Modeling and Comprehension of Human Movements: Personal Digital Bodyguards for e-Security, e-Health and e-Learning

愿景：在五年内，手持平板电脑和手机的普及，沿着增加的计算能力和符合人体工程学的数据捕获性能，将使这些设备转化为个性化数字保镖（PDB）成为可能。PDB将通过签名验证保护人们的敏感数据，通过作家身份验证（电子安全）提供设备使用安全，并执行单词识别以监测用户的精细运动控制，这可以检测压力，老化和健康问题（电子健康）。在孩子的手中，这些工具将帮助他们学习和掌握他们的优良motricity，成为更好的作家和学生（电子学习）。 背景技术背景：我们的团队开发了快速人体运动的运动学理论及其对数正态模型，以解释人类运动控制的经典研究中报道的许多基本现象，并研究涉及精细运动的几个因素。多年来，我们已经创建了几个软件包，以在一系列实验条件下从各种笔尖速度曲线中提取对数正态参数。这些工具允许研究人员研究作家的神经肌肉系统的状态。 基本假设：神经肌肉脉冲响应的对数正态性是反映完全控制其运动的人的行为的基本特征。作为一个必然的结果，运动控制学习可以被解释为一种向完美掌握的运动的理想表示的迁移。反过来，衰老和健康问题应该揭示出逐渐偏离对数正态性。在这两个渐进过程之间，人类一生的大部分时间都利用对数正态性来控制他们的运动。 目标：本研究计划侧重于三个具体目标： 1.理论：利用定量磁共振成像（qMRI）为运动学理论提供了新的实验支持，并对如何使用对数正态性原理提出了独到的见解。 2.技巧：定义、实施和测试一个人体工程学研究平台，该平台利用新的输入设备进行手写采集，在云环境中的服务器上运行强大的算法，以及图形处理单元来研究对数正态性。 3.电子申请：通过与世界各地的领先专家合作定义新的评估指标，利用、扩展和传播我们在生物统计（电子安全）、生物医学（电子健康）和神经认知（电子学习）工程中创新电子应用的对数正态性知识。 预期影响：以及培训许多博士后研究员和博士生，整个计划将导致神经运动建模的重大理论突破，为我们设计高效的PDB奠定基础，将个人安全和保护选择放在人们手中，以实现更好的电子社会。

VISION: In five years, the ubiquity of hand-held tablets and cell phones, along with their increased computing power and ergonomic data capture performances, will make it possible to convert these devices into Personalized Digital Bodyguards (PDBs). PDBs will protect people’s sensitive data with signature verification, provide equipment use security with writer authentication (e-security) and perform word spotting to monitor user fine motor control, which can detect stress, aging and health problems (e-health). In the hands of children, these tools will help them to learn and master their fine motricity and become better writers and students (e-learning). BACKGROUND: Our team developed the kinematic theory of rapid human movements and its lognormal models ¸¸ to explain many basic phenomena reported in classical studies on human motor control and to study several factors involved in fine motricity. We have created several software packages over the years to extract the lognormal parameters from various pen tip velocity curves under a range of experimental conditions. These tools allow a researcher to study the state of a writer’s neuromuscular system. BASIC HYPOTHESIS: the lognormality of the neuromuscular impulse response is a basic feature reflecting the behaviour of people who are in perfect control of their movements. As a corollary, motor control learning can be interpreted as a migration toward an ideal representation of perfectly mastered movements. In turn, aging and health problems should reveal a progressive departure from lognormality. In between these two progressive processes, for most of their lives, humans take advantage of lognormality to control their movements. GOALS: This research program focuses on three specific goals: 1. Theory: Provide new experimental support to the kinematic theory using quantitative Magnetic Resonance Imaging (qMRI), and propose original ideas for ways to use the lognormality principle. 2. Technique: Define, implement and test an ergonomic research platform that takes advantage of new input devices for handwriting acquisition, powerful algorithms working on a server in a cloud environment, and Graphic Processing Units to investigate lognormality. 3. E-application: Exploit, expand and disseminate our know-how about lognormality for innovative e-applications in biometrical (e-security), biomedical (e-health) and neurocognitive (e-learning) engineering by defining new evaluation metrics in collaboration with leading experts all over the world. EXPECTED IMPACT: As well as training many post-doc fellows and Ph.D students, the whole program will lead to major theoretical breakthroughs in neuromotor modeling, setting the stage for us to design efficient PDBs that will put individual security and protection choices in people’s hands for a better e-society.