Collaborative Research: SCH: Psychophysiological sensing to enhance mindfulness-based interventions for self-regulation of opioid cravings

合作研究：SCH：心理生理学传感，以增强基于正念的干预措施，以自我调节阿片类药物的渴望

• 批准号: 2320678
• 负责人: Tauhidur Rahman
• 金额: $ 33.75万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2320678&HistoricalAwards=false
• 关键词: Collaborative; Research; SCH; Psychophysiological; sensing

Opioid use disorder (OUD) is a chronic condition and a leading public health problem in the U.S. The risk of overdose is particularly high following a period of abstinence leading to drug-related deaths. OUD includes physical dependency and neural adaptations in brain circuits of reward and motivation, self-regulation, and stress reactivity that can persist years after drug discontinuation. Substance craving is one of the primary causes of OUD patient's relapse. Studies have shown psychological cues such as stress, anxiety, and arousal can precipitate the cultivation of drug craving. Research has found that mindfulness-based strategies reduce cravings, psychological cues and prevent relapse. Mindfulness-based interventions (MBIs) bring about clinically relevant changes to physiological arousal, stress, and addictive behavior through cognitive behavioral skill development. This project focuses on developing and testing innovative technologies to aid sustainable recovery of OUD with wearable and in-home physiological monitoring and generation of adaptive, personalized, and just-in-time MBIs. While the research is focused on OUD, the principle and the outcomes can be expanded to include other substance use disorders. The project includes several education and outreach activities such as machine learning course for medical professionals and annual workshops for middle school girls.This study focuses on opioid use disorder (OUD), related cognition, and behaviors associated with a) reward, b) self-regulation, c) stress reactivity, d) opioid craving, e) physical opioid withdrawal symptoms and MBIs known to be impacted by OUD and post-acute withdrawal from opioids. In particular, the research tasks focus on there areas. First, effective physiological feature identification and extraction to detect craving that is generalizable across large OUD populations and consider the external factors such as age, gender, drug use habits, etc. Second, development of an effective multi-modal sensing integration approach to capture psychological craving cues (e.g., stress, arousal) from a combination of acoustic and physiological sensing. This will include novel multiple instance (MIL) multitask learning based classification techniques that are scalable with near real-time performance. The study will address the fundamental gaps of indoor craving-relevant sensing where only a small fraction of a long signal may convey information relevant to the targeted emotional state/class. The last task will include development of a craving context-aware MBI recommender system that models the dynamic nature of OUD subjects craving-interventions and feedbacks. The system will be formally validated to ensure safety against adverse outcomes. Successful execution of the research will begin to test the effectiveness of integrating passive sensing, adaptive artificial intelligence (AI), and mindfulness interventions on regulating drug craving.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.

阿片类药物使用障碍（OUD）是一种慢性疾病，也是美国的一个主要公共卫生问题。在一段时间的禁欲后，过量用药的风险特别高，导致与药物有关的死亡。OUD包括身体依赖和大脑回路中的奖励和动机，自我调节和压力反应的神经适应，这些适应在停药后持续数年。物质渴求是OUD患者复发的主要原因之一。研究表明，心理暗示，如压力，焦虑和觉醒可以促进药物渴望的培养。研究发现，基于正念的策略可以减少渴望，心理暗示并防止复发。基于正念的干预（MBIs）通过认知行为技能的发展，为生理唤醒，压力和成瘾行为带来临床相关的变化。该项目的重点是开发和测试创新技术，通过可穿戴和家庭生理监测以及自适应，个性化和即时MBI的生成来帮助OUD的可持续恢复。虽然研究的重点是OUD，但其原理和结果可以扩展到包括其他物质使用障碍。该项目包括几个教育和推广活动，如医疗专业人员的机器学习课程和中学女生的年度研讨会。这项研究的重点是阿片类药物使用障碍（OUD），相关认知，以及与a）奖励，B）自我调节，c）压力反应，d）阿片类药物渴望，e）已知受OUD和阿片类药物急性戒断后影响的身体阿片类药物戒断症状和MBI。特别是，研究任务集中在这些领域。第一，有效的生理特征识别和提取，以检测可在大OUD人群中推广的渴望，并考虑外部因素，如年龄，性别，吸毒习惯等。第二，开发有效的多模态传感集成方法，以捕获心理渴望线索（例如，压力、唤醒）。这将包括新的多实例（MIL）多任务学习分类技术，可扩展的近实时性能。该研究将解决室内渴望相关感测的基本差距，其中只有一小部分长信号可以传达与目标情绪状态/类相关的信息。最后一项任务将包括开发一个渴望上下文感知MBI推荐系统，该系统模拟了OUD受试者渴望干预和反馈的动态性质。该系统将得到正式验证，以确保安全性，防止不良后果。该研究的成功执行将开始测试整合被动感知、自适应人工智能（AI）和正念干预对调节药物渴望的有效性。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

项目成果

"Reading Between the Heat": Co-Teaching Body Thermal Signatures for Non-intrusive Stress Detection

“阅读热之间”：共同教授用于非侵入式压力检测的身体热特征

• 发表时间: 2023
• 期刊: Wearable and Ubiquitous Technologies
• 作者: Yi Xiao, Harshit Sharma

Building MechanoBeat: Instrumenting Mechanical "Heartbeats" on Everyday Objects for User Interaction

构建 MechanoBeat：在日常物体上检测机械“心跳”以进行用户交互

• DOI: 10.1145/3583571.3583573
• 发表时间: 2023
• 期刊: GetMobile: Mobile Computing and Communications
• 作者: Oshim, Md. Farhan;Killingback, Julian;Follette, Dave;Peng, Huaishu;Rahman, Tauhidur
• 通讯作者: Rahman, Tauhidur

Towards Accurate and Scalable Mental Health Screening Technologies for Young Children

• DOI: 10.1145/3594739.3610763
• 发表时间: 2023-10
• 期刊: Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing
• 作者: Manasa Kalanadhabhatta;Deepak Ganesan;Tauhidur Rahman

Neuromorphic High-Frequency 3D Dancing Pose Estimation in Dynamic Environment

• DOI: 10.1016/j.neucom.2023.126388
• 发表时间: 2023-01
• 期刊: Neurocomputing
• 影响因子: 6
• 作者: Zhongyang Zhang;Kaidong Chai;Haowen Yu;Ramzi M Majaj;Francesca Walsh;Edward Wang;U. Mahbub;H. Siegelmann;Donghyun Kim-;Tauhidur Rahman

Temporally Layered Architecture for Adaptive, Distributed and Continuous Control

用于自适应、分布式和连续控制的时间分层架构

• 发表时间: 2023
• 期刊: AAMAS '23: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems
• 作者: Patel, Devdhar;Russell, Joshua;Walsh, Francesca;Rahman, Tauhidur;Sejnowski, Terrence;Siegelmann, Hava
• 通讯作者: Siegelmann, Hava