Research Areas - The Center for Neuromechanics

We study the mechanical behavior of the brain and neuronal tissue through advanced computational modeling and experimental techniques. Our computational models are designed to address significant clinical problems, such as progression of Alzheimer’s disease or modeling of brain injury. Experimentally, we try to better understand the structure-stiffness relationship of the brain and to design better neural implants for the treatment of Parkinson’s disease.

We utilize novel neuroimaging techniques to inform our computational brain models of brain aging and neurodegenerative disease. The increasing availability of open-source large datasets with longitudinal medical image data provides fascinating new avenues to study morphological, anatomical, and functional changes as the brain ages. We develop new tools to track these changes across long time scales with the goal to identify underlying damage mechanisms. These mechanisms then inform computational models that are used to make predictions about aging and potential diseases.

This interdisciplinary area of research brings together knowledge in biology, mechanics, and electronics to study new wearable or implantable electromechanical systems for assistive, therapeutic, or diagnostic purposes. Examples of such systems include robotic exoskeletons for performance augmentation of able-bodied subjects, powered orthoses for assistance of individuals with impaired motor function, robotic devices for therapeutic training, active prostheses for the restoration of function after traumatic limb loss, computerized interfaces for neuromotor training, and wearable sensors to monitor biomechanical or physiological variables during clinical assessments or real-life activities.

We formulate fundamental science and engineering basis towards new process development, modeling, and optimization of additive biomanufacturing methods in various engineered neuronal tissue applications. We aim to combine principles of molecular, cellular and cognitive neurosciences and developmental neurobiology with electrical, mechanical, biomedical and material sciences and engineering for developing systems and approaches that help: 1) Increase our understanding of basic neurosciences and nervous development, and 2) Find treatments and rehabilitation strategies for neurological disorders and disabilities.

We study the relationships between the brain, language abilities and mental health. It is well known that diseases like Alzheimers and stroke affect a patient’s language ability. We develop interpretable and explainable artificial intelligence (AI) engines to predict these diseases using a patient’s language abilities. In 2019 alone, Americans spent $244B in caring for patients with Alzheimer’s Disease and Related Dementia (ADRD). The National Academy of Sciences, the National Plan to Address Alzheimer’s Disease, and the Affordable Care Act through the Medicare Annual Wellness, all identify earlier detection of ADRD as a core aim for improving the brain health for millions of Americans. The success of disease modification and preventive therapeutics for ADRD requires the identification of the disease in very early stages, at least a decade before onset. As language functions play an important role in the detection of cognitive deficiency across different stages of ADRD, speech transcripts can assist in early detection of the disease. Hence techniques at the nexus of natural language processing and deep learning offer an inexpensive solution to this early detection problem. Our interpretable/explainable methods not only provide state-of-the-art results in detecting Alzheimer’s diseases, but can also offer a window into the functioning of the AI when making these decisions.

We develop new AI tools to gain insights into consciousness and neurological status using the large volumes of healthcare data collected every day in intensive care units. Our approaches have been used to learn how causes of complications change over time during stroke recovery, and how physiologic data can be used to identify a patient’s level of consciousness.

Stroke is a leading cause of death in the United States and is a major cause of serious disability for adults. About 87% of all strokes are ischemic strokes, in which blood flow to the brain is blocked.

We research how we can control and leverage acoustic waves in different engineering applications, including the use of ultrasound for biomedical imaging, sensing, and therapy.