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[VIRTUAL] Fall 2020 GRASP SFI: Laura Hallock, UC Berkeley, “A Systematic Modeling Framework for Deformation-Based Muscle Force Inference: Toward Safe and Capable Assistive Device Control”

November 18, 2020 @ 3:00 pm - 4:00 pm

ABSTRACT

While there exist a number of mechanically sophisticated exoskeletons and prostheses, with articulations similar to that of the intact human arm and hand,  these devices remain limited in their ability to safely and comprehensively augment human dexterity. In particular, due to the limits of conventional sensing, users can often modulate only a single degree of freedom, and we have almost no understanding of the resulting physiological impacts on the user’s musculoskeletal system.

We address these dual problems of device capability and safety by leveraging a novel class of signals  — muscle deformation, as measured via ultrasound — to probe individual muscle forces, which cannot currently be measured noninvasively but are key to understanding musculoskeletal dynamics during dexterous motion. In this talk, I will discuss our current efforts to precisely characterize this deformation signal and its relationship to muscle output force, and to measure it in real time, paving the way for both the extraction of multiple independent signals for high-dimensional device control and enhanced overall understanding of the joint human–machine dynamical system.

Presenter

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Laura Hallock is a final-year PhD student in the EECS department at UC Berkeley, advised by Ruzena Bajcsy in the Human-Assistive Robotic Technologies (HART) Lab. Her research focuses on improving system identification of human arm dynamics using multiple sensing modalities, including ultrasound and acoustic myography, to generate physics-based models applicable to assistive device design, medical diagnostics, and studies of motor control. Prior to joining the graduate program, she received her SB in EECS from MIT, where she worked on neuromuscular modeling for lower-limb prostheses in the MIT Media Lab’s Biomechatronics Group.

Details

Date:
November 18, 2020
Time:
3:00 pm - 4:00 pm
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