MRI: Development of an Instrument that Monitors Behaviors Associated with Obsessive-Compulsive Behaviors and Schizophrenia
MRI: Development of an Instrument that Monitors Behaviors Associated with Obsessive-Compulsive Behaviors and Schizophrenia
批准号:
1338042
负责人:
Nikolaos Papanikolopoulos
金额:
$55.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-10-01 至 2022-09-30
中文摘要
提案#:13-38042PI(S):Papanikolopoulos,Nikolaos Banerjee,Arindam;Bernstein,Gail;Hadjiyanni,Tassoulla;Lim,Kelvin,K.机构:明尼苏达大学双子城分校标题:磁共振/开发:监测与强迫症和精神分裂症相关的行为的仪器建议:该项目开发了一种新的工具,以促进与强迫症等复杂精神健康障碍临床评估相关的数据收集,旨在使计算机视觉、活动识别和三维重建算法方面的长期研究进展,以自动识别强迫症受试者的典型行为。选定对象在虚拟现实房间(洞穴)中的沉浸被用来触发要捕获和分析的特定行为。正在开发的复杂传感器系统将用于收集这些数据,并提供智能数据处理能力,使今后能够探索和测试新的诊断和治疗方案,从而为寻找儿童和青少年早期危险标记奠定基础并加以利用。该仪器计划基于这样的前提,即专业知识可以准确地识别有用的诊断标记,并且相信现在可以开发技术来以以前未完成的方式收集大量行为数据并发现行为模式。预期该仪器将提供与被诊断为相应疾病的受试者相关的广泛数据收集(数据不仅对临床医生有用,而且对计算机视觉和机器学习研究人员等有用),-捕获对真实和/或合成多模式刺激(光学、声学等)的交互、行为和生理反应,-允许计算机和信息科学家开发计算工具和算法来产生定量的、适当的、-通过整合可刺激或抑制精神分裂症或强迫症发作的技术来增强认知行为疗法(CBT)的程序和诊断协议,-评估特定的增强和虚拟环境(AE/VE)和社交媒体设备(智能手机和平板电脑)及其对正常和受影响受试者的认知存在的影响,以及-评估通过AE/VE增强的认知存在是否可以增加或抑制(习惯)传感器可检测到的行为症状的强度。更广泛的影响:我们有:-创建大型和复杂的数据集,使计算机科学家能够对它们应用最新的计算工具,开发一种潜在的变革性技术驱动的工具来检测强迫症的早期风险标记,-探索一个适合于更好地描述精神障碍的新方向的平台,-系统地开发量化的多模式数据和更可靠和更准确的更早检测的基础,-降低总体成本,并并行地减少由于先前延迟或错误的诊断而造成的长期成本,-减少焦虑、干扰、压力,有时还减少患者及其家人的真正悲剧,-更早地发现并减少对基于药物的后期干预的需要,这是由于易于测试以及相关的社会益处,以及-学生在使用该仪器方面的教育和培训。
英文摘要
Proposal #: 13-38042PI(s): Papanikolopoulos, Nikolaos Banerjee, Arindam; Bernstein, Gail; Hadjiyanni, Tassoulla; Lim, Kelvin, K.Institution: University of Minnesota-Twin CitiesTitle: MRI/Dev.: Instrument that Monitors Behaviors Associated with OCD and Schizophrenia Project Proposed:This project, developing a new instrument to facilitate data collection associated with clinical assessment of complex mental health disorders such as obsessive-compulsive behaviors (known as OCD), aims to enable long-term research advances in computer vision, activity recognition and tridimensional reconstruction algorithms to automate the identification of behaviors typical of OCD subjects. The immersion of selected subjects in a virtual reality room (CAVE) is used to trigger specific behaviors to be captured and analyzed. The sophisticated sensor system under development will serve to collect these data and provide intelligent data processing capabilities that would enable future exploration and testing of new diagnostic and therapeutic protocols, leading to the establishment of the basis for, and utility in, seeking early at-risk markers in children and adolescents. This instrument initiative is based on the premise that expertise can accurately identify useful diagnostic markers and on the belief that technologies can now be developed to collect massive behavioral data in ways not previously done and discover behavioral patterns.The instrument is expected to- Provide extensive data collection associated with subjects diagnosed with the respective disorders (data useful not only to clinicians but also to computer vision and machine learning researchers among others),- Capture interactions, behaviors, and physiological reactions to real and/or synthetic multimodal stimuli (optical, acoustical, etc.),- Allow computer and information scientists to develop computational tools and algorithms to generate quantitative, adequate, and cost-effective norms for screening a broad population, - Enhance Cognitive Behavior Therapy (CBT) procedures and diagnostic protocols by integration of technologies that can excite or inhibit triggers for schizophrenic or OCD episodes,- Assess particular Augmented and Virtual Environments (AE/VEs) and social media devices (smart phones and tablets) and their impacts on the cognitive presence of normal versus afflicted subjects, and- Evaluate whether an enhanced cognitive presence via an AE/VE can increase or suppress (habituate) the intensity of behavioral symptoms detectable by sensors. Broader Impacts: Among these we have:- Creation of large and complex datasets that will enable computer scientists to apply the newest computational tools on them,Development of a potentially transformative technology-driven instrument for detecting early risk markers of OCD,- Exploration of a platform well-suited to new directions for a better characterization of mental disorders,- Systematic database development of quantified, multimodal data and a sounder and more precise basis for earlier detection,- Reduction of overall costs and a parallelizing reduction in the long-term costs due to previously delayed or incorrect diagnoses,- Reduction of anxiety, disruption, stress, and sometimes real tragedy on patients and their families, - Earlier detection and reduced need for drug-based, later stage interventions enabled by the ease of testing, and associated societal benefits, and- Student education and training in the use of the instrument.
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