Jose Pons

About

José L. Pons, PhD, is a world-renowned scientist leading a translational research team at Shirley Ryan AbilityLab, focusing on developing advanced methods for measuring and restoring lower-limb function in diverse patient populations. He is a creative engineer with a long-standing history of collaboration with physicians in physical medicine and rehabilitation, and he is best known for his work in wearable robotics and neuroprosthetics as applied to patients with spinal cord injury, stroke, and Parkinsonism. Dr. Pons has authored more than 150 peer-reviewed articles and has developed methods for studying balance and tremor, creating robotic manipulators and mobility devices for children with cerebral palsy, modifying computer cursors for patients with limited mobility, and developing movement sensors for amputees. His expertise in physics enables him to perform fundamental analyses of devices and movement patterns applicable to various movement disorders. Prior to joining Shirley Ryan AbilityLab in 2019, he built his academic career at the Spanish National Research Council (CSIC) in Madrid, where he was director of the Neural Rehabilitation Group in the Department of Translational Neuroscience. Dr. Pons received his BS in mechanical engineering from the University of Navarra and his PhD in physics from Complutense University of Madrid. He is a Fellow of the American Institute of Medical and Biological Engineering (AIMBE) and serves as an associate editor for several…

Research topics

• Computer Science
• Artificial Intelligence
• Human–computer interaction
• Risk analysis (engineering)
• Embedded system
• Simulation
• Data science
• Engineering

Selected publications

• Performance Evaluation of Lower Limb Exoskeletons: A Systematic Review

  IEEE Transactions on Neural Systems and Rehabilitation Engineering · 2020 · 211 citations

  Senior authorCorresponding

  Benchmarks have long been used to verify and compare the readiness level of different technologies in many application domains. In the field of wearable robots, the lack of a recognized benchmarking methodology is one important impediment that may hamper the efficient translation of research prototypes into actual products. At the same time, an exponentially growing number of research studies are addressing the problem of quantifying the performance of robotic exoskeletons, resulting in a rich a…

  DOI

• Human-machine-human interaction in motor control and rehabilitation: a review

  Journal of NeuroEngineering and Rehabilitation · 2021 · 46 citations

  Senior authorCorresponding

  BACKGROUND: Human-human (HH) interaction mediated by machines (e.g., robots or passive sensorized devices), which we call human-machine-human (HMH) interaction, has been studied with increasing interest in the last decade. The use of machines allows the implementation of different forms of audiovisual and/or physical interaction in dyadic tasks. HMH interaction between two partners can improve the dyad's ability to accomplish a joint motor task (task performance) beyond either partner's ability…

  DOI

• A session of transcutaneous electrical nerve stimulation changes the input-output function of motoneurons and alters the sense of force

  Journal of Neurophysiology · 2025-04-08 · 4 citations

  articleOpen accessSenior authorCorresponding

  It is often assumed that transcutaneous electrical nerve stimulation (TENS) has a transient effect on proprioception and motor control. We found that position, force, and touch perception were altered during TENS. However, the sense of force remained altered following TENS. As the discharge rate of motor units also increased in first dorsal interosseus (FDI) and abductor pollicis brevis (APB) muscles for the same force output following TENS, we suggest that their input-output function was altere…

  PublisherDOI

• Deep-Learning Control of Lower-Limb Exoskeletons via Simplified Therapist Input

  2025-05-12 · 3 citations

  articleSenior author

  Partial-assistance exoskeletons hold significant potential for gait rehabilitation by promoting active participation during (re)learning of "normal" walking patterns. Typically, the control of interaction torques in partial-assistance exoskeletons relies on a hierarchical control structure. These approaches require extensive calibration due to the complexity of the controller and user-specific parameter tuning, especially for activities like stair or ramp navigation. To address the limitations o…

  PublisherDOI

• Leveraging neural drive to assess hand motor function in individuals with chronic stroke

  Journal of NeuroEngineering and Rehabilitation · 2026-01-08 · 1 citations

  articleOpen access

  BACKGROUND: Stroke is a leading cause of disability, with up to 80% of survivors experiencing motor impairments. These impairments are attributed to various factors, including reduced neural drive and altered motor unit firing patterns. Rehabilitation aims to restore motor function by enhancing motor unit recruitment and synchronization. High-density electromyography (HD-EMG) is a valuable tool for evaluating these changes in motor unit activity. METHODS: We tested a wearable HD-EMG forearm slee…

  PublisherOA PDFDOI

Recent grants

• NRI: INT: Co-Robot Controllers for Human-Like Physical Interaction and Improved Motor Learning

  NSF · $1.5M · 2020–2025

Frequent coauthors

• Juan C. Moreno

  278 shared

• Diego Torricelli

  184 shared

• Eduardo Rocón

  157 shared

• Filipe Oliveira Barroso

  150 shared

• Yue Wen

  Beijing Institute of Technology

  116 shared

• Dario Farina

  103 shared

• Antonio J. del‐Ama

  Universidad Rey Juan Carlos

  84 shared

• Sangjoon J. Kim

  University of California, Irvine

  82 shared

Awards & honors

• Fellow of the American Institute of Medical and Biological E…

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