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I am a Full Professor and the Head of Chair of Neuromuscular Robotics at the University of Twente where I also direct the Neuromechanical Modelling & Engineering Lab. 

My research focuses on understanding how human movement emerges from the interplay between the nervous and the musculoskeletal systems. My goal is to translate such knowledge for the development of symbiotic assistive robots such as exoskeletons and bionic limbs. 

On these topics I have obtained blue-sky research funding including the European Research Council (ERC) Starting Grant, an ERC Consolidator Grant and an ERC Proof of Concept Grant. I have contributed to develop widely used open-source software (e.g., CEINMS, MyoSuite) and I have created patented technology with leading companies (e.g, OttoBock HealthCare).

I conducted my PhD (2009-2011) across the Universities of Padova (Italy), Western Australia (Australia) and Stanford (USA). I continued with a post-doc at the University of Göttingen (Germany, 2011) where I become Junior Research Group Leader in 2015. Since In April 2017 I joined the University of Twente as a tenure-track scientist where I am leading an expanding independent research group.

Throughout my career I received awards (e.g. OpenSim Outstanding Research), was guest editor in academic journals (e.g. IEEE TBME, Front Comput Neurosci), and was Workshop Chair at leading congresses (e.g. IEEE BioRob 2018) in the field.

I am currently chairing the IEEE RAS Technical Committee on BioRobotics. I am Associate Editor at the IEEE Transactions on Neural Systems and Rehabilitation Engineering: https://www.embs.org/tnsre/associate-editors/. Moreover, I am a member of leading scientific societies spanning across the fields of robotics and biomechanics including: IEEE Robotics and Automation Society, IEEE Engineering in Medicine and Biology Society, IEEE International Consortium on Rehabilitation Robotics, and European Society of Biomechanics.

More about me via the UT Featured Scientist page.

Keywords: model-based control; model-based myoelectric control; wearable robot; electromyography; neuromechanics; biomechanics; neuromusculoskeletal modelling; human movement.

Expertise

  • Computer Science

    • Models
    • Control
    • Robotics
  • Medicine and Dentistry

    • Muscle
    • Electromyography
    • Joint
    • Exoskeleton
  • Engineering

    • Joints (Structural Components)

Organisations

For detailed information about my research please visit my research group website. 

My goal is to establish a unique roadmap for discovering fundamental principles of movement at the interface between humans and machines. My research focuses on understanding the neuro-musculo-skeletal mechanisms underlying human movement and how these are altered by impairment. I apply neuro-mechanical modelling and electrophysiological signal processing, in a translational way, to develop real-time model-based control technologies for restoring natural motor function and for enhancing human health.

 

Software Highlights:

  • MyoSuite: An embodied AI platform that unifies neural and motor intelligence Vittorio Caggiano, Huawei Wang, Guillaume Durandau, Massimo Sartori, Vikash Kumar. Link to Website.

 

  • NeurIPS-MyoChallenge 2023: Learning Physiological Agility & Dexterity. Coming up too at this Website. 

 

  • NeurIPS-MyoChallenge 2022: Learning contact-rich manipulation using a musculoskeletal hand. Vittorio Caggiano, Huawei Wang, Guillaume Durandau, Seungmoon Song, Yuval Tassa, Massimo Sartori, Vikash Kumar. Link to Website. 

 

  • MyoSim: Fast and physiologically realistic MuJoCo models for musculoskeletal and exoskeletal studies. Huawei Wang*, Vittorio Caggiano*, Guillaume Durandau, Massimo Sartori, Vikash Kumar. Link to Website. 

 

  • CEINMS: A toolbox to investigate the influence of different neural control solutions on the prediction of muscle excitation and joint moments during dynamic motor tasks. Claudio Pizzolato, David G Lloyd, Massimo Sartori, Elena Ceseracciu, Thor F Besier, Benjamin J Fregly, Monica Reggiani. Link to Website. 

 

  • MOtoNMS: A MATLAB toolbox to process motion data for neuromusculoskeletal modeling and simulation. A Mantoan, C Pizzolato, M Sartori, Z Sawacha, C Cobelli, M Reggiani. Website. 

 

Check out how we interface humans with wearable robot:

Publications

Jump to: 2024 | 2023

2024

Person-specific modelling of α-motoneurons: Towards customized neurorehabilitation (2024)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Ornelas Kobayashi, R. E.https://doi.org/10.3990/1.9789036562911Towards Personalized Motor-Restoring Technologies: Characterizing Neural Data-Driven Alpha-Motoneuron Model Parameters (2024)In 2024 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob) (pp. 1581-1586). Ornelas-Kobayashi, R., Mooiweer, R. & Sartori, M.https://doi.org/10.1109/BioRob60516.2024.10719875Personalized Alpha-Motoneuron Pool Models Driven by Neural Data Encode the Mechanisms Controlling Rate of Force Development (2024)IEEE transactions on neural systems and rehabilitation engineering, 32, 3699-3709. Ornelas-Kobayashi, R., Gomez-Orozco, I., Gogeascoechea, A., Asseldonk, E. V. & Sartori, M.https://doi.org/10.1109/TNSRE.2024.3467692Towards Wearable Electromyography for Personalized Musculoskeletal Trunk Models using an Inverse Synergy-based Approach (2024)[Working paper › Preprint]. bioRxiv. Rook, J. W., Sartori, M. & Refai, M. I.https://doi.org/10.1101/2024.07.23.603973Alpha to Tau: Mapping the Neuromechanical Continuum from α-Motor Neuron Firing Behavior to Joint Torque (2024)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Gogeascoechea, A.https://doi.org/10.3990/1.9789036561853Neuromuscular Modeling for Locomotion with Wearable Assistive Robots -- A primer (2024)[Working paper › Preprint]. ArXiv.org. Refai, M. I., Wang, H., Gogeascoechea, A., Ornelas Kobayashi, R., Avanci Gaudio, L., Damonte, F., Durandau, G. V., van der Kooij, H., Yavuz, U. S. & Sartori, M.https://doi.org/10.48550/arXiv.2407.14289Peak-delay method for estimating the average motor unit action potential conduction velocity (2024)[Dataset Types › Dataset]. Zenodo. Brouwer, N. P., Tabasi, A., Kingma, I., Stegeman, D. F., van Dijk, W., Moya-Esteban, A., Sartori, M. & Dieën, J. H.https://doi.org/10.5281/zenodo.11358224Electromyography-driven musculoskeletal models with time-varying fatigue dynamics improve lumbosacral joint moments during lifting (2024)Journal of biomechanics, 164. Article 111987. Mohamed Refai, M. I., Moya-Esteban, A. & Sartori, M.https://doi.org/10.1016/j.jbiomech.2024.111987Toward a wearable gait lab for the quantitative assessment of musculoskeletal function (2024)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Simonetti, D.https://doi.org/10.3990/1.9789036558853Benchmarking commercially available soft and rigid passive back exoskeletons for an industrial workplace (2024)Wearable Technologies, 5. Article e6. Mohamed Refai, M. I., Moya-Esteban, A., van Zijl, L., van der Kooij, H. & Sartori, M.https://doi.org/10.1017/wtc.2024.2Editorial: Job integration/reintegration of people with neuromuscular disorders in the epoch of “industry 4.0” (2024)Frontiers in neurology, 15. Article 1371430. Ranavolo, A., Ajoudani, A., Bonnet, V., De Nunzio, A. M., Draicchio, F., Sartori, M. & Serrao, M.https://doi.org/10.3389/fneur.2024.1371430Editorial: Rehabilitation robotics: challenges in design, control, and real applications, volume II (2024)Frontiers in neurorobotics, 18. Article 1437717. Romero-Sánchez, F., Menegaldo, L. L., Font-Llagunes, J. M. & Sartori, M.https://doi.org/10.3389/fnbot.2024.1437717

2023

Kinematics, Kinetic and EMG Dataset of overground locomotion with IMUs, optical motion tracking and EMG systems (2023)[Dataset Types › Dataset]. Zenodo. Simonetti, D., Hendriks, M., Koopman, B. F. J. M., Keijsers, N. & Sartori, M.https://doi.org/10.5281/zenodo.8360017Estimating Biological Stiffness Without Relying on External Joint Perturbations: A Musculoskeletal Modeling Framework (2023)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Cop, C. P.https://doi.org/10.3990/1.9789036558426Towards the adoption of wearable exoskeletons in occupational workspaces: model-based assessment and control of back-support exoskeletons (2023)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Moya Esteban, A.https://doi.org/10.3990/1.9789036558389Trunk extensor muscle endurance and its relationship to action potential conduction velocity and spectral parameters estimated using high-density electromyography (2023)Journal of electromyography and kinesiology, 73. Article 102830. Brouwer, N. P., Tabasi, A., Kingma, I., Stegeman, D. F., van Dijk, W., Moya-Esteban, A., Sartori, M. & van Dieën, J. H.https://doi.org/10.1016/j.jelekin.2023.102830A Neuromechanical Model-Based Strategy to Estimate the Operator’s Payload in Industrial Lifting Tasks (2023)IEEE transactions on neural systems and rehabilitation engineering, 31, 4644-4652. Feola, E., Refai, M. I., Costanzi, D., Sartori, M. & Calanca, A.https://doi.org/10.1109/TNSRE.2023.3334993Subject-Specific and COM Acceleration-Enhanced Reflex Neuromuscular Model to Predict Ankle Responses in Perturbed Gait (2023)In 2023 International Conference on Rehabilitation Robotics (ICORR). Avanci Gaudio, L., González-Vargas, J., Sartori, M. & van der Kooij, H.https://doi.org/10.1109/ICORR58425.2023.10304748Synergy-Driven Musculoskeletal Modeling to Estimate Muscle Excitations and Joint Moments at Different Walking Speeds in Individuals with Transtibial Amputation (2023)In 2023 International Conference on Rehabilitation Robotics, ICORR 2023 (IEEE International Conference on Rehabilitation Robotics). IEEE. Damonte, F., Durandau, G., Gonzalez-Vargas, J., Van Der Kooij, H. & Sartori, M.https://doi.org/10.1109/ICORR58425.2023.10304814Adaptive Assistance With An Active And Soft Back-Support Exosuit To Unknown External Loads Via Model-Based Estimates Of Internal Lumbosacral Moments (2023)[Working paper › Preprint]. ArXiv.org. Moya-Esteban, A., Sridar, S., Mohamed Refai, M. I., van der Kooij, H. & Sartori, M.https://doi.org/10.48550/arXiv.2311.01843

Research profiles

In 2016, 2018 and 2023 I was awarded a EU H2020 Marie SkƂodowska-Curie Individual Fellowship (MIMICS) and an ERC Starting Grant (INTERACT) and an ERC Consolidator Grant (ROBOREACTOR) respectively. In 2023 I obtained an ERC Proof of Concept Grant (SMARTSEMS). I am co-leading a EU H2020 Marie SkƂodowska-Curie Innovative Training Network on Bionic Limb Control (SimBionics), an EU-EFRO project on smart sensing garments for stroke rehabilitation (GUTs), an EU H2020 Project of human-robot interaction for injury risk prevention (SOPHIA). I am involved in a NWO Perspectief project on wearable robotics. 

I previously led scientific activities on neuro-mechanical modelling and prosthetic/orthotic technologies on European and National projects including the ERC Advanced Grant DEMOVE (2011-2016), the FP7 EU Project H2R (2013-2016) and the BMBF Innovation Cluster INOPRO (2016-2020). I have served as Scientific Advisory Board member in the FP7 EU Project BioMot (2013-2016). 

Current projects

ROBOREACTOR: Robotic bioreactors for the longitudinal control of restorative remodelling in the human skeletal muscle

Muscle damage impairs vital functions e.g., movement, respiration. Recovery depends on the long-term interaction between neuromuscular and immune systems. If exposed to regimens of electro-mechanical stimuli, damaged muscles can remodel new structural properties over days. Inflammation at the damage site is initially needed to clear debris but if prolonged, as in many neuromuscular disorders, it may hamper structural remodeling. Rehabilitation robots such as exoskeletons and neurostimulators can deliver tunable stimuli to muscles. However, although they can compensate for lack of e.g., muscle strength (within seconds), they cannot control for how muscles remodel across days. ROBOREACTOR shifts the paradigm, to control muscle key inflammation and remodeling factors over large time scales, where the knowledge gap is. 1) I will develop robots that deliver electro-mechanical stimuli to fibres and innervating spinal neurons in humans across weeks. By combining biosignal processing and modeling, I will predict how robot-stimuli influence key inflammation and remodeling processes in vivo, with cell-scale resolution. 2) I will engineer human tissues in vitro and develop robots that can expose tissues to the same stimuli experienced by muscles during robotic training in vivo. This will enable modeling subcellular inflammation and remodeling factors, with detail not attained in humans. 3) I will fit subcellular models in vitro and embed them in multi-scale models built in vivo. This will create new model-based controllers to demonstrate how robots optimize for inflammation to enhance, otherwise hampered remodeling. With a focus on neural and muscular dependences in post-stroke subjects, I propose muscle remodeling as a proxy for neuromuscular repair, a new concept in neurorobotics. This opens to chronic robotic bioreactors, for maintenance of skeletal, cardiac, tubular organs; revisiting fundamental principles of human-robot interaction with broad impact on health.

SMARTSENS: Smart wear for sensing the neuromusculoskeletal system during human movement in vivo

ERC Proof of Concept Grant: Smart wear for sensing the neuromusculoskeletal system during human movement in vivo

Neurological injuries such as stroke or spinal cord injury, leave 5 million people disabled worldwide annually, drastically impairing individuals' ability to move independently. The main element hampering efficacy of current neuro-rehabilitation procedures is the inability of sensing the activity of neural cells involved in the control of movement, along with the movement-generating mechanical force produced by innervated muscle-tendon units, in the intact moving human in vivo. Current technologies for sensing the neuromusculoskeletal system rely on expensive, large, and bulky sensing devices that can only be used in the highly controlled settings of research laboratories. Therefore, a wearable, rapid-to-wear system that could track function in a person’s motor neuron activity along with associated function in muscle, tendon and joint function would revolutionise current neuro-rehabilitation paradigms. SMARTSENS proposes a fully wearable, non-invasive solution to monitor a range of clinically relevant neuromuscular parameters, which currently could only be extracted in constrained laboratory settings via lengthy procedures. SMARTSENS enables measuring such information during daily life activities using a sensorised smart wear that is unobstructive and rapid to wear. This will enable continuous monitoring of the human neuromusculoskeletal system, which will disrupt current movement-measuring and diagnostic systems, by enabling causal understanding of the activity of neural and musculoskeletal structures in vivo at a resolution not considered before.

INTERACT: Modelling the neuromusculoskeletal system across spatiotemporal scales for a new paradigm of humanmachine motor interaction

INTERACT

Neurological injuries such as stroke or spinal cord injury leave millions of people disabled worldwide every year. However, for these individuals recovery is often suboptimal. The impact of current neuro-rehabilitation machines is hampered by limited knowledge of their physical interaction with the human body. Motor recovery requires positive neuro-muscular adaptation to be steered over time. If we could predict such adaptation and control it, to induce a positive change in the future, then a new era in rehabilitation robotics would begin. INTERACT will address this challenge by combining spinal cord electrical-stimulation and robotic exoskeletons with a new class of predictive multi-scale models of the neuromuscular system. This will enable robots to autonomously discover the electro-mechanical stimuli needed for repairing motor function over time. INTERACT will answer fundamental questions in movement neuromechanics via novel principles of human-machine interaction, with broad impact on bioengineering and robotics.

S.W.A.G.: Soft wearable assistive garments for human empowerment

Horizon Europe (CL4-Digital Emerging): Soft wearable assistive garments for human empowerment

Soft robotics has become one of the fastest growing fields over the last decade, and the development of technologies related to the associated modelling, sensing, actuation and control challenges has flourished as part of the field’s impetus. Soft robots have been demonstrated in diverse applications such as wearable devices, mobile or locomotive robots, as well as soft manipulators. Soft lower extremity exoskeletons ( “soft wearable robotics (SWRs)) are one of the most challenging research topics, and require multidisciplinary approaches involving diverse fields such as neuroscience, biomechanics, robot control, ergonomics and other fields. SWAG aims to explore a fundamentally new approach to engineering soft structures that omit fully rigid materials for inflatable ones made from high-strength fabrics and films when manufacturing human-assistive exoskeletal devices that target strainprone segments of the human body (i.e. lower body and core). Such soft wearable adaptive garments with actuation capabilities offer higher variable stiffness and force-to-weight ratios compared to other existing methods, and simultaneously entirely conform to each joint’s intricate kinematics. Because of this, new design approaches can be used as building blocks to realise complete assistance for multi-degree-of-freedom joints, such as the ankle or hip, by adapting flexible and conforming motions achieved by continuum robot designs. SWAG’s advances will demonstrated in 4 different application scenarios. The project brings together 13 partners from 5 EU countries and the UK. The partners consist of an interdisciplinary combination of leading academics with very strong track records in their respective fields. They are supported by RTOs with demonstrated capabilities of developing and validating application-driven solutions, as well as two commercial partners aiming to lead the exploitation of SWAG’s outcomes.

SimBionics

Neuromechanical Simulation and Sensory Feedback for the Control of Bionic Legs

Robotic lower limb prostheses, or bionic legs, have underwent tremendous mechatronic advances in the past decade. However, current prosthesis control interfaces are still sub-optimal leading to inefficient walking. To address this limit, there is need for highly trained professionals that work at the intersection of academic research, clinical assessment and market translation. However, current doctoral training programs do not equip candidates with the complex skillset required to develop prosthetic limbs. SimBionics will establish a comprehensive training program that will equip Early Stage Researchers (ESRs) with the engineering, clinical and entrepreneurial skills required to bring an idea into the market. SimBionics brings together two internationally recognized academic centers, one clinical center and one of the world leading companies in prosthetics. Four ESRs will be trained to develop a radically new control interface that integrates, for the first time, neuromechanical modeling and artificial sensory feedback. This will enable bionic legs to mimic the mechanics of their biological counterparts, so that amputees perceive the prosthesis as an extension of their own body. ESR training will cover all phases of development; from technology conceptualization to translation into a successful product. ESRs will learn to investigate user and stakeholder requirements. They will learn regulatory aspects for medical products, reimbursement mechanisms, intellectual property, and elements that can block successful development. ESRs will thus receive a tailored career development plan including skills acquisition, project/teamwork management, and open science/gender aspects. Outreach activities will be realized to improve public understanding of SimBionics’ socio-economical potentials and clinical benefits. SimBionics will enhance ESRs’ career perspectives and establish a reference for technology development training program.

Finished projects

ExoAid: 'PERSPECTIEF' Programme in Wearable Robotics

The programme 'wearable robotics' is led by UT Professor Herman van der Kooij. This is a national multi-centric project involving Dutch universities and European companies. I am co-responsible for one of the 8 sub-projects constituting the global initiative. The project aims at the development of so-called Exo-Aids: soft, comfortable robot technology supporting smooth and versatile movements. Patients with a damaged spinal cord or loss of muscle power, can come out of their wheelchair and stand up without needing crutches. Another application of wearable robots is preventing job-related injuries, like the lower back pain people are suffering from when doing heavy work.

GUTS: Get under the skin

Over 15 million people suffer from stroke each year worldwide. However, current neuro-rehabilitation treatments are sub-optimal. The main reason is that stroke movement assessment is currently done using subjective and not precise techniques. This project aims at transforming current stroke rehabilitation, based on therapist's subjective assessments, towards personalized treatment based on objective quantitative assessments of muscle function. GUTs will develop a soft and stretchable leg covering for measuring high-density electromyography, joint kinematics and musculoskeletal forces. The availability of this information in the clinics will transform the way a treatment is designed, planned and performed. The project involves a consortium of companies, universities and medical clinics including: the University of Twente, TMSi, Bard.zo, and Sint Maartenskliniek

Electromyography-driven musculoskeletal modelling for biomimetic myoelectric control of prostheses with variable stiffness actuators

Upper limb loss affects 94.000 individuals in Europe. Advanced treatments rely on myoelectric prostheses controlled by amputees’ electromyograms or EMG. Despite expected benefits, today's schemes provide limited re-gain of functionality and lack of bio-mimesis, i.e. they use: (1) direct mapping between EMG and prosthesis joint angle, disregarding underlying neuromusculoskeletal processes, and failing to generalize to unseen conditions (robustness lack), (2) stiff actuators not mimicking biological compliant joints, preventing natural motion (functionality lack). MIMICS proposes a biomimetic paradigm: (1) a modelling formulation that simulates amputee’s phantom limb musculoskeletal dynamics as controlled by EMGs, and (2) prostheses with variable stiffness “soft” actuators. This opens to next-generation “soft” prostheses that can mimic biological limb functionality and robustness; a priority of current European policies and technology roadmaps, with estimated initial markets for functional myoelectric prostheses of €1 billion. MIMICS combines required interdisciplinary skills on soft actuation (host), neuromusculoskeletal modelling (fellow), and clinical bionic reconstruction (secondment). The career development plan is tailored on fellow’s needs: new skills acquisition (soft actuation/clinical prosthetics), project/teamwork management, open science/gender aspects care, ERC grant writing support. The action transfers fellow’s pre-acquired knowledge to the host and opens cooperation with secondment institute, thus increasing host’s visibility in myoelectric control and clinical prosthetics. The secondment expands MIMICS outcomes to boarder clinical perspectives and boosts knowledge transfer among organizations. Outreach activities plan to improve public understanding of MIMICS achievements, socio-economical potentials and clinical benefits. This all is set to improve fellow’s career prospects and form a European network of excellence in neurorehabilitation technologies

H2R: Integrative Approach for the Emergence of Human-like Locomotion

The major drawbacks of existing walking bipeds are related to stability, energy consumption, and robustness to unknown disturbances. In healthy humans, walking emerges naturally from a hierarchical organization and combination of motor control mechanisms. The result of this process is a highly efficient, stable and robust gait. The goal of H2R project is to demonstrate human-like gait and posture in a controlled compliant biped robot as a result of a combination of the most relevant motor control and cognitive mechanisms found in humans. In order to achieve this goal, we will adopt a threefold process: 1. Investigating the human behavior in order to formalize the most crucial biomechanical and neuromotor principles of walking and standing. For more information visit the section Studying humans 2. Testing the formalized biological concepts, by their integration into currently existing robotic platforms. At the same time, we will develop a new biped (namely H2R biped), by iteratively including the components and methods successfully tested. For more information, visit the section Developing robots 3. Giving birth to an internationally validated benchmarking scheme to test the human-like properties of robotic bipeds. This process will strongly rely on worldwide participation of other research groups, through workshops, seminars, and networking activities. For more information, visit the section Benchmarking

INOPRO: Intelligent Orthotics and Prosthetics for Enhanced Human-Machine Interaction (INOPRO)

https://foerderportal.bund.de/foekat/jsp/SucheAction.do?actionMode=view&fkz=13N14909

SOPHIA

Socio-physical Interaction Skills for Cooperative Human-Robot Systems in Agile Production

Collaborative robotics has established itself as a major force in pushing forward highly adaptive and flexible production paradigms in European large and small-medium enterprises. It is contributing to the sustainability and enhancement of Europe’s efficient and competitive manufacturing, to reshoring production, and to economic growth. However, still today the potential of collaborative technologies is largely underexploited. Indeed, collaborative robots are most often designed to coexist and to safely share a working space with humans. They are rarely thought to enter in direct socio-physical contact with humans to perceive, understand, and react to their distress or needs, and to enable them to work more productively and efficiently through better ergonomics. SOPHIA responds to this need by developing a new generation of socially cooperative human-robot systems in agile production. Its modular core technologies will enable dynamic state monitoring of the human-robot pair and anticipatory robot behaviours to: (1) improve human ergonomics, trust in automation, and productivity in manufacturing environments, and (2) achieve a reconfigurable, flexible, and resource-efficient production. By advancing the decisional autonomy and interaction ability of its innovative collaborative systems, SOPHIA will contribute to the reduction of work-related musculoskeletal disorders, the single largest category of work-related injuries and responsible for 30% of all workers’ compensation costs. SOPHIA’s societal relevance and the research groups’ experience in acceptability and standardization aspects of its core technologies will ensure their comfort-of-use by industrial workers, and the underlying design compliance to standards, thus strengthening the competitiveness in European manufacturing. We will illustrate and verify SOPHIA usability through the exploration of three real-world use-cases encouraging potential customers to integrate our core technologies in their workflow.

YOUTUBE:

  • Subscribe to the YouTube channel of my lab to be up to date with our latest research in model-based-control, neuromechanics and wearable robotics. Just follow this link. 

PODCAST:

  • Listen to our podcast on AI-powered Digital Human Twins from this link.

ON DUTCH TV:

  • Watch the NPO2's Focus show on the Ukraine war and amputations featuring our work on bionic legs.

In the press

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University of Twente

Horst Complex (building no. 20), room W111
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