Non-Contact Solution for Quantitative Clinical Management of MTD

MTD 定量临床管理的非接触式解决方案

基本信息

批准号：
10256594
负责人：
Jennifer Michele Vojtech
金额：
$ 25.64万
依托单位：
ALTEC, INC.
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-02-01 至 2023-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10256594
关键词：
Acoustics Address Affect Agreement Auditory Auditory Perception Behavior Boston COVID-19 Caring Clinic Clinical Clinical Management Communication Complement Computational algorithm Computer software Consumption Databases Development Devices Dysphonia Endoscopy Equilibrium Exercise Feedback Foundations Funding Goals Health Image Individual Laboratories Language Language Disorders Laryngeal muscle structure Larynx Lead Loudness Manipulative Therapies Manuals Massage Measurable Measures Medical Methods Monitor Muscle Muscle Tension National Institute on Deafness and Other Communication Disorders Neck Operative Surgical Procedures Otolaryngologist Outcome Measure Pain Palpation Pathologist Patients Peer Review Performance Persons Phase Procedures Protocols documentation Quality of life Research Personnel Risk Sampling Series Signal Transduction Site Small Business Innovation Research Grant Social Interaction Software Tools Specialist Speech Speech Disorders System Technology Testing Time Translating Translations United States National Institutes of Health Universities Visit Voice Voice Disorders Work automated algorithm base behavioral response chronic pain clinical care clinical infrastructure clinical practice compliance behavior cost data management design evidence base impression improved meetings microphone new technology non-compliance point of care prevent prototype remote assessment remote health care signal processing software development sound telehealth tool treatment response vocal cord vocalization voice therapy

项目摘要

This Phase I SBIR will develop a new clinical software that can be used by Speech Language Pathologists (SLPs) to inform the assessment and treatment of Muscle Tension Dysphonia (MTD), one of the most common voice disorders in clinical practice. MTD is characterized by abnormal coactivation of muscles in and around the larynx that causes vocal strain - leading to discomfort and pain that impede vocal communication and may lead to surgery. While voice therapy can mitigate these health risks by reducing laryngeal tension and restoring muscle balance, the current standard for guiding therapy is by manual palpations and auditory-perceptual impressions – highly subjective methods with poor inter-rater reliability. The most direct approach to quantitative measures of laryngeal muscle tension is manual analysis of vocal fold images from an endoscopy – an invasive and time- consuming method that is not clinically viable for routine assessment and management of MTD. These methods are also incompatible with the recent need for technology that facilitates remote assessment in the wake of COVID-19. We will address these needs by developing a new non-contact software tool that provides accurate, valid, acoustic measures of MTD during speech exercises involving the offset and onset of vocalization. This approach has been shown in our prior NIH-funded studies to elicit measurable acoustic changes associated with the presence and absence of MTD and following voice therapy. Leveraging this clinical foundation, our team of signal processing experts at Altec Inc. will partner with speech researchers, SLPs and otolaryngologists at Boston University to translate our preliminary laboratory-based software into a turn-key clinical tool to support both in-person and remote assessment and management of MTD. We will do so by translating our existing time- consuming manual approach for measuring laryngeal tension into clinical software that uses fully-automated algorithms to achieve high accuracy when tested on an existing database of N=450 individuals with and without MTD (Aim 1). The automated algorithms will be complemented by software to guide patient compliance with the MTD-specific speech exercises and provide SLPs with quantitative outcome measures for a robust, clinically- viable implementation (Aim 2). Aim 3 will evaluate our MTD software prototype by N=4 SLPs in N=12 patients with MTD to demonstrate the proof of concept that: 1) it provides accurate measures compared to validated manual procedures; 2) it detects changes in laryngeal tension due to increased vocal effort or laryngeal massage therapy with >95% agreement to manual procedures; and 3) it achieves favorable ratings of feasibility, acceptability and perceived value by patients and SLPs. Phase II will advance our Phase I prototype with real- time calculations, an acoustic signal quality monitor, and a HIPPA-compliant data management infrastructure for clinical point-of-care or remote use. It’s reliance on low-cost, readily available, non-contact sensing provides a practical and effective tool to support in-person and remote clinical care for those with MTD that advances the NIDCD priorities for technologies to improve health among individuals with speech and language disorders. 1

第一阶段 SBIR 将开发一种可供语音语言病理学家 (SLP) 使用的新临床软件为肌肉紧张性发声困难 (MTD) 的评估和治疗提供信息，MTD 是最常见的声音之一临床实践中的 MTD 疾病的特点是喉部及其周围肌肉的异常协同激活。导致声音紧张 - 导致不适和疼痛，阻碍声音交流，并可能导致而声音治疗可以通过减少喉部张力和恢复肌肉来减轻这些健康风险。平衡，目前指导治疗的标准是通过手动触诊和听觉感知印象 – 高度主观的方法，评估者间的可靠性较差。最直接的定量测量方法。喉部肌肉张力的分析是对内窥镜检查中的声带图像进行手动分析——一种侵入性且耗时的方法。对于 MTD 的常规评估和管理来说，临床上不可行的消费方法。也不符合最近对促进远程评估的技术的需求我们将通过开发一种新的非接触式软件工具来满足这些需求，以应对新冠肺炎 (COVID-19) 的需求。在涉及发声偏移和开始的言语练习中，有效的 MTD 声学测量。我们之前的 NIH 资助的研究表明，这种方法可以引起可测量的声学变化 MTD 的存在与否以及声音治疗之后，我们的团队利用这一临床基础。 Altec Inc. 的信号处理专家将与波士顿的语音研究人员、SLP 和耳鼻喉科医生合作大学将我们初步的基于实验室的软件转化为交钥匙临床工具，以支持两者我们将通过转换现有的时间来实现 MTD 的现场和远程评估和管理。将用于测量喉部张力的手动方法导入到使用全自动的临床软件中在 N=450 个人的现有数据库上进行测试时，算法可以实现高精度 MTD（目标 1）将由软件补充，以指导患者遵守规定。 MTD 特定的演讲练习，并为 SLP 提供定量结果测量，以实现稳健的临床- 可行的实施（目标 2）将通过 N=12 名患者的 N=4 个 SLP 来评估我们的 MTD 软件原型。使用 MTD 来证明概念证明：1) 与经过验证的相比，它提供了准确的测量结果手动程序；2) 它检测由于发声力度增加或喉部按摩而导致的喉部张力变化治疗与手动手术的一致性超过 95%；并且 3) 它获得了良好的可行性评级，患者和 SLP 的可接受性和感知价值将进一步推进我们的 I 期原型。时间计算、声学信号质量监视器和符合 HIPPA 标准的数据管理基础设施用于临床护理点或远程使用，它依赖于低成本、易于获得的非接触式传感。一种实用且有效的工具，支持对 MTD 患者进行现场和远程临床护理，从而推动 NIDCD 优先考虑改善言语和语言障碍患者健康的技术。 1