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.

项目总结