to improve the quality of care in persons with ALS and facilitate ongoing efforts to discover a cure for this fatal disease through the development of this innovative technology.