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Ph.D. Dissertation Defense - Nayef Ahmar

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TitleSlow Intermuscular Oscillations and Strategies to Tango with a Robot

Committee:

Dr. Minoru Shinohara, Bio Sciences, Chair , Advisor

Dr. Mark Clements, ECE, Co-Advisor

Dr. Jun Ueda, ME

Dr. David Anderson, ECE

Dr. Omer Inan, ECE

Dr. Frank Hammond III, ME

Abstract:

Steadiness and stiffness control failures are recurring problems and possibly a byproduct of "common drive", a nervous system process that activates or relax all muscles in synchrony. Slow correlated neural oscillations, a function of common drive, were investigated for improving concurrent activation control around elbow joint muscles with direct application to HRI. Experiments were designed, data collected from 80 healthy subjects. Many methods to assess and quantify common intermuscular oscillations were tested including event related coherence (amplitude and phase) and in-phase synchrony. Linear associations between system performance (neural or mechanical) and muscle correlated oscillations (amplitude and phase coherence) under different conditions (static, dynamic, and transient coactivation) were established. Multiple methods were studied to modulate or influence these associations such as repetition, and intervention (out-of-phase cocontraction, and single muscle habituation). Findings suggest that a proper HRI framework would benefit from a good grasp of task-specific demands as well as system hardware properties in addition to models representation of neural and mechanical output as a function of internal processes such as correlated oscillations.

Status

  • Workflow Status:Published
  • Created By:Daniela Staiculescu
  • Created:10/24/2018
  • Modified By:Daniela Staiculescu
  • Modified:10/24/2018

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