Center for Smart Use of Technology to Assess Real-world Outcomes (C-STAR)

智能运用技术评估现实世界成果中心 (C-STAR)

• 批准号: 10646509
• 负责人: Richard L. Lieber
• 金额: $ 116.46万
• 依托单位: REHABILITATION INSTITUTE OF CHICAGO D/B/A SHIRLEY RYAN ABILITYLAB
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10646509
• 关键词: Address; Applications Grants; Area; Biomedical Engineering; Calibration; Cellular Phone; Chicago; Client; Clinic; Clinical; Collaborations; Communities; Data; Databases; Disabled Persons; Disease Progression; Economics; Educational process of instructing; Elements; Engineering; Environment; Evidence based practice; Feedback; Funding; Goals; Grant; Home; Hospitals; Human; Individual; Infrastructure; Institution; Instruction; Intervention; Kinesiology; Laboratories; Learning; Letters; Level of Evidence; Life; Measures; Mechanics; Mentors; Mentorship; Methodology; Network Infrastructure; Neurosciences; Outcome; Outcome Measure; Patient Outcomes Assessments; Patient-Focused Outcomes; Patients; Performance; Physical Medicine; Physical therapy; Physiology; Pilot Projects; Process; Proliferating; Publications; R24; Rehabilitation therapy; Research; Research Infrastructure; Research Personnel; Resources; Robot; Schools; Scientist; Seasons; Senior Scientist; Standardization; Technology; Technology Assessment; Testing; Time; Translational Research; United States National Institutes of Health; Universities; Veterans; Visit; Work; clinically relevant; cohort; community engagement; compliance behavior; design; experience; experimental study; implementation science; insight; new technology; novel; operation; patient population; physically handicapped; programs; rehabilitation research; rehabilitation science; sabbatical; sensor; smart watch; technology validation; treatment response; web site; webinar

Project Summary—Overall We propose a national infrastructure center entitled “Center for Smart Use of Technologies to Assess Real- World Outcomes (C-STAR)” that directly addresses priority area #6 from RFA HD-20-04: “Technology to Track Real-World Outcomes.” Leveraging the collective experience of our clinicians, scientists, engineers, and patients, our program will provide the expertise, instruction, and mentoring to support the smart (i.e., appropriate, accurate, and clinically meaningful) use of technology to assess performance in the laboratory (e.g., by providing design insight for a new sensor), in the clinic (e.g., by teaching proper selection and placement of sensors on a patient's body) and in the community (e.g., by guiding investigators on appropriate, validated patient reported outcome measures to evaluate technology). By measuring performance across these domains, rehabilitation researchers and clinicians will be able to both track real-world outcomes and investigate mechanisms underlying response to therapy or disease progression. A compelling need for rehabilitation research infrastructure exists in this area because of: (1) the huge proliferation of sensors and other technologies that make it easy to “acquire data” without the necessary expertise to validate, interpret, and establish the clinical relevance of these data, (2) the need to quantify and standardize outcomes—to not just understand clinical outcomes but to provide important economic and societal perspectives, and (3) the need to customize, validate, standardize, and calibrate technologies in the context of specific patients' needs and abilities, which often requires access to particular patient cohorts. Our four cores—engineering, clinical, outcomes, and implementation Science/community engagement—will provide the necessary expertise to allow C-STAR clients to develop, test, validate, and standardize the use of new and existing technologies to track real-world outcomes across many disabling conditions. C-STAR clients will be individuals or teams who would like to use technology to measure performance of individuals with physical disabilities. We will provide numerous didactic, hands-on, visitation, pilot funding, and advisory resources to support C-STAR clients. We will connect with our clients through our C-STAR website and our proprietary Rehabilitation Measures Database (RMD) website (www.rehabmeasures.org) that currently averages 11,000 unique page visits per day from likely C-STAR clients. The resources C-STAR offers to the rehabilitation community include its leaders, who have 20 years of cumulative experience with the R24 national infrastructure network, and other senior scientists who experienced in the application of technology to help medical rehabilitation patients and mentorship of junior researchers. C- STAR exploits the extraordinary environment and resources of our new translational research hospital, the Shirley Ryan AbilityLab (SRAlab, formerly the Rehabilitation Institute of Chicago, RIC) as well as the collegial and fruitful collaborations developed over the past 30 years between the RIC/SRAlab and Northwestern University.

项目总结——总体 我们提议建立一个国家基础设施中心，名为“智能使用技术评估实际情况中心” 世界成果 (C-STAR)”直接解决 RFA HD-20-04 中的优先领域#6：“跟踪技术 利用我们的前辈、科学家、工程师和技术人员的集体经验。” 对于患者，我们的计划将提供专业知识、指导和指导，以支持聪明的（即适当的、 准确且具有临床意义）使用技术来评估实验室的表现（例如，通过 为新传感器提供设计见解），在临床中（例如，通过教授正确的选择和放置 患者身体上的传感器）和社区（例如，通过指导研究人员进行适当的、经过验证的 通过衡量这些领域的表现，患者报告了评估技术的结果措施）。 康复研究人员和牧师将能够跟踪现实世界的结果并进行调查 对治疗或疾病进展的反应的机制迫切需要康复。 该领域存在研究基础设施是因为：(1) 传感器和其他技术的大量扩散 这使得无需必要的专业知识即可轻松“获取数据”来验证、解释和建立临床数据 这些数据的相关性，（2）需要量化和标准化结果——而不仅仅是理解临床 结果，但提供重要的经济和社会观点，以及（3）需要定制、验证、 根据特定患者的需求和能力标准化和校准技术，这通常 需要接触特定的患者群体——工程、临床、结果和 实施科学/社区参与——将提供必要的专业知识，使 C-STAR 客户能够 开发、测试、验证和标准化新技术和现有技术的使用，以跟踪现实世界的结果 C-STAR 的客户将是希望使用技术的个人或团队。 为了衡量身体残障人士的表现，我们将提供大量的教学、实践、 我们将与客户建立联系，以支持 C-STAR 客户的访问、试点资金和咨询资源。 通过我们的 C-STAR 网站和我们专有的康复措施数据库 (RMD) 网站 (www.rehabmeasures.org)，目前平均每天有 11,000 次来自可能的 C-STAR 客户的独立页面访问。 C-STAR 为康复社区提供的资源包括其领导者，他们拥有 20 年的康复经验 R24国家基础设施网络的累积经验，以及其他经历过的资深科学家 应用技术帮助患者康复并指导初级研究人员 C- STAR 利用我们新的转化研究医院的非凡环境和资源， 雪莉·瑞安能力实验室（SRAlab，前身为芝加哥康复研究所，RIC）以及学院 以及 RIC/SRAlab 和西北大学在过去 30 年里开展的富有成效的合作 大学。

项目成果

Post-stroke Depressive Symptoms and Cognitive Performances: A Network Analysis.

中风后抑郁症状和认知表现：网络分析。

• 发表时间: 2023-10-24
• 影响因子: 4.3
• 作者: Shi, Yun;Lenze, Eric J;Mohr, David C;Lee, Jin;Hu, Lu;Metts, Christopher L;Fong, Mandy W M;Wong, Alex W K
• 通讯作者: Wong, Alex W K

Heart rate variability as a biomarker of functional outcomes in persons with acquired brain injury: Systematic review and meta-analysis.

心率变异性作为获得性脑损伤患者功能结果的生物标志物：系统评价和荟萃分析。

• 发表时间: 2021-12
• 影响因子: 8.2
• 作者: Lee, Yejin;Walsh, Ryan J;Fong, Mandy W M;Sykora, Marek;Doering, Michelle M;Wong, Alex W K
• 通讯作者: Wong, Alex W K

Ecological Momentary Assessment of Real-World Functional Behaviors in Individuals With Stroke: A Longitudinal Observational Study.

中风患者现实世界功能行为的生态瞬时评估：一项纵向观察研究。

• 发表时间: 2022-07
• 影响因子: 4.3
• 作者: Bui, Quoc;Kaufman, Katherine J.;Pham, Vy;Lenze, Eric J.;Lee, Jin-Moo;Mohr, David C.;Fong, Mandy W. M.;Metts, Christopher L.;Tomazin, Stephanie E.;Wong, Alex W. K.
• 通讯作者: Wong, Alex W. K.

Dual-Task Interference Effects on Lower-Extremity Muscle Activities during Gait Initiation and Steady-State Gait among Healthy Young Individuals, Measured Using Wireless Electromyography Sensors.

使用无线肌电图传感器测量健康年轻人步态启动和稳态步态期间双任务干扰对下肢肌肉活动的影响。

• 发表时间: 2023-10-31
• 作者: Waldon, Ke'Vaughn Tarrel;Stout, Angeloh;Manning, Kaitlin;Gray, Leslie;Wilson, David George;Kang, Gu Eon
• 通讯作者: Kang, Gu Eon

An LSTM-based Gesture-to-Speech Recognition System.

基于 LSTM 的手势语音识别系统。

• 发表时间: 2023-06
• 作者: Rafiq, Riyad Bin;Karim, Syed Araib;Albert, Mark V
• 通讯作者: Albert, Mark V