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BEGIN:VEVENT
DTSTAMP:20261012T210905Z
LOCATION:Summit Pavilion
DTSTART;TZID=America/Los_Angeles:20261021T173000
DTEND;TZID=America/Los_Angeles:20261021T183000
UID:HFESAM_ASPIRE 2026_sess257_POST228@linklings.com
SUMMARY:A Digital Twin Framework of Motor Performance  Variability and Fat
 igue Trajectories:  Modeling the Interaction Between Baseline Motor Instab
 ility and Cumulative Sleep Debt
DESCRIPTION:Cindy von ahlefeldt (University of Central Florida)\n\nFatigue
  from chronic sleep restriction produces cumulative attentional impairment
 s, while elevated motor variability has been identified as a sensitive mar
 ker of underlying neuromotor instability. Existing fatigue models, however
 , typically assume homogeneous baseline performance and do not account for
  how pre-existing motor instability may amplify fatigue-related decline. T
 his study introduces an agent-based digital twin framework modeling the in
 teraction between baseline motor variability and cumulative sleep debt. Tw
 o populations of 200 synthetic agents were calibrated using published Psyc
 homotor Vigilance Test (PVT) dose-response data and open-source gait varia
 bility parameters from the PhysioNet Gait in Parkinson’s Disease Database.
  Normal-variability agents reflected healthy stride-time variability, wher
 eas elevated-variability agents were initialized at 2.5 times control vari
 ability. Both groups underwent a simulated 14-day severe sleep restriction
  protocol involving four hours of sleep opportunity per night. Results dem
 onstrated a strong multiplicative interaction between baseline variability
  and fatigue accumulation. Elevated-variability agents reached the perform
 ance instability threshold on Day 3, compared to Day 11 for normal-variabi
 lity agents. By Day 14, elevated-variability agents showed nearly double t
 he attentional lapses despite comparable mean reaction times, indicating t
 hat variability indices, rather than average performance, may provide a mo
 re sensitive marker of fatigue vulnerability and operational risk\n\n
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