About

Dagmar Sternad is a University Distinguished Professor at Northeastern University, with appointments in the departments of Biology and Electrical and Computer Engineering, and affiliated roles in Bioengineering and Physics. Her research centers on computational motor neuroscience, human movement control and learning, human-robot interaction, and clinical applications. She investigates the learning and control of sensorimotor coordination in humans, including both healthy individuals and those with neurological impairments. Her work integrates behavioral experiments with mathematical models of control and nonlinear dynamics, bridging biology, engineering, and physics. At the core of her research is the Action Lab, which focuses on understanding the control and coordination of goal-directed human behavior through a systems-level approach. This involves revealing the organizational principles of the nervous system in interaction with the mechanical system of the body and environment. Her experimental work examines single- and multi-joint movements, upper limb manipulation, and locomotion, including studies involving virtual environments and populations such as the elderly and patients with neurological disorders like Parkinson's disease. Her contributions have been recognized through numerous awards and continuous research support from agencies such as the NIH, NSF, and Office of Naval Research.

Research topics

• Computer Science
• Artificial Intelligence
• Human–computer interaction
• Engineering
• Psychology
• Cognitive psychology
• Cognitive science
• Simulation
• Neuroscience
• Mathematics

Selected publications

• Force-velocity coupling limits human adaptation in physical human–robot interaction

  Scientific Reports · 2026-01-16

  articleOpen accessSenior author

  In physical human-robot interaction, both humans and robots need to adapt to ensure synergetic behavior. This study investigated how humans respond to robots moving with different velocity profiles. In unconstrained human movements, velocity scales with the trajectory's curvature, i.e., moving fast at linear segments while slowing down at curved segments. Two experiments examined humans tracking a robot that traced an elliptic path with different velocity profiles, while instructed to minimize interaction forces. Results showed involuntary forces were higher when the robot moved with constant velocity or exaggerated the biological velocity-curvature scaling. Specifically, higher angular velocities in the robot were associated with greater tangential and normal forces. Experiment 1 tested whether biomechanical constraints caused these forces by reversing movement direction, but observed differences were small. Experiment 2 explored human adaptation across three practice sessions and found that interaction forces decreased for non-biological profiles only when real-time visual feedback was provided. The force-velocity modulations weakened, indicating that humans learned to predict and compensate for inertial forces. These findings highlight the need to consider human motor limitations and learning processes in physical interaction. The results have practical implications for collaborative and wearable robots where physical contact and coordination between humans and robots are critical.

  PublisherOA PDFDOI

• Testing sensorimotor timing across age and music experience in a real-world environment

  Scientific Reports · 2026-02-11

  articleOpen accessSenior author

  Rhythmic ability has been studied for more than a century in laboratory settings testing timed finger taps. While robust results emerged, it remains unclear whether these findings reflect behavioral limitations in realistic scenarios. This study tested the synchronization-continuation task in a museum with 335 visitors of a wide variety of ages (5-68yrs), music experiences (0-40yrs) and educational and cultural backgrounds. Adopting a dynamic system’s perspective, three metronome pacing periods were anchored around each individual’s preferred tempo: the preferred tempo, 20% faster, and 20% slower. Key laboratory findings were replicated and extended to a large age range and individuals with only informal music training: timing error and variability decreased during childhood and increased in older adults, and they were lower even with only moderate music experience. Consistent with an oscillator perspective, timing at non-preferred tempi drifted toward their preferred rate. Overall, these findings demonstrate that some of the main results on sensorimotor timing from controlled experiments are robust to noisy, naturalistic settings.

  PublisherOA PDFDOI

• Dynamical stability and mechanical impedance are optimized when manipulating uncertain dynamically complex objects

  PLoS Computational Biology · 2025-12-09

  articleOpen accessSenior author

  Manipulating complex objects is ubiquitous in our daily activities, such as donning a jacket or carrying a cup of coffee. However, such non-rigid objects easily become unstable: When carrying a cup of coffee, the coffee could slosh unpredictably and spill out of the cup. It remains unclear what motor control strategies ensure stability, especially when the physical properties of the object, like the amount of liquid in the cup, are unknown. The task of transporting a 'cup of coffee' was simplified to transporting a virtual cup with a sliding ball inside, modeled as a cart-pendulum system. Participants were instructed to 'jiggle' the cup in one dimension to prepare the cup and ball states for the ensuing continuous rhythmic movement. To introduce uncertainty regarding the object's properties, the pendulum's length was manipulated either to 1) change randomly from trial to trial, or to 2) remain constant across trials. We measured the ball's angle at the end of preparation and the cup's oscillation frequency during the rhythmic portion of the trial. Grip force on the robot handle served as proxy for mechanical impedance of the arm. The results supported three predictions: 1) When dynamic uncertainty was high, object preparation was important to stabilize the transient dynamics; stability increased during preparation and humans prepared longer when the dynamics was uncertain. 2) Humans maximized dynamic stability by flexibly covarying system initialization and cup frequency; dynamic stability matched participant behavior better than magnitude or smoothness of force. 3) Humans increased their arm impedance to accommodate uncertain dynamics, while the net force applied on the cup remained the same. Feedforward simulations using an impedance controller and stochastic open-loop optimal control corroborated these findings, further revealing that participants' selection of preparation and interaction frequencies also minimized mechanical impedance. In sum, humans used preparation and interaction strategies to optimize the mechanical impedance and dynamic stability of the hand-object interactions. These results may inform approaches in robotic control and rehabilitation.

  PublisherDOI

• Trial-By-Trial Variation In Upper Extremity Movement Smoothness After Acute Stroke Relates To Clinical Assessments And Corticospinal Tract Injury

  Neurorehabilitation and neural repair · 2025-05-31

  articleOpen access

  Background Variability in movement is critical for performance under dynamic conditions. Stroke causes focal injury to the motor system, disrupts voluntary motor control, and leads to less smooth and more variable upper extremity movements. Few studies have characterized trial-by-trial variation in upper extremity movement smoothness and its clinical and neuroanatomic correlates in the first week post-stroke. Objective To evaluate trial-by-trial variation in upper extremity movement smoothness during planar reaching and relate it to clinical outcomes and neuroanatomical injury after acute stroke. Methods Twenty-two patients (4.4 ± 1.7 days post-stroke) and 22 able-bodied adults completed a planar center-out reaching task. Smoothness was quantified with spectral arc length (SPARC). Median and interquartile range (IQR, a quantification of trial-by-trial variation) of SPARC values were assessed. Patients completed a clinical assessment battery acutely and at 90 days post-stroke. MRI-derived stroke lesions were analyzed to estimate basal ganglia, motor cortex, and corticospinal tract injury. Intraclass correlation, Spearman’s correlation, and multivariate regression evaluated trial-by-trial variation and its relation to clinical assessments, outcomes, and neuroanatomical injury. Results Post-stroke reaching was less smooth and more variable (larger IQR) compared to able-bodied adults. Variability in post-stroke smoothness was primarily driven by within-subject, trial-by-trial variation. More variable smoothness, even after controlling for median smoothness, related to worse performance on clinical assessments and 90-day outcomes. More variable smoothness related to greater corticospinal tract injury (ρ = 0.537, P = .011), but not to basal ganglia or motor cortex injury. Conclusion Trial-by-trial variation of movement is valuable for understanding sensorimotor control post-stroke and has implications for targeted neurorehabilitation.

  PublisherOA PDFDOI

• Predictive strategies for the control of complex motor skills: recent insights into individual and joint actions

  Current Opinion in Behavioral Sciences · 2025-04-04 · 6 citations

  preprintOpen access

  Humans perform exquisite sensorimotor skills, both individually and in teams, from athletes performing rhythmic gymnastics to everyday tasks like carrying a cup of coffee. The ‘predictive brain’ framework suggests that mastering these skills relies on predictive mechanisms, raising the question of how we deploy predictions for real-time control and coordination. This review highlights two research lines, showing that during the control of complex objects, people make the interaction with ‘tools’ predictable, and that, during dyadic coordination, people make their behavior predictable and legible for their partners. These studies demonstrate that to achieve sophisticated motor skills, we play ‘prediction tricks’: we select subspaces of predictable solutions and make sensorimotor interactions more predictable and legible by and for others. This synthesis underscores the critical role of predictability in optimizing control strategies across contexts. Furthermore, it emphasizes the need for novel studies on the scope and limits of predictive mechanisms in motor control. • Humans use ‘prediction tricks’ to simplify complex motor tasks. • Increased task predictability enhances control by preempting errors. • Motor skills rely on selecting subspaces of predictable solution for efficiency. • Humans interpret co-actors’ kinematics, while co-actors make their actions clearer.

  PublisherDOI

• Emergent motor timing enhances time perception

  iScience · 2025-08-14 · 2 citations

  articleOpen access

  Precise timing underlies many behaviors, from musical performance to navigating a dynamic environment. This study examined how stable temporal patterns that emerge during goal-directed movements influence timing acuity in perceptual discrimination. Rather than relying on explicitly timed actions, we used a self-paced throwing task in which temporal structure develops implicitly with practice. Across three experiments, participants were trained for four days, developing stable motor timing reflected in consistent "ball release times." This emergent timing selectively enhanced sensitivity to matching temporal intervals in a perceptual discrimination task. Importantly, this effect was not explained by perceptual learning and persisted over several weeks, suggesting a durable motor-perceptual linkage. The results point to a shared representation of time in action and perception, an emergent timing primitive that arises through experience in spatiotemporal movements. These findings shed light on how motor learning can shape temporal perception in ecologically relevant contexts, with implications for rehabilitation and sensorimotor integration.

  PublisherDOI

• Testing Sensorimotor Timing in a Living Laboratory – Behavioral Signatures of a Neural Oscillator

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-06-25

  preprintOpen accessSenior author

  Abstract Rhythmic ability has been studied for more than a century in laboratory settings testing timed finger taps. While robust results emerged, it remains unclear whether these findings reflect behavioral limitations in realistic scenarios. This study tested the synchronization-continuation task in a museum with 455 visitors of a wide variety of ages (5-74yrs), musical experiences (0-40yrs) and educational and cultural backgrounds. Adopting a dynamic system’s perspective, three metronome pacing periods were anchored around each individual’s preferred tempo, and 20% faster and 20% slower. Key laboratory findings were replicated and extended: timing error and variability decreased during childhood and increased in older adults and were lower, even with moderate musical experience. Consistent with an oscillator perspective, timing at non-preferred tempi drifted toward their preferred rate. Overall, these findings demonstrate that timing limitations may reflect attractor properties of a neural oscillator and its signature is still present even in noisy, naturalistic settings.

  PublisherOA PDFDOI

• Tracking Limb Movement in Preterm Infants Using an Inertial Measurement Bracelet

  2025-07-14

  article

  Preterm infants are monitored continuously in the neonatal intensive care unit (NICU), often for weeks to months. Cardiac and respiratory signals are routinely collected to enable detection and early interventions that mitigate a wide range of complications associated with prematurity. Neurological monitoring is often lacking in the NICU despite the high risk of neurological sequelae including motor and cognitive disorders. Here we report our design and implementation of a wireless wearable device for quantifying limb movements of preterm infants. The Limb Inertial Measurement Bracelet for Infant Tracking (LIMBIT) is a thin, flexible, 3-gram bracelet placed around the infants' wrists and ankles for continuous measurement of limb motion. Three-dimensional acceleration and angular velocity are recorded using the device's inertial measurement unit (IMU). Ultra-low battery consumption is achieved through an embedded system architecture with a power-saving algorithm for optimal interplay between the accelerometer and gyroscope sensors. With a battery life of several days, we demonstrate the feasibility of accurate longitudinal and continuous recordings in the NICU. Movement signals are synchronized with other routinely collected health signals. The device's size, weight, flexibility, and integration within soft, sterile materials allows for a safe and non-invasive recording method in the NICU. LIMBITs enable the study of movement as a physiological vital sign and, like other vital signs, may enable more accurate detection and forecasting of adverse events as well as improved motor and cognitive outcomes in preterm infants.

  PublisherDOI

• Time-warping analysis for biological signals: methodology and application

  Scientific Reports · 2025-04-05 · 5 citations

  articleOpen accessSenior author

  Any set of biological signals has variability, both in the temporal and spatial domains. To extract characteristic features of the ensemble, these spatiotemporal profiles are typically summarized by their mean and variance, often requiring prior padding or resampling of the data to equalize signal length. Such compression can conceal essential information in the signal. This work presents the method of time-warping, reformulated as elastic functional data analysis (EFDA), in an accessible way. This powerful approach rescales the temporal evolution of signals, aligns them accurately, decouples their spatial and temporal variability, and faithfully extracts their characteristics. This technique was compared to conventional methods of normalizing or padding data followed by averaging, using synthetized signals with controlled variability and real human data from a complex manipulation task. Comparative analysis demonstrates that EFDA successfully reveals otherwise concealed features and teases apart temporal and spatial variability. Critical advances to the more common method of dynamic time-warping (DTW) are discussed. Application of EFDA and potential new insights are illustrated in the context of human motor neuroscience. Annotated code to facilitate the use of this technique is provided.

  PublisherOA PDFDOI

• Human Control of Underactuated Objects: Adaptation to Uncertain Nonlinear Dynamics Ensures Stability

  IEEE Transactions on Medical Robotics and Bionics · 2025-02-01 · 2 citations

  articleOpen accessSenior author

  Humans frequently interact with objects that have dynamic complexity, like a cup of coffee. Such systems are nonlinear and underactuated, potentially creating unstable dynamics. Instabilities generate complex interaction forces that render the system unpredictable. And yet, humans interact with these objects with ease. Nonlinear dynamic analysis shows that the initial conditions and frequencies of input forces determine the system's stability. Taking inspiration from carrying a cup of coffee, participants rhythmically moved a cup with a ball rolling inside which was modelled as a cart-pendulum system. They were encouraged to prepare the cup-and-ball system by 'jiggling' the cup before moving it back and forth on a horizontal line. We tested the hypothesis that humans initialize the system and choose interaction frequencies that stabilize their interactions. To create uncertainty about the specific cup-and-ball system, the pendulum length was varied without providing cues to the participant. Stability was quantified by variability of relative phase between cup and ball. Results showed that participants nonlinearly co-varied the initial ball angle at the end of preparation and the cup frequency during the rhythmic phase. Mapping participants' choices onto the highly nonlinear manifold of stable solutions generated by forward-simulations verified that they indeed achieved stable solutions.

  PublisherOA PDFDOI

Recent grants

• NRI: Collaborative Research: Towards Robots with Human Dexterity

  NSF · $500k · 2017–2020

• Dynamics of Action and Perception in a Rhythmic Task

  NSF · $284k · 2005–2008

• Predictability in Complex Object Control

  NIH · $1.8M · 2015–2022

• Collaborative Research: Learning to Control Dynamically Complex Objects

  NSF · $419k · 2018–2023

• Predictability in complex object control

  NIH · $3.0M · 2015–2027

Frequent coauthors

• Salah Bazzi

  Northeastern University

  101 shared

• Reza Sharif Razavian

  Center for the Neural Basis of Cognition

  94 shared

• Mohsen Sadeghi

  Northern Arizona University

  94 shared

• Aaron P. Batista

  Center for the Neural Basis of Cognition

  92 shared

• Raeed H. Chowdhury

  Center for the Neural Basis of Cognition

  92 shared

• Patrick J. Loughlin

  University of Pittsburgh

  92 shared

• Neville Hogan

  Massachusetts Institute of Technology

  47 shared

• Marta Russo

  Northeastern University

  29 shared

Labs

• Action LabPI

Education

• PhD, Psychology

  University of Connecticut

  1995

Awards & honors

• 2021-22 Fulbright Award to research “Variability and Redunda…
• Klein Lectureship Award Distinguished Lecturer on Life and t…
• 2025 Stanford University Annual Assessment of Author Citatio…
• 2024 Stanford University Annual Assessment of Author Citatio…
• 2023 Stanford University Annual Assessment of Author Citatio…