Patient Monitoring Technologies for In-Situ Assessment of Emotional Processes In Naturalistic Settings

用于自然环境中情绪过程现场评估的患者监测技术

• 批准号: RGPIN-2015-05028
• 负责人: Kushki, Azadeh
• 金额: $ 1.31万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=708566
• 关键词: Patient; Monitoring; Technologies; Situ; Assessment

In-situ and ambulatory patient monitoring in naturalistic settings enables symptom observation outside controlled clinical settings, ultimately enhancing assessment and diagnostic processes. While a plethora of systems have been proposed for in-situ monitoring of physiological pathologies (e.g., cardiac abnormalities, seizures), technologies that monitor psychiatric- and mental health-related symptoms are scarce. These technologies can complement and enhance existing assessment methods which generally rely on highly subjective self- and care-giver reports. In this domain, monitoring of emotional processes is of specific interest as these processes play a key role in psychopathology (e.g., anxiety, depression, borderline personality disorder, bipolar disorders). The long-term objective of the proposed program is to develop intelligent, mobile, and wearable computing systems for continuous and in-situ monitoring of symptoms associated with psychiatric disorders as well as the related contextual factors. In this proposal, we will focus on emotion monitoring based on physiological signals as these variables can be non-invasively measured with wearable sensors in a variety of environments. Physiological change is also a key component of the emotional experience and atypical physiology has been associated with psychopathology. Existing systems for physiological monitoring of emotional processes have been developed and evaluated in highly controlled laboratory settings where emotional experiences are artificially induced. To allow the translation of these systems ambulatory and in-situ emotion monitoring in naturalistic settings, technical challenges related to modeling inter- and intra-personal variability as well as confounding affects of other cognitive and physical processes must be resolved. To address these gaps, the short-terms objectives of this program are to 1) develop algorithms for continuous estimation and adaptation of a time-varying physiological baseline, 2) develop classification algorithms for differentiating emotion-related physiological changes from those associated with cognitive and physical activity, and 3) develop a wearable and mobile system for continuous measurement and labeling of emotion-related physiological responses in real-life conditions. This research program will establish innovative new methods to advance emotion detection research from controlled laboratory settings to naturalistic environments. Ultimately, the outcomes of the proposed program can improve and enhance diagnosis and assessment of psychiatric and mental health disorders. The methods developed in this research program will be directly transferable to other application domains including affective computing and enriched human-computer interaction.

在自然环境中进行原位和动态患者监测，可以在受控临床环境之外进行症状观察，最终增强评估和诊断过程。虽然已经提出了过多的系统用于生理病理的原位监测（例如，心脏异常、癫痫发作），但监测精神病和心理健康相关症状的技术很少。这些技术可以补充和增强现有的评估方法，这些方法通常依赖于高度主观的自我和护理报告。在这一领域，对情绪过程的监测是特别感兴趣的，因为这些过程在精神病理学中起着关键作用（例如，焦虑、抑郁、边缘型人格障碍、双相情感障碍）。该计划的长期目标是开发智能的、移动的和可穿戴的计算系统，用于连续和原位监测与精神疾病相关的症状以及相关的背景因素。 在这项提案中，我们将专注于基于生理信号的情绪监测，因为这些变量可以在各种环境中用可穿戴传感器进行非侵入性测量。生理变化也是情绪体验的关键组成部分，非典型生理学与精神病理学有关。已经在高度受控的实验室环境中开发和评估了用于情绪过程的生理监测的现有系统，其中情绪体验是人工诱导的。为了使这些系统的翻译流动和原位的情绪监测在自然的设置，技术的挑战，相关的建模间和个人内的变化，以及其他认知和物理过程的混杂影响必须得到解决。为了解决这些差距，该计划的短期目标是：1）开发用于连续估计和适应时变生理基线的算法，2）开发用于区分与认知和身体活动相关的情绪相关生理变化的分类算法，以及3）开发可穿戴和移动的系统，用于在现实生活条件下连续测量和标记与情绪相关的生理反应。 该研究计划将建立创新的新方法，将情绪检测研究从受控实验室环境推进到自然环境。最终，拟议方案的结果可以改善和加强精神和心理健康疾病的诊断和评估。在这项研究计划中开发的方法将直接转移到其他应用领域，包括情感计算和丰富的人机交互。