Conformable systems for spatiotemporal decoding of facial strains

点击翻译按钮获取中文摘要

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.