A digital tool for monitoring speech decline in ALS

项目摘要 肌萎缩侧索硬化症（ALS）是一种致命的神经退行性疾病， 肢体、躯干和头颈部（延髓）运动功能丧失，是最常见的成人发病运动神经元 疾病该疾病的特征是在发病区域和发病部位具有显著的患者间异质性。 模式和进展速度，使早期和准确的诊断困难。大多数ALS患者会 最终获得延髓症状，包括言语和吞咽的丧失。的社会和心理 交流丧失对ALS患者生活质量的影响是显著的，并且是一种诊断工具， 及早、准确地发现这些变化，并且容易得不到满足。 此外，ALS中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。虽然演讲 测试是许多神经评估电池的核心组成部分，很少有商业数字语音 已经开发或科学验证了监测工具，特别是针对ALS。该项目旨在开发 并科学地验证数字语音评估工具-模态数字语音监测工具（M- DSMT）-用于监测ALS引起的言语衰退。 M-DSMT是完全自动化的，在线的，客观的，可扩展的，可访问的，并在实时使用。工具 与操作系统和设备无关，在商用笔记本电脑、平板电脑或智能手机上运行。 因此，如果证明是有效的，所提出的工具可以迅速商业化并部署到 标准治疗和临床试验我们的具体目标是（1）优化远程质量和产量 用于自动测量的音频和视频记录，（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。此项目的 目的是改善ALS患者的诊断，降低语言评估的成本，并允许 旅行有困难的患者可以继续获得定期的语言评估。最终我们 旨在提高ALS患者的护理质量，并促进正在进行的发现治愈方法的努力。 通过这项创新技术的发展来治疗致命疾病。

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.