Medical Biometrics Enabled Affective Computing (MBEAC)

医学生物识别支持情感计算 (MBEAC)

• 批准号: RGPIN-2017-06099
• 负责人: Hatzinakos, Dimitrios
• 金额: $ 2.4万
• 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: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=637490
• 关键词: Medical; Biometrics; Enabled; Affective; Computing

Affective Computing is the associated field that focuses on the study and development of systems that can recognize, interpret, process and simulate human emotion. Medical biometrics denote physiological signals such as heart signatures, electrodermal responses of the skin and breathing rate, among others. The goal of the proposed work is to research methodologies for affective computing using medical biometrics with potential applications in healthcare for assessment of mental health, behavioral analysis in shopping and advertisement, detection of motivational characteristics in entertainment or education, among others. In the proposed work, human emotional states will be modeled, detected and classified using machine learning technology. Using information that results from biological responses, the most intimate expressions of emotions, the applicant and his team at the University of Toronto will research and develop algorithms that uncover hidden patterns of emotional behavior. For the first time, wearable technology will be used to measure bioresponses continuously in real-world settings. To date, the lack of a database of appropriate signals has limited any systematic development of emotion recognition technologies. Therefore, major objectives of the proposed research are: i) the investigation and development of pattern recognition algorithms suitable to characterize human emotions and be relevant to both military and non-military environments, and ii) the compilation of a suitable-scale database of emotionally-labeled physiological signals that is suitable for the evaluation of affective computing algorithms. The database will be made publicly available and it is expected that it will be endorsed by scientific teams performing research in the field of human emotion classification.

情感计算是一个相关领域，专注于研究和开发能够识别、解释、处理和模拟人类情感的系统。医学生物识别技术表示生理信号，例如心脏特征、皮肤电反应和呼吸频率等。拟议工作的目标是研究使用医学生物识别技术进行情感计算的方法，以及在医疗保健领域的潜在应用，以评估心理健康、购物和广告中的行为分析、娱乐或教育中的动机特征检测等。在拟议的工作中，将使用机器学习技术对人类情绪状态进行建模、检测和分类。申请人和他在多伦多大学的团队将利用生物反应产生的信息（最亲密的情绪表达）研究和开发算法，以揭示隐藏的情绪行为模式。可穿戴技术将首次用于在现实环境中连续测量生物反应。迄今为止，缺乏适当信号的数据库限制了情绪识别技术的系统发展。因此，本研究的主要目标是：i）研究和开发适合表征人类情感并与军事和非军事环境相关的模式识别算法，以及ii）编制适合评估情感计算算法的情感标记生理信号的适当规模的数据库。该数据库将公开，预计将得到在人类情感分类领域进行研究的科学团队的认可。