I-Corps: Integrated Wearable System for Management of Substance Use Disorder

I-Corps项目的更广泛影响/商业潜力是开发一种神经技术，可以改善物质使用障碍（SUD）和其他精神疾病（例如创伤后应激障碍和重度抑郁症）患者的生活质量。这种神经技术系统可以帮助个人控制多种精神疾病，以及疾病的严重程度，并提供对精神健康的持续监测。该技术旨在帮助患有SUD的个体以个性化的方式管理他们的心理健康，同时通过提供神经生理学和心理物理学数据来帮助临床医生进行远程预后和远程诊断。这种设备可以在家庭和医疗中心使用，作为数字健康的可穿戴设备，可以告诉临床医生关于SUD的管理和实时、现实世界条件下的最佳治疗方案。I-Corps项目的基础是开发一种集成的便携式神经技术，该技术能够使用可穿戴生物传感器管理物质使用障碍（SUD），包括皮电活动（EDA）和脑电图（EEG）传感器。该系统检测并调节压力，这是药物滥用的关键诱因。该系统将由四个主要部分组成：(1)基于有充分记录的压力对SUD的负面影响，使用EEG和EDA传感器检测压力和情绪状态；(2)机器学习（ML）和人工智能（AI）算法，用于改进对压力、情绪和行为的检测；(3)利用脑电图传感器测量、管理和修改大脑活动以及相关行为的神经反馈；(4)智能手机应用程序，可以提供用户友好和个性化的图形用户界面，以提供神经反馈。拟议的技术可以以直接和个性化的方式帮助患有SUD的个人。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is the development of a neurotechnology that could improve the quality of life for individuals with substance use disorder (SUD) and other mental illnesses (e.g. post-traumatic stress disorder and major depression). This neurotechnology system could help individuals manage multiple mental illnesses, as well as the severity of the illness and provide continuous monitoring of mental health. The technology aims to help individuals with SUD manage their mental health in a personal manner, and simultaneously help clinicians by providing neurophysiological and psychophysical data to assist tele-prognosis and telediagnosis. Such devices can be used in-home and in medical centers, and as a wearable device for digital health, could inform clinicians about the management of SUD and optimal treatment options in real-time, real-world conditions. This I-Corps project is based on the development of an integrated portable neurotechnology that is capable of management of substance use disorder (SUD) using wearable biosensors, including electrodermal activity (EDA) and electroencephalography (EEG) sensors. The system detects and modulates stress, a key trigger in substance abuse. This system will have four major components: (1) based on well documented negative effects of stress in SUD, detection of stress and emotional states recorded using EEG and EDA sensors; (2) machine-learning (ML) and artificial intelligence (AI) algorithms for improving the detection of stress, emotion and behavior; (3) neurofeedback using EEG sensors to measure, manage and modify brain activity and thus, associated behavior; and (4) a smartphone app that can provide a user-friendly and personalized graphical user interface for providing neurofeedback. The proposed technology could help individuals with SUD in an immediate and personal manner.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.