A digital tool for monitoring speech decline in ALS

用于监测 ALS 言语衰退的数字工具

• 批准号: 10482581
• 负责人: JORDAN R GREEN
• 金额: $ 33.28万
• 依托单位: MODALITY.AI , INC
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10482581
• 关键词: ALS patients; Address; Adoption; Adult; Adverse effects; Affect; Amyotrophic Lateral Sclerosis; Area; Artificial Intelligence; Assessment tool; COVID-19 pandemic; Caring; Cellular Phone; Characteristics; Clinical; Clinical Trials; Communication; Computers; Data; Data Analyses; Data Collection; Deglutition; Development; Devices; Diagnosis; Diagnostic; Diagnostic tests; Disease; Early Diagnosis; Effectiveness; Ensure; Goals; Head and neck structure; Health Personnel; Health Professional; Healthcare; Heterogeneity; Impairment; Individual; Internet; Intervention; Intuition; Laboratories; Language; Learning; Machine Learning; Measurement; Measures; Modality; Monitor; Motor; Motor Neuron Disease; National Institute on Deafness and Other Communication Disorders; Neurodegenerative Disorders; Neurologic; Online Systems; Operating System; Outcome; Palliative Care; Participant; Pathologist; Patients; Pattern; Persons; Pharmacologic Substance; Phase; Psychological Impact; Quality of Care; Quality of life; Research; Resolution; Risk; Running; Sensitivity and Specificity; Services; Severities; Small Business Technology Transfer Research; Social Impacts; Speech; Strategic Planning; Surveys; Symptoms; System; Tablets; Target Populations; Technology; Testing; Time; Training; Travel; Treatment outcome; Underserved Population; United States National Institutes of Health; Video Recording; Vulnerable Populations; Work; accurate diagnosis; base; behavioral clinical trial; behavioral pharmacology; cohort; cost; data quality; diagnostic accuracy; diagnostic tool; digital; experience; handheld mobile device; improved; innovative technologies; instrumentation; laptop; limb loss; novel; performance tests; programs; response; routine practice; service delivery; speech accuracy; standard care; success; telehealth; tool; usability

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.

项目概要 肌萎缩侧索硬化症 (ALS) 是一种致命的神经退行性疾病，会导致进行性进展 肢体、躯干和头颈（延髓）运动功能丧失，是最常见的成人发病的运动神经元 疾病。该疾病的特点是发病区域和发病部位存在显着的跨患者异质性。 模式和进展率，使得早期和准确的诊断变得困难。大多数 ALS 患者会 最终出现延髓症状，包括语言障碍和吞咽障碍。社会和心理 沟通障碍对 ALS 患者生活质量的影响是显着的，并且是一种诊断工具 尽早、准确地发现这些变化，并且很容易无法满足。 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；(2) 加快行为和药物干预的临床试验。虽然言语 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 监测工具已经开发出来或经过科学验证，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——模态数字语音监控工具（M- DSMT) - 用于监测 ALS 导致的言语衰退。 M-DSMT 是完全自动化、在线、客观、可扩展、可访问且实时使用的。工具 与操作系统和设备无关，可在市售笔记本电脑、平板电脑或智能手机上运行。 因此，如果被证明是有效的，所提出的工具可以快速商业化并部署到 ALS 的标准护理和临床试验。我们的具体目标是 (1) 优化远程生产的质量和产量 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。这个项目的 目标是改善 ALS 患者的诊断，降低言语评估的成本，并允许 旅行有困难的患者可以继续接受定期言语评估。最终，我们 旨在提高 ALS 患者的护理质量，并促进不断努力寻找治疗方法 通过这项创新技术的发展，可以治疗致命的疾病。