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: 10838866
• 负责人: JORDAN R GREEN
• 金额: $ 99.85万
• 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 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10838866
• 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; Health Services; Healthcare; Heterogeneity; Impairment; Individual; Internet; Intervention; Intuition; Laboratories; Language; Learning; Licensing; Machine Learning; Marketing; 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; Performance; Persons; Pharmacologic Substance; Phase; Psychological Impact; Quality of Care; Quality of life; Research; Resolution; Risk; Running; Sensitivity and Specificity; 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; behavioral clinical trial; cohort; commercialization; cost; data quality; diagnostic accuracy; diagnostic tool; digital; digital tool; experience; handheld mobile device; health care delivery; improved; innovative technologies; instrumentation; laptop; limb loss; novel; pharmacologic; programs; public health relevance; remote administration; response; risk mitigation; routine practice; 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.

肌萎缩性侧索硬化症（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，是最常见的成人发病的运动神经元疾病。该疾病的特点是在发病区域、模式和进展率上具有显著的跨患者异质性，使早期和准确诊断变得困难。大多数ALS患者最终会出现球症状，包括丧失语言和吞咽能力。沟通丧失对ALS患者生活质量的社会和心理影响是显著的，而早期、准确和容易发现这些变化的诊断工具仍然缺乏。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。虽然语音测试是许多神经系统评估电池的核心组成部分，但很少有商业数字语音监测工具被开发或科学验证，特别是针对ALS。本项目旨在开发并科学验证一种数字语音评估工具-模态数字语音监测工具(M- DSMT) -用于监测ALS引起的语音衰退。M-DSMT是全自动的、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，可以运行在商用笔记本电脑、平板电脑或智能手机上。因此，如果被证明是有效的，所提出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ALS患者的诊断，降低语言评估的成本，并允许有旅行困难的患者继续获得定期的语言评估。最终，我们的目标是提高ALS患者的护理质量，并通过这项创新技术的发展促进对这种致命疾病的治疗。