About

Eric J. Perreault is a Professor of Biomedical Engineering at Northwestern University. His research group focuses on understanding the neural and biomechanical factors involved in the normal control of multi-joint movement and posture, as well as how these factors are modified following neuromotor pathologies such as stroke and spinal cord injury. The goal of his research is to provide a scientific basis for understanding normal and pathological motor control that can be used to guide rehabilitative strategies and user interface development for restoring function to individuals with motor deficits. His work employs a combination of experimentation, computer simulations, and machine learning to achieve these objectives.

Research topics

• Computer Science
• Medicine
• Physics
• Physical therapy
• Artificial Intelligence
• Physical medicine and rehabilitation
• Classical mechanics
• Neuroscience
• Biology
• Mathematics
• Speech recognition
• Engineering
• Psychology
• Mechanics
• Anatomy
• Structural engineering

Selected publications

• Reflex hyperexcitabilicty persists during voluntary muscle activation following stroke

  Journal of Neurophysiology · 2026-03-27

  articleOpen accessSenior author

  After a stroke, the spinal stretch reflex is altered, but its behavior during functionally relevant, active-muscle conditions remained unclear. By accounting for both agonist and antagonist muscle activity, we reconcile discrepancies in the literature and demonstrate that the post-stroke stretch reflex is increasingly hyperexcitable with muscle activation. These results reveal persistent poststroke reflex differences during active conditions, highlighting impaired stretch reflex modulation as a potential contributor to movement deficits and a critical target for rehabilitation.

  PublisherDOI

• Composite material homogenization for shear wave elastography of muscle-like fiber-laden viscoelastic waveguides under prestress

  SSRN Electronic Journal · 2026-01-01

  preprintOpen access
  PublisherDOI

• Along- and cross-muscle fiber shear moduli in skeletal muscle

  Journal of Biomechanics · 2025-11-19

  articleOpen access
  PublisherOA PDFDOI

• Mechanical characterization of an incompressible, strain-hardening, transversely isotropic material

  Acta Biomaterialia · 2025-11-03

  articleOpen access

  A strain energy approach for the characterization of strain-hardening, transversely isotropic materials was developed and validated through a combination of indentation and uniaxial extension experiments. These experiments were utilized because they can also be applied to directly measure the mechanical properties of many living tissues, including muscle. Model materials with transversely isotropic mechanical properties broadly representative of biological tissues were utilized in the experiments. These organogels were made from acrylic triblock copolymer solutions with an aligned cylindrical domain morphology. The strain energy function used here was proposed recently by Hegde et al., and is based on the three independent linear elastic constants for a transversely isotropic material, along with two additional strain-hardening parameters. These five parameters were determined for the model material by indentation with a blade indenter aligned both parallel and perpendicular to the unique axis of the gel, and by uniaxial extension of the material along the directions parallel and perpendicular to the unique axis. The effect on the indentation curves of an applied tensile pre-stress applied along the unique axis was also investigated. Finite element modeling was used to generate interpolated functions that allow the elastic constants, along with their uncertainty, to be obtained from the experimental data in a straightforward manner. These parameters were then used to predict the wave speeds in pre-stressed material that would be measured by shear wave elastography, a commonly used technique for non-invasively characterizing the mechanical properties of biological tissues.

  PublisherDOI

• Along- and Cross-Muscle Fiber Shear Moduli in Skeletal Muscle

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• Muscles Functioning as Primary Shoulder Movers Aid the Rotator Cuff Muscles in Increasing Active Glenohumeral Stiffness

  Annals of Biomedical Engineering · 2025-03-18 · 1 citations

  articleSenior author
  PublisherDOI

• Effects of Uni- and Bi-Directional Interaction During Dyadic Ankle and Wrist Tracking

  IEEE Transactions on Neural Systems and Rehabilitation Engineering · 2025-01-01 · 2 citations

  articleOpen access

  Haptic human-robot-human interaction allows users to feel and respond to one another's forces while interfacing with separate robotic devices, providing customizable infrastructure for studying physical interaction during motor tasks (e.g., physical rehabilitation). For upper- and lower-limb tracking tasks, previous work has shown that virtual interactions with a partner can improve motor performance depending on the skill level of each partner. However, whether the mechanism explaining these improvements is identical in the upper and lower limbs is an open question. In this work, we investigate the effects of haptic interaction between healthy individuals during a trajectory tracking task involving single-joint movements at the wrist and ankle. We compare tracking performance and muscle activation during haptic conditions where pairs of participants were uni- and bidirectionally connected to investigate the contribution of real-time responses from a partner during the interaction. Findings showed similar improvements in tracking performance during bidirectional interaction for both the wrist and ankle. This was observed despite distinct strategies in muscle co-contraction between joints, as co-contraction was dependent on partner ability for the wrist but not the ankle. For each joint, bidirectional and unidirectional interaction resulted in similar improvements for the worse partner in the dyad. For the better partner, bidirectional interaction resulted in greater improvements than unidirectional interaction. While these results suggest that unidirectional interaction is sufficient for error correction of less skilled individuals during simple motor tasks, they also highlight the mutual benefits of bidirectional interaction which are consistent across the upper and lower limbs.

  PublisherDOI

• Wave propagation in prestressed and transversely isotropic viscoelastic structures: Inverse modeling challenges in elasticity imaging

  The Journal of the Acoustical Society of America · 2025-04-01

  article

  The functional role and structure of skeletal muscle results in anisotropy in both material properties and imposed stresses, as well as waveguide effects. Dynamic elastography reconstruction methods for estimating muscle tissue viscoelastic properties that are rooted in assumptions of isotropy and bulk wave motion may produce inaccurate estimates. The superposition of axially aligned orthotropy (transverse isotropy) in material properties and axially aligned prestress conditions due to passive stretch or muscle activation makes it difficult to independently discern how much of the apparent anisotropy is due to the muscle material or the imposed stress field. Furthermore, this stress field may result in large strain conditions that require the use of higher-order terms in the stress–strain relationship. The significance of these confounding conditions and strategies for decoupling material and stress-based anisotropy are investigated with a series of numerical finite element studies based on simple and morphological image-informed geometries, and experimental elastography studies using scanning laser Doppler vibrometry and magnetic resonance elastography.

  PublisherDOI

• Mechanical Characterization of an Incompressible, Strain-Hardening, Transversely Isotropic Material

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• Consensus for experimental design in electromyography (CEDE) project: Checklist for reporting and critically appraising studies using EMG (CEDE-Check)

  Journal of Electromyography and Kinesiology · 2024-03-13 · 38 citations

  articleOpen access

  The diversity in electromyography (EMG) techniques and their reporting present significant challenges across multiple disciplines in research and clinical practice, where EMG is commonly used. To address these challenges and augment the reproducibility and interpretation of studies using EMG, the Consensus for Experimental Design in Electromyography (CEDE) project has developed a checklist (CEDE-Check) to assist researchers to thoroughly report their EMG methodologies. Development involved a multi-stage Delphi process with seventeen EMG experts from various disciplines. After two rounds, consensus was achieved. The final CEDE-Check consists of forty items that address four critical areas that demand precise reporting when EMG is employed: the task investigated, electrode placement, recording electrode characteristics, and acquisition and pre-processing of EMG signals. This checklist aims to guide researchers to accurately report and critically appraise EMG studies, thereby promoting a standardised critical evaluation, and greater scientific rigor in research that uses EMG signals. This approach not only aims to facilitate interpretation of study results and comparisons between studies, but it is also expected to contribute to advancing research quality and facilitate clinical and other practical applications of knowledge generated through the use of EMG.

  PublisherDOI

Recent grants

• NIH Grant K25HD044720

  NIH · $621k · 2009

• Stretch Reflex Contributions to Multijoint Coordination

  NIH · $2.4M · 2006–2018

• A primate model of an intra-cortically controlled FES prosthesis for grasp

  NIH · $7.4M · 2006–2023

• Pathophysiology and Rehabilitation of Neural Dysfunction

  NIH · $7.5M · 1992–2027

• CPS: Large: Cybernetic Interfaces for the Restoration of Human Movement through Functional Electrical Stimulation

  NSF · $3.4M · 2009–2015

Frequent coauthors

• Daniel Ludvig

  McCormick (United States)

  167 shared

• Levi J. Hargrove

  Northwestern University

  70 shared

• Wendy M. Murray

  57 shared

• Robert F. Kirsch

  Case Western Reserve University

  48 shared

• José L. Pons

  Shirley Ryan AbilityLab

  44 shared

• François Hug

  Université Côte d'Azur

  41 shared

• Yue Wen

  Beijing Institute of Technology

  39 shared

• Emek Barış Küçüktabak

  Shirley Ryan AbilityLab

  38 shared