CAREER: Synergy-based Human Machine Interfaces

凭借脑控外骨骼，一名脊髓损伤患者为2014年巴西世界杯进行了象征性的开球表演。人机界面不仅成为流行的技术，而且成为许多人恢复失去的肢体功能的希望。几十年的研究使人与机器之间的界面变得无缝，但科学家们无法有效地解决内在的挑战，即复杂性、适应性和变异性。为了克服上述挑战，从计算上理解和定量描述人类如何控制他们的感官和运动能力是至关重要的。仿生模型可以帮助理解这一过程，并可以实现对机器的有效控制。人类的手有许多维度，是了解与计算机和其他机器交互时的感觉运动控制的理想试验台。因此，这个项目的目标是设计和开发控制人类手的仿生模型，并将这些模型扩展到控制多维机器。拟议项目的社会影响将是为残疾人开发功能接近自然的假肢的新设计。该项目的教育和推广影响将为学生和在职工程师创造机会，让他们了解人机界面的重要性。该项目将为学生提供有指导的国际研究和教育机会。作为拟议研究的成果而开发的动手模块将点燃各级学生，特别是女性和代表性不足的少数民族对科学和技术的兴趣。中枢神经系统如何毫不费力地控制高维人类的手仍然是一个未解的谜。为了解决这一高维控制问题，人们提出了许多仿生电机控制模型，其中一种是基于协同效应的。根据这个模型，中枢神经系统不是控制单个运动单位，而是通过称为协同作用的运动单位组的协调控制来简化控制。然而，今天有几个问题没有得到回答。协同效应存在于哪里？它们在运动控制和运动学习中扮演什么角色？为了回答这些根本问题，本项目采取了整体和综合的方法。它将人类运动控制、计算神经科学、机器学习和验证的概念与非侵入性人体实验相结合。该项目的研究目标是：模拟人类手部运动中协同效应的产生，并使用计算模型、脑电和经颅磁刺激通过非侵入性人体实验验证模型，模拟协同效应在运动学习中的行为和作用，并将这些协同效应应用于多维机器控制和机器辅助学习。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

With a brain controlled exoskeleton, an individual with spinal cord injury performed a symbolic-kickoff of for the World Cup in Brazil in 2014. Human-machine interfaces have not only become popular technologies but have become the hope of many individuals for restoring their lost limb function. Decades of research went into making the interface between the human and the machine seamless, but scientists were unable to effectively address the inherent challenges, namely, complexity, adaptability and variability. To overcome the above challenges, it is critical to computationally understand and quantitatively characterize how humans control their senses and motor abilities. Biomimetically inspired models can help to understand this process, and can enable efficient control of the machine. The human hand has many dimensions and is an ideal testbed to understand sensorimotor control while interacting with computers and other machines. Hence the goal of this project is to design and develop biomimetic models that control the human hand and extend these models to the control of multidimensional machines. The societal impacts of the proposed project will be the development of new designs of artificial limbs for individuals with disabilities that are as close to natural in their functions. The educational and outreach impacts of the project will create opportunities for students and working engineers to learn the importance of human machine interfaces. The project will facilitate mentored international research and educational opportunities for students. The hands-on modules developed as an outflow of the proposed research will ignite interest in science and technology among students at all levels, particularly women and underrepresented minorities.The means by which the central nervous system effortlessly controls the high dimensional human hand is still an unsolved mystery. To address this high dimensional control problem, many bioinspired motor control models have been proposed, one of which is based on synergies. According to this model, instead of controlling individual motor units, central nervous system simplifies the control using coordinated control of groups of motor units called synergies. However, there are several unanswered questions today. Where are synergies present? What is their role in motor control and motor learning? To answer these fundamental questions, this project takes a holistic and comprehensive approach. It combines the concepts of human motor control, computational neuroscience, machine learning and validation with noninvasive human experiments. The research objectives of this project are: to model the generation of synergies in human hand movements and validate the model with noninvasive human experiments using computational models, electroencephalography and transcranial magnetic stimulation, to model the behavior and the role of synergies in motor learning and to apply these synergies in multidimensional machine control and machine-assisted learning.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.