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无处不在，加上它们更强大的计算能力和符合人体工程学的数据捕获性能，将使这些设备转变为个性化数字保镖(PDB)成为可能。PDB将通过签名验证保护人们的敏感数据，通过写入者身份验证为设备使用提供安全(电子安全)，并执行单词识别以监控用户的精细运动控制，可以检测压力、老化和健康问题(电子健康)。在儿童手中，这些工具将帮助他们学习和掌握他们的精细运动，并成为更好的作家和学生(电子学习)。背景：我们团队发展了人体快速运动的运动学理论及其对数正态模型，以解释经典研究中关于人类运动控制的许多基本现象，并研究与精细运动有关的几个因素。多年来，我们已经开发了几个软件包，用于从各种笔尖速度曲线中提取各种实验条件下的对数正态参数。这些工具使研究人员能够研究作家神经肌肉系统的状态。基本假设：神经肌肉冲动反应的对数正态分布是反映完全控制自己动作的人的行为的基本特征。作为推论，运动控制学习可以被解释为向完美掌握的动作的理想表现的迁移。反过来，老龄化和健康问题应该逐渐背离对数正态分布。在这两个渐进的过程之间，人类一生中的大部分时间都在利用对数正态来控制自己的动作。*目标：本研究计划专注于三个具体目标：*1.理论：使用定量磁共振成像(QMRI)为运动学理论提供新的实验支持，并为如何使用对数正态原理提出原创性想法。*2.技术：定义、实现和测试人体工学研究平台，该平台利用新的输入设备进行手写学习，强大的算法在云环境中的服务器上工作，和图形处理单位调查对数正态。*3.电子应用：通过与世界各地的领先专家合作定义新的评估指标，开发、扩展和传播我们在生物测定(e-安全)、生物医学(e-Health)和神经认知(e-Learning)工程中创新的e-应用的对数正态知识。*预期影响：除了培养许多博士后研究员和博士后，整个项目将导致神经运动建模方面的重大理论突破，为我们设计高效的PDB奠定了基础，这些PDB将把个人安全和保护选择交到人们手中，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.*********