Accelerating Research Translation

Multimodal System Integrating Nanocomposite Wearable & EMG Sensors for Tracking Human Movements and Physical Rehabilitation
Sagar Doshi, Center for Composite Materials  

This UD team is developing a technology that will enable real-time and continuous monitoring of human movements and gait outside of a clinic/laboratory setting to help physical therapy (PT) clinicians and patients make the post knee-replacement rehabilitation process more efficient, convenient and affordable. Based on 30+ voice-of-customer interviews with PT clinicians, there is no affordable, convenient way for them to track their patient's progress — to determine if the patients are compliant with the prescribed exercises — which makes recovery inefficient and could lead to additional injuries or loss of functionality. This team’s proposed solution is the development of a multimodal sensing platform consisting of (i) commercially available (electromyography) EMG sensors from mTrigger LLC, which measure the electrical activity produced by target muscle groups during physical rehabilitation, and (ii) our patented textile-based wearable sensors that are comfortable, flexible and easy to use to measure joint mobility and pressure.

Music for Listeners with Autism: An Online Platform for Collecting Music Interaction Data from Children with Autism

Matthew Mauriello, Dept. of Computer and Information Sciences, and Daniel Stevens, School of Music

In 2020, the Centers for Disease Control (CDC) reported that 1 in 36 U.S. children were diagnosed with autism spectrum disorders (ASD), a significant rise over prior years. While many children with ASD are musically inclined, those who struggle to engage in early, formative participatory music listening do not fully benefit from the cognitive, motor, emotional and social growth that attends this activity. This project aims to develop a web-based music listening, interaction and data collection platform that features modular arrangements of children’s songs designed for children with ASD. These variable-speed arrangements allow listeners to add, subtract and recombine musical layers according to their preferences, needs, emotional states and expressive desires. By recording these interactions at scale, this UD team seeksto create datasets to generate insights about listener preferences and inform future compositions and music therapies.

Novel Assay Platform for Detection of Ubiquitinated Tau as an Alzheimer’s Disease Biomarker

Chris Martens, Dept. of Kinesiology and Applied Physiology, and Zhihao Zhuang, Dept. of Chemistry and Biochemistry

Is there any way to move the right arrow so that it doesn’t cut off “states” in United States?

Alzheimer’s disease (AD) is the most prevalent neurodegenerative condition in the United States, imposing a significant economic burden on society. Biomarkers for AD and related dementias not only aid in early diagnosis and treatment but also enhance drug discovery by enabling patient stratification and improving clinical trial success rates. On the therapeutic front, the repertoire of disease-modifying treatments for AD remains exceptionally limited. Given the important roles of Tau ubiquitination in the AD pathophysiology and disease progression, it is imperative to explore ubiquitinated Tau (Ub-Tau) as a potential biomarker for AD. Currently, there are no blood-based Ub-Tau biomarker assays reported in the literature and adopted in the clinics. The PI’s lab has developed a patented method for generating well-defined and homogenous Ub-Tau. This project will establish the validity of this UD assay for future research, diagnostic and clinical applications.