STTR Phase I: Biomimetic Solution for Gesture-Based Human Machine Interactions

这个小企业技术转让（STTR）第一阶段项目的更广泛/商业机会是解决对直观人机界面的新兴需求。对虚拟和增强现实（VR/AR）技术的兴趣已经大幅增加，但是由于当前机器学习算法的限制，当前的VR/AR接口算法通常效率低下并且阻碍了许多基于手势的接口。这限制了新VR/AR技术的性能和广泛采用。这里开发的技术将实现与VR/AR的直观交互，这将大大扩展商业应用的范围，并缩短新产品的开发时间。 这个小企业技术转让（STTR）第一阶段项目将开发一种原型肌肉骨骼技术，用于从肌肉活动中解码运动。传统的基于机器学习的虚拟和增强现实（VR/AR）界面手势识别方法无法满足更自然和直观的交互需求，因为它只依赖于运动观察。 当前的手势识别技术通常不能推广到新颖的或扰动的运动。该项目的目标是开发一种后端技术，用于从肌肉活动中实时准确地解码预期的手臂和手部运动，从而克服这两个限制。这个项目将导致一个新的工具，连续实时计算机接口与多维手势或movement.This奖项反映了NSF的法定使命，并已被认为是值得的支持，通过评估使用基金会的智力价值和更广泛的影响审查标准。

The broader/commercial opportunity of this Small Business Technology Transfer (STTR) Phase I project is to address the emerging demand for intuitive human-machine interfaces. Interest in virtual and augmented reality (VR/AR) technologies has increased substantially, but current VR/AR interface algorithms are often inefficient and hamper many gesture-based interfaces, due to limitations in current machine learning algorithms. This limits the performance and widespread adoption of new VR/AR technologies. The technology developed here will enable intuitive interactions with VR/AR that will greatly expand the scope of commercial applications and shorten the development timelines for new products. This Small Business Technology Transfer (STTR) Phase I project will develop a prototype musculoskeletal technology for decoding movement from muscle activity. Traditional machine-learning-based gesture recognition approaches for virtual and augmented reality (VR/AR) interfaces cannot fulfill the demand for more natural and intuitive interactions, due to the reliance on only motion observation. Current gesture recognition technologies are often not generalizable to novel or perturbed movements. The goal of this project is to develop a backend technology for real-time and accurate decoding of intended arm and hand movement from muscle activity, which overcomes both of those limitations. This project will lead to a new tool for continuous real-time computer interface with multidimensional hand gestures or movements.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.