Allitia DiBernardo
Papers
2
Total Citations
180
H-Index
2
About
Allitia DiBernardo is a leading researcher in neurorehabilitation and stroke recovery, whose work bridges the gap between robotics and clinical neurology. Her primary research focuses on developing objective, quantitative biomarkers of motor impairment using robotic measurement systems. In her landmark 2013 study, "Robotic Measurement of Arm Movements After Stroke Establishes Biomarkers of Motor Recovery," DiBernardo demonstrated that robotic kinematic and kinetic data collected from stroke patients correlate strongly with standard clinical outcome measures. This work, cited over 150 times, established a foundation for using high-resolution robotic devices to track recovery trajectories with unprecedented precision. Building on this, her 2021 paper introduced machine learning models that accurately predict clinical stroke scales from robotic measurements, addressing the critical challenge of rater subjectivity in clinical trials. By reducing variability in endpoint measurement, DiBernardo’s innovations promise to enhance the statistical power and reliability of stroke rehabilitation studies. Her contributions have positioned her at the forefront of precision medicine for motor recovery, offering researchers and clinicians powerful tools to objectively assess and accelerate patient rehabilitation.
Research Focus
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Top Papers
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