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Francisco Valero-Cuevas, PhD




1540 Alcazar St., CHP 155,
Los Angeles, CA 90089-9006


The Valero Laboratory, directed by Francisco Valero-Cuevas, is dedicated to understanding the biomechanics, neuromuscular control and clinical rehabilitation of complex neuromuscular systems such as the human hand. Toward this end, he and his team employ a synergy of experimental and theoretical techniques. This diverse experimental arsenal ranges from EMG recordings and custom-made virtual reality modules to human brain mapping with fMRI. These procedures in turn inform theoretical work to characterize neuromuscular function through rigorous and complete neuromuscular computer models, artificial intelligence and nonlinear systems analysis.

The lab focuses on the fundamental mechanisms of interactions between the brain and the body that give rise to versatile physical function. His team’s conceptual approach is that machines and organisms are part of a continuum of solutions that have evolved to respond to the demands of the physical environment. They differ only in their means to respond to these demands. Therefore, the apparently separate fields of neuroscience, computation and modeling, biomechanics, manipulation, robotics and clinical research (which have historically been mostly studied in isolation) can be combined and applied to the grand challenges of reverse engineering neuromuscular systems to understand the neuromechanical basis for versatile physical function, improve clinical restoration of function and create innovative and versatile machines.

Dr. Valero-Cuevas’ laboratory insists on anatomical and neurophysiological fidelity, mathematical and computational rigor and clinical usefulness. More specifically, a rich mixture of behavioral, experimental and conceptual tools enables the theoretical and experimental lines of research and development in the laboratory. These projects include studies of able and impaired human function, electrophysiological recordings from muscles and the brain, structural and functional MRI and novel virtual reality environments. The conceptual basis of this work comes from computational neuroscience, linear systems theory, nonlinear dynamics, machine learning, control theory and computational geometry. More recent applications range from novel clinical measures of dynamic manipulation, innovative robot design and control and immersive environments for rehabilitation. His laboratory and graduate student facilities are on both the University Park and Health Sciences Campuses.

  • Doctor of Philosophy, Mechanical Engineering, Biomechanical Engineering, Stanford University, 1997
  • Master of Science, Engineering, Queen’s University, 1991
  • Bachelor of Science, Engineering, Swarthmore College, 1988


See Francisco Valero-Cuevas’ curriculum vitae.


Valero Lab


See complete publication list


Peer-Reviewed Articles

  • Krenn O, Werner I, Lawrence EL, Valero-Cuevas FJ. “The lower extremity dexterity test quantifies sensorimotor control for cross country skiing.”
  • E. Müller; J. Kröll; S. Lindinger; J. Pfusterschmied & T. Stöggl. Science in Skiing VI. p. 439-45. Meyer & Meyer Sport (UK) ISBN: 978-1-78255-066-2, 2015.
  • Ko N, Laine CM, Fisher BE, Valero-Cuevas FJ. “Force variability during dexterous manipulation in individuals with mild to moderate Parkinson’s disease.” Frontiers in Aging Neuroscience – The Hand at Work: Effects of Aging 7(108), doi: 10.3389/fnagi.2015.00151, 2015.
  • Lawrence EL, Dayanidhi S, Fassola I, Requejo P, Leclercq C, Winstein CW,Valero-Cuevas FJ “Outcome measures for hand function naturally reveal three latent domains in older adults: Strength, coordinated upper extremity function, and sensorimotor processing.” Frontiers in Aging Neuroscience – The Hand at Work: Effects of Aging, 7(108), doi: 10.3389/fnagi.2015.00108, 2015.
  • Pavlova EL, Hedberg A, Ponten E, Gantelius S, Valero-Cuevas FJ, Forssberg H. “Activity in the brain network for dynamic manipulation of unstable objects is robust to acute tactile nerve block: An fMRI study.” Brain Research, 1620: p. 98-106, 2015
  • Valero-Cuevas FJ, Cohn BA, Yngvason HF, Lawrence EL. “Exploring the high-dimensional structure of muscle redundancy via subject-specific and generic musculoskeletal model” Journal of Biomechanics, ASB Special Issue, 48(11): p. 2887-96, 2015.
  • Duff SV, Aaron DH, Gogola, GR, Valero-Cuevas FJ. “Innovative evaluation of dexterity in pediatrics.” Journal of Hand Therapy, 28(2): p. 144-50, 2015
  • Lightdale-Miric N, Mueske NM, Lawrence EL, Loiselle J, Berggren J, Dayanidhi S,tevanovic M, Valero-Cuevas FJ, Wren TAL. “Long Term Functional Outcomes After Early Childhood Pollicization.” Journal of Hand Therapy, 28(2): p. 158-66, 2014.
  • Lightdale-Miric N, Mueske NM, Dayanidhi S, Loiselle J, Berggren J, Lawrence EL, Stevanovic M, Valero-Cuevas FJ, Wren TAL. “Quantitative Assessment of Dynamic Control of Fingertip Forces After Pollicization Gait & Posture.” Best Paper Award – GCMAS 2014, 41(1), p. 1-6, 2014.
  • Lawrence EL, Fassola I, Werner I, Leclercq C, Valero-Cuevas FJ. “Quantification of dexterity as the dynamical regulation of instabilities: comparisons across gender, age, and disease.” Frontiers in Neurology – Movement Disorders, 5(53). doi .3389/fneur.2014.00053, 2014.
  • Dayanidhi S and Valero-Cuevas FJ. “Dexterous manipulation is poorer at older ages and is dissociated from decline of hand strength.” Journal of Gerontology Series A: Biological Sciences and Medical Sciences, 69(9): p. 1139-45. doi: 10.1093/gerona/glu025, 2014.
  • Lyle MA, Valero-Cuevas FJ, Gregor RJ, Powers CM. “Lower extremity dexterity is associated with agility in adolescent soccer athletes.” Scandinavian Journal of Medicine and Science in Sports, 25(1): p. 81-8.
  • Inouye JM and Valero-Cuevas FJ. “Computational Optimization and Experimental Evaluation of Grasp Quality for Tendon-Driven Hands Subject to Design Constraints.” ASME Journal of Mechanical Design, 136(2), 021009, 2013.
  • Rácz K and Valero-Cuevas FJ. “Spatio-temporal analysis reveals active control of both task-relevant and task-irrelevant variables.” Frontiers in Computational Neuroscience – Modularity in Motor Control, 7:155, 2013.
  • Lyle MA, Valero-Cuevas FJ, Gregor RJ, Powers CM. “Control of Dynamic Foot-ground Interactions in Male and Female Soccer Athletes: Females Exhibit Reduced Dexterity and Higher Limb Stiffness During Landing.” Journal of Biomechanics, 47(2): p. 512-7, 2013.
  • Inouye JM and Valero-Cuevas FJ. “Anthropomorphic tendon-driven robotic hands can exceed human grasping capabilities following optimization.” The International Journal of Robotics Research (IJRR), Special Issue on Mechanics and Design of Robotic Hands: 278364913504247, 2013.
  • Dayanidhi S, Kutch JJ, Valero-Cuevas FJ. “Decrease in muscle contraction time complements neural maturation in the development of dynamic manipulation.” Journal of Neuroscience, 33(38): p. 15050-55, 2013.
  • Dayanidhi S, Hedberg A, Valero-Cuevas FJ, Forssberg H. “The developmental improvements in dynamic control of fingertip forces last throughout childhood and into adolescence.” Journal of Neurophysiology, 110: p. 1583-92, 2013.
  • Lyle MA, Valero-Cuevas FJ, Gregor RJ, Powers CM. “The lower extremity dexterity test as a measure of lower extremity dynamical capability.” Journal of Biomechanics, 46: p. 998–1002, 2013.
  • Inouye JM, Kutch JJ, and Valero-Cuevas FJ. “Optimizing the Topology of Tendon-Driven Fingers: Rationale, Predictions and Implementation. in The Human Hand: A Source of Inspiration for Robotic Hands.” Springer Tracts in Advanced Robotics (STAR) series, Balasubramanian, R. and Santos, V.J., Eds., Springer, Heidelberg: p. 247-266.
  • Rácz K, Brown D, and Valero-Cuevas FJ. “An involuntary stereotypical grasp tendency pervades voluntary dynamic multifinger manipulation.” Journal of Neurophysiology, 108: p.2896-911, 2012.]
  • Saxena A, Lipson H and Valero-Cuevas FJ. “Functional inference of complex anatomical tendinous networks at a macroscopic scale via sparse experimentation.” PLoS Computational Biology, 8(11): p.1-17, 2012.
  • Inouye JM, Kutch JJ, and Valero-Cuevas FJ. “A novel synthesis of computational approaches enables optimization of grasp quality of tendon-driven hands.” IEEE Transactions on Robotics, 28(4): p.958-66, 2012.
  • Kurse MU, Lipson H, and Valero-Cuevas FJ. “Extrapolatable analytical functions for tendon excursions and moment arms from sparse datasets.” IEEE Transactions on Biomedical Engineering, 59(6): p.1572-1582, 2012.
  • Kutch JJ and Valero-Cuevas FJ. “Challenges and new approaches to proving the existence of muscle synergies of neural origin.” PLoS Computational Biology. 2012;8(5):e1002434. Epub 2012 May 3.


Book Chapters

  • Valero-Cuevas FJ. “Why the hand?” Adv Exp Med Biol 629: 553-557, 2009.
  • Valero-Cuevas FJ. “A mathematical approach to the mechanical capabilities of limbs and fingers.” Adv Exp Med Biol 629: 619-633, 2009.
  • Chang J, Valero-Cuevas FJ, Hentz VR and Chase R. Chapter 163: “Anatomy and Biomechanics of the Hand. In Plastic Surgery, Volume VII: The hand and upper limb, Part 1. 2nd Edition. Hentz VR, Editor. Mathes, Series Editor. Saunders, 1005 pp. 2006.


Published Book