HAL: A TOOL FOR ASSESSING HUMAN ACTION IN THE WORKPLACE

HAL：评估工作场所人类行为的工具

• 批准号: 7666930
• 负责人: JOHN YIANNIS ALOIMONOS
• 金额: $ 29.07万
• 依托单位: UNIV OF MARYLAND, COLLEGE PARK
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-26 至 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7666930
• 关键词: Activities of Daily Living; Affect; Arts; Autistic Disorder; Behavior; Behavioral; Behavioral Sciences; Characteristics; Child; Cognitive; Computers; Data; Development; Developmental Coordination Disorders; Diagnostic; Disadvantaged; Discipline; Early Diagnosis; Elderly; Environment; Evolution; Gestures; Goals; Home environment; Human; Human Activities; Human Development; Individual; Infant; Institutes; Interdisciplinary Study; Intervention; Language; Learning; Linguistics; Literature; Magnetism; Measurement; Measures; Mental disorders; Motion; Motor; Movement; Movement Disorders; National Institute of Child Health and Human Development; National Institute of Mental Health; Nature; Nervous System Physiology; Nervous system structure; Neurologic; Neurosciences; Occupational Therapist; Parkinson Disease; Pattern; Population; Population Control; Production; Request for Applications; Research; Schools; Scientist; Semantics; Series; Social Interaction; Software Tools; Specialist; Structure; System; Techniques; United States National Institutes of Health; Wireless Technology; Work; Workplace; base; brain behavior; cost; data mining; innovation; motor control; novel; portability; sensor; social communication; syntax; tool

DESCRIPTION (provided by applicant): Human movement has been a large window into the functioning of the nervous system. Behavioral scientists have had major accomplishments, such as documenting movement milestones in human development and establishing a relationship between brain and behavior in typical and atypical populations. These measurements are performed today with a cornucopia of sophisticated techniques, ranging from infrared and video to wireless sensor networks. However, despite the tremendous progress on measuring human movement, we still don't fully understand, for example, motor decline in elderly people or Parkinson's disease during daily living activities at home and the workplace; or how atypical social interaction in autism or developmental coordination disorder are manifested in body gestures. Why can't we yet deal with problems of such nature? It is clear that the problems mentioned above have characteristics that are beyond the state of the art or any single discipline. Thus, we propose a novel, interdisciplinary, and multi-level motion understanding tool to extract multi-scaled, nested representations of transitive and intransitive actions and communicative actions at different levels of abstraction at the "individual" and "workgroup" levels. Our specific aim is to develop a Human Action Language (HAL) tool, a tool for describing and understanding human actions. The underlying premise is that the space of human actions is characterized by a language; this new language has its own phonemes (primitives), its own morphemes (words/actions) and its own syntax, semantics and pragmatics. Although previous research has concentrated on finding primitives in very often isolated types of human action, the innovation here is the use of large amounts of human motion data in ecologically valid settings and in conjunction with modern data mining and grammatical induction techniques. To validate the HAL tool, we will apply it to assess atypical movement in Developmental Coordination Disorder (DCD) and Parkinson's disease (PD). Specifically, we propose to extract the DCD grammar and the PD grammar and compare them with the grammars from the control populations, investigating relationships between the corresponding grammars at the individual and workgroup levels. Our interdisciplinary team consists of a computational scientist, a behavioral scientist (motor development) , and a computational neuroscientist (motor control and learning). The proposed tool will extend the scope of behavioral sciences (grounding of language, imitation, and gesture-based social communication) and facilitate interdisciplinary research bringing together movement disorders specialists, behavioral scientists, physical or occupational therapists and computer scientists. Several NIH Institutes would benefit from the availability of such a tool, including NIA/NINDS, NIMH and NICHD. The ultimate goal is to better understand human action production and understanding, and to develop optimal diagnostic and intervention tools for populations with atypical movement patterns. The proposed tool will extend the scope of behavioral sciences (grounding of language, imitation, and gesture- based social communication) and facilitate interdisciplinary research bringing together movement disorders specialists, behavioral scientists, physical or occupational therapists and computer scientists. Several NIH Institutes would benefit from the availability of such a tool, including NIA/NINDS - for understanding motor decline in the elderly and neurological populations in single and group-based daily living activities, NIMH - for understanding stereotypical behaviors in populations affected with mental disorders, and NICHD - for understanding developmental aspects of cognitive motor behavior in children at school or home. The ultimate goal is to better understand human action production and understanding, and developing optimal diagnostic and intervention tools for populations with atypical movement patterns.

描述（由申请人提供）：人类运动是研究神经系统功能的一个重要窗口。行为科学家已经取得了重大成就，例如记录了人类发展中的运动里程碑，并在典型和非典型人群中建立了大脑和行为之间的关系。如今，这些测量使用了丰富的复杂技术，从红外和视频到无线传感器网络。然而，尽管在测量人类运动方面取得了巨大的进步，我们仍然不能完全理解，例如，老年人的运动能力下降或帕金森病在家庭和工作场所的日常生活活动中；或者自闭症或发育性协调障碍的非典型社会互动如何表现在肢体动作上。为什么我们还不能处理这种性质的问题？很明显，上面提到的问题具有超越技术水平或任何单一学科的特征。因此，我们提出了一种新颖的、跨学科的、多层次的动作理解工具，用于在“个人”和“工作组”的不同抽象层次上提取及物和不及物动作和交流动作的多尺度、嵌套表示。我们的具体目标是开发一个人类行为语言（HAL）工具，一个描述和理解人类行为的工具。其基本前提是人类活动的空间以语言为特征；这种新语言有它自己的音素（原语），它自己的语素（词/动作），它自己的语法，语义和语用学。虽然以前的研究集中在寻找非常孤立的人类行为类型的原语，但这里的创新是在生态有效的环境中使用大量的人类运动数据，并与现代数据挖掘和语法归纳技术相结合。为了验证HAL工具，我们将应用它来评估发育协调障碍（DCD）和帕金森病（PD）的非典型运动。具体来说，我们建议提取DCD语法和PD语法，并将它们与对照群体的语法进行比较，研究个人和工作组层面上相应语法之间的关系。我们的跨学科团队由一名计算科学家、一名行为科学家（运动发展）和一名计算神经科学家（运动控制和学习）组成。提议的工具将扩展行为科学的范围（语言、模仿和基于手势的社会交流的基础），并促进跨学科的研究，将运动障碍专家、行为科学家、物理或职业治疗师和计算机科学家聚集在一起。美国国立卫生研究院的几个研究所将受益于这种工具的可用性，包括NIA/NINDS、NIMH和NICHD。最终目标是更好地了解人类行为的产生和理解，并为具有非典型运动模式的人群开发最佳诊断和干预工具。提议的工具将扩展行为科学的范围（语言、模仿和基于手势的社会交流的基础），并促进跨学科的研究，将运动障碍专家、行为科学家、物理或职业治疗师和计算机科学家聚集在一起。NIH的几个研究所将受益于这种工具的可用性，包括NIA/NINDS——用于了解老年人和神经系统人群在单个和群体日常生活活动中的运动衰退，NIMH——用于了解受精神障碍影响人群的刻板行为，以及NICHD——用于了解儿童在学校或家庭中的认知运动行为的发展方面。最终目标是更好地理解人类行为的产生和理解，并为具有非典型运动模式的人群开发最佳诊断和干预工具。

项目成果

Sensory grammars for sensor networks.

传感器网络的感觉语法。

• DOI: 10.3233/ais-2009-0002
• 发表时间: 2009
• 期刊: Journal of ambient intelligence and smart environments
• 影响因子: 1.7
• 作者: Aloimonos,Yiannis

Active Segmentation.

• DOI: 10.1142/s0219843609001784
• 发表时间: 2009
• 期刊: International journal of HR : humanoid robotics
• 作者: Mishra A;Aloimonos Y
• 通讯作者: Aloimonos Y

Parkinson's disease differentially affects adaptation to gradual as compared to sudden visuomotor distortions.

• DOI: 10.1016/j.humov.2010.08.020
• 发表时间: 2011-08
• 期刊: HUMAN MOVEMENT SCIENCE
• 影响因子: 2.1
• 作者: Venkatakrishnan, Anusha;Banquet, Jean P.;Burnod, Yves;Contreras-vidal, Jose L.
• 通讯作者: Contreras-vidal, Jose L.