Developing an Objective and Quantifiable Measure of Itch Using Artificial Intelligence and Radio Signals

使用人工智能和无线电信号开发客观且可量化的瘙痒测量方法

• 批准号: 10683931
• 负责人: Dina Katabi
• 金额: $ 26.22万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10683931
• 关键词: Address; Adherence; Affect; Artificial Intelligence; Behavior; Body part; Breathing; Child; Circadian Rhythms; Clinic; Clinical; Clinical Research; Clinical Trials; Collaborations; Communities; Data; Development; Devices; Disease; Disease Management; Environment; Expenditure; FDA approved; Future; Gait; Head; Heart Rate; Home; Human; Impaired cognition; Life; Longitudinal Studies; Machine Learning; Measures; Methods; Monitor; Morbidity - disease rate; Motion; Neural Network Simulation; Observational Study; Outcome Assessment; Patient Self-Report; Patients; Perception; Performance; Persons; Polysomnography; Population; Privacy; Property; Pruritus; Quality of life; Radio; Reaction; Research; Respiration; Self Assessment; Severities; Signal Transduction; Sleep; Sleep Stages; Sleep disturbances; Specificity; Testing; Therapeutic; Time; Vulnerable Populations; Wrist; actigraphy; awake; chronic itch; chronic pain; drug development; falls; improved; invention; machine learning model; novel; novel therapeutics; prospective; sensor; sensor technology; skin irritation; sleep onset; sleep quality; standard of care; success; wireless electronic; wireless fidelity; wireless sensor

PROJECT SUMMARY Chronic itch affects 13% of the population and is associated with over $90 billion in annual population- expenditures in the US. It has a profound negative impact on quality of life, and is often as debilitating as chronic pain. Yet, there are currently no FDA-approved treatments for chronic itch. A major obstacle in assessing therapeutics for itch is the difficulty in measuring it, which hinders assessment of outcomes in the clinic and the development of new drugs. The current clinical standard for quantifying itch relies on patients’ self-assessment of the severity of their itch on a scale of 0 to 10, which is: 1) highly subjective and hard to generalize across patients, 2) lacks sensitivity to small changes, and 3) is difficult to use in vulnerable populations such as children and those with cognitive impairment. Thus, clinical research on itch has an urgent need for a new objective, accurate, and low overhead method for quantifying itch. Furthermore, given that disturbed sleep is a major factor leading to diminished quality of life for chronic itch patients, the new method should ideally also assess sleep quality. The overall objective of our proposal is to provide an objective, sensitive, and reliable metric for measuring both itch and its impact on sleep. The central hypothesis of this proposal is that a novel, wireless sensor can be employed to effectively capture scratching activity and associated itch morbidity, and also measure its impact on sleep. Our approach is based on a non-obtrusive wireless device that sits in the background at home, much like a Wi-Fi router. It analyses the radio signals that bounce off people's bodies using novel machine learning models to infer people’s sleep quality and scratching motion -- and it does it in a touchless manner without asking patients to wear sensors, or incur any burden. The Katabi lab invented this sensor technology and has already demonstrated its ability to measure sleep stages, respiration signal, heart rate, falls, gait and other behaviors in humans. Further, the Katabi and Kim labs have preliminary data that demonstrate the feasibility of extending this method to monitor scratching in a touchless manner in chronic itch patients. The specific aims of this proposal will assess the accuracy, sensitivity, and specificity of this novel method in measuring nocturnal scratching in chronic itch patients, its performance in comparison to the current clinical standard based on patients’ self-assessment of their condition, and its ability to track changes over time in the same patient. It will also leverage the device’s ability to monitor sleep to assess the impact of itch on patients’ sleep quality, and the relationship between sleep metrics (e.g., sleep onset, sleep efficiency, and sleep stages) and scratching severity. The rationale for this proposal is that the ability to quantify itch and its impact on sleep in an objective, sensitive method that is widely applicable, including to children and cognitively impaired patients, would improve clinical research, and facilitate the assessment of therapeutics for both disease management and drug development.

项目概要 慢性瘙痒影响 13% 的人口，每年与超过 900 亿美元的人口相关 它对美国的生活质量产生深远的负面影响，并且往往与慢性病一样令人衰弱。 然而，目前还没有 FDA 批准的慢性瘙痒治疗方法。 瘙痒治疗的难点在于测量瘙痒，这阻碍了临床和临床结果的评估 新药的开发目前量化瘙痒的临床标准依赖于患者的自我评估。 瘙痒的严重程度从 0 到 10 分，即： 1) 高度主观且难以一概而论 患者，2）对微小变化缺乏敏感性，3）难以在儿童等弱势群体中使用 因此，瘙痒的临床研究迫切需要一个新的目标， 准确且低开销的量化瘙痒的方法此外，考虑到睡眠障碍是一个主要因素。 导致慢性瘙痒患者生活质量下降，新方法理想情况下还应该评估睡眠 我们提案的总体目标是提供客观、敏感且可靠的衡量标准。 测量瘙痒及其对睡眠的影响该提案的中心假设是一种新颖的无线技术。 传感器可用于有效捕获抓挠活动和相关的瘙痒发病率，并且 我们的方法是基于位于房间内的非干扰性无线设备。 家中的背景，就像 Wi-Fi 路由器一样，它会分析从人们身体反射回来的无线电信号。 新颖的机器学习模型可以推断人们的睡眠质量和抓挠动作——而且是在非接触式的情况下完成的 Katabi 实验室发明了这种传感器，无需患者佩戴传感器，也不会造成任何负担。 技术，并且已经展示了其测量睡眠阶段、呼吸信号、心率、跌倒、 此外，卡塔比和金实验室的初步数据证明了人类的步态和其他行为。 扩展这种方法以非接触式方式监测慢性瘙痒患者的抓挠的可行性。 该提案的具体目标将评估这种新方法的准确性、敏感性和特异性 测量慢性瘙痒患者的夜间抓挠情况，与目前临床表现进行比较 标准基于患者对其病情的自我评估，以及跟踪病情随时间变化的能力 它还将利用该设备监测睡眠的能力来评估瘙痒对患者的影响。 睡眠质量以及睡眠指标之间的关系（例如睡眠开始时间、睡眠效率和睡眠阶段） 该提案的基本原理是量化瘙痒及其对睡眠的影响。 采用客观、敏感且广泛适用的方法，包括儿童和认知障碍患者， 将改善临床研究，并促进疾病管理和治疗的评估 药物开发。