BME Seminar Series: Collin Dunlap, Gretchen Baker, & Mario Mendez-Perez, The Ohio State University

All dates for this event occur in the past.

ZOOM
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United States

Collin Dunlap
Graduate Student
The Ohio State University

Gretchen Baker
Graduate Student
The Ohio State University

Mario Mendez-Perez
Graduate Student
The Ohio State University

 

Collin Dunlap:

"Promoting Independent Operation of Intracortical Brain-Machine Interfaces"

Loss of motor function due to spinal cord injury, stroke, and other neurologic disorders complicates everyday tasks and profoundly affects an individual’s independence and quality of life. Brain-machine interface (BMI) technology restores lost functionality by bridging the nervous system directly to assistive devices including computer cursors, robotic arms, and neuromuscular stimulation orthotics. While laboratory demonstrations have validated intracortical BMIs on time scales of hours, neural decoder performance can rapidly degrade due to signal fluctuations caused by neurophysiological changes, neural interface disruptions, and implant degradation. These limitations interfere with long-term, independent operation of intracortical BMIs because they necessitate technician intervention to evaluate signal quality and calibrate neural decoders. Our team has collected the longest longitudinal intracortical recording dataset in humans, and we have used these recordings to characterize BMI disruptions. I will share a case series of signal disruptions from our study and several methods we developed to mitigate them and streamline BMI operation.

Gretchen Baker: 

"Evaluation of Posture, Belt Fit, and Belt Torso Contact for Children on Belt-Positioning Booster Seats"

Interaction between the seatbelt and torso is important to understand when identifying potentially injurious scenarios for belt-positioning booster (BPB)-seated children; however, previous evaluations of static belt fit may not fully discriminate between designs which provide good vs. poor outcomes during motor vehicle crashes. Children have also been shown to adopt a variety of postures when seated in BPBs, which may also influence belt fit and contribute to varying kinematic injury outcomes. Thus, the purpose of this study was to quantify posture, belt fit, and belt torso contact for children on BPBs. A cohort of 50 child volunteers were recruited and evaluated on a randomized selection of BPBs in a laboratory environment. Novel and conventional measurements of belt fit and belt torso contact were quantified using a 3D coordinate measurement device, and an inertial measurement unit (IMU)-based motion capture system was utilized to quantify posture. Belt fit, belt torso contact, and posture results varied significantly between BPBs, and specific BPB design features contributed to this variation. Overall, results will be used to identify boundary conditions for dynamic full-scale sled testing to investigate kinematic, kinetic, and injury outcome differences due to variations in initial belt fit and belt torso contact.

Mario Mendez-Perez:

"A data assimilation approach to predict cell population epithelial-mesenchymal transition dynamics"

Epithelial-mesenchymal transition (EMT) is a biological process that plays a central role in embryonic development, tissue regeneration, and cancer metastasis. Transforming growth factor-β (TGFβ) is a potent inducer of this cellular transition, comprised of transitions from an epithelial state to partial EMT state(s), then to a mesenchymal state. Recent experimental studies have shown that within a population of epithelial cells, different phenotypical profiles were correlated with different time- and dose-dependent responses to TGFβ1 during EMT. This offers a challenge for computational models, as most model parameters are typically averages from a range of experimental conditions. Thus, model simulations generally represent typical cell responses, not necessarily specific responses nor capture population variability. In this seminar, I will describe our work applying a statistical technique called data assimilation for reconstructing EMT dynamics of a heterogeneous virtual epithelial cell population. Moreover, we performed series of in silico studies for which the data assimilation approach was tasked with predicting the specific cellular responses to EMT-suppressing or EMT-promoting perturbations in the in the presence of physiological model error and parameter uncertainty.