Conformable systems for spatiotemporal decoding of facial strains

许多神经肌肉疾病，如肌萎缩性侧索硬化症（ALS），通常表现为生理变化，包括逐渐丧失锻炼精细运动技能和发出清晰语音的能力。因此，持续跟踪面部动态皮肤张力的可预测方法可以为患有此类疾病的个体提供新的交流形式。目前面部变形的体内表征方法包括肌电图（EMG）、皮肤阻抗测量或相机跟踪。然而，这些通常导致高度不确定性或具有笨重的结构，与柔软的皮肤具有高度可见的界面，在日常生活中难以持续使用，特别是对于神经肌肉疾病患者。该研究的目的是实现可将面部软组织生物力学模式转化为可解释的电信号的传感器和系统，以实现新形式的非语言交流。本项目引入的概念、材料、系统设计和表征方法可以为动态运动过程中表皮表面的快速、体内生物动力学评估提供新的途径。这种系统可以帮助对各种神经肌肉状况进行持续的临床监测，其中的变化可能是由于(i)肌肉运动的时间依赖性改变，从而可测量神经退行性进展引起的表皮变形，或（ii）整个药物治疗过程中的反应。拟议的跨学科项目将与教育和推广活动相结合，包括关于兼容传感器微加工的跨学科课程，以及为从K-12到研究生阶段的代表性不足的学生开发低功耗、计算轻范式的医学传感。软组织生物动力学的精确测量，如面部变形时的皮肤张力，可用于计算识别不同的面部运动，从而促进缺乏说话能力或与传统电子通信接口交互能力的患者的非语言交流。然而，现有的非语言交流系统不适合用于身体的曲线区域，如脸部。一个广泛部署的面部运动实时检测系统，结合使用低成本材料，易于制造的工艺，以及制造，测试和验证的无缝管道，为临床实现的非语言通信技术提供了前所未有的潜力。该研究的主要目标是引入一套材料、设备设计、制造步骤、理论计算、模拟和验证协议，通过使用由柔性衬底上的压电薄膜组成的兼容设备，实现对时空表皮应变的鲁棒、机械自适应、可预测和视觉不可见的体内监测，并解码不同的面部变形特征。该项目将解决的挑战包括：1)开发一个兼容的面部代码外推传感器（cFaCES）， 2)三维数字图像相关（3D-DIC）用于动态变形下软组织的时空评估，以及3)在各种面部变形期间对健康和肌萎缩侧索硬化症（ALS）受试者进行体内实时解码（RTD）。拟议的工作将建立在PI在压电，微制造生物医学设备和兼容系统方面的跨学科专业知识和经验之上。该系统将引入一种新颖的设备设计和微加工策略，以及一个框架和先进的算法，这将是重建任何人体软组织的时空精确应变图的关键因素。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Many neuromuscular disorders, such as amyotrophic lateral sclerosis (ALS), often manifest themselves through physiological changes including gradual loss of the ability to exercise fine motor skills and to vocalize intelligible speech. Predictable methods for continuous tracking of dynamic skin strain on the face, therefore, can enable new forms of communication for individuals with such disorders. Present methods for in vivo characterization of facial deformations involve electromyography (EMG), skin impedance measurements, or camera tracking. Yet these typically result in high uncertainties or have bulky structures with highly visible interfaces to soft skin, presenting difficulty for continuous use in daily life, especially for individuals with neuromuscular disorders. The aim of the proposed research is to realize conformable sensors and systems that can translate patterns of facial soft tissue biomechanics in vivo into interpretable electrical signals to enable new forms of non-verbal communication. The concepts, materials, system design and characterization methods to be introduced in this project can offer new routes for rapid, in vivo biokinematic assessment of epidermal surfaces during dynamic movements. Such systems can help for continuous clinical monitoring of a wide range of neuromuscular conditions, where variations are anticipated due either to (i) time-dependent alterations in muscle movements, and thus measurable epidermal deformations due to neurodegeneration progression, or (ii) a response throughout medical therapy. The proposed interdisciplinary project will be integrated with educational and outreach activities, including interdisciplinary classes on the microfabrication of conformable sensors and the development of lower-power, computationally light paradigms for medical sensing for underrepresented students all the way from K-12 to graduate levels.Precise measurements of soft tissue biokinematics, such as skin strain during facial deformations, can be used to computationally recognize distinct facial motions, and thus facilitate nonverbal communication for patients who lack the ability to speak or interact with traditional electronic communication interfaces. However, existing nonverbal communication systems are unsuitable for use on curvilinear regions of the body, such as the face. A widely deployable system for real-time detection of facial motions, when combined with the use of low-cost materials, easily manufacturable processes, and a seamless pipeline for fabrication, testing, and validation, offers unprecedented potential for clinically realizable nonverbal communication technologies. The primary goal of the proposed research is to introduce a set of materials, device designs, fabrication steps, theoretical calculations, simulations, and validation protocols that realize robust, mechanically-adaptive, predictable, and visually-invisible in vivo monitoring of spatiotemporal epidermal strains and decoding of distinct facial deformation signatures through the use of conformable devices comprised of piezoelectric thin films on compliant substrates. The challenges that will be addressed during the course of the project include: 1) Development of a conformable Facial Code Extrapolation Sensor (cFaCES), 2) Three-Dimensional Digital Image Correlation (3D-DIC) for spatiotemporal assessment of soft tissues under dynamic deformations, and 3) In vivo Real-Time Decoding (RTD) on both healthy and amyotrophic lateral sclerosis (ALS) subjects during various facial deformations. The proposed work will build upon the PI's interdisciplinary expertise and experience in piezoelectric, microfabricated biomedical devices and conformable systems. The proposed system will introduce a novel device design and microfabrication strategy, along with a framework and advanced algorithms that will be a key enabler to reconstruct spatiotemporally accurate strain maps for any human body soft tissue.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.