Assistant Professor at the crossroads of AI and sensing techniques applied to space biomechanics and wearable robotics. I am part of the Neuromechanical Engineering Chair.  

I have extensive background in musculoskeletal modeling for real-time applications, sensor fusion for wearable biomechanics, and data-driven approaches for biomechanics. This helps me identify how we can explore novel methodologies for movement sensing in extreme environments by fusing model-based and data-driven approaches. 


  • Nursing and Health Professions

    • Measurement
    • Error
    • Pressure
  • Medicine and Dentistry

    • Foot
    • Gait
    • Exoskeleton
    • Position
    • Workplace


I have built my research career around different themes within assistive biomechanics.  Currently, I am an Assistant Professor with Prof. Massimo Sartori within the Neuromechanical Engineering chair. My focus is towards fusing data-driven and model-based approaches for sensing and assisting movement in extreme environments (Space for example). 

During my postdoctoral research, I worked with two EU Horizon projects SOPHIA ( and SWAG (SWAG ( The SOPHIA project developed real-time personalized musculoskeletal models (also accounting for fatigue) to understand the impact of and provide assistance to back support exosuits. Within the SWAG project, we will extend the musculoskeletal models to capture biological joint stiffness during gait. 

During my Ph.D., I worked within a Dutch NWO project AMBITION with Dr. Bert-Jan van Beijnum, Prof. Peter Veltink, and Prof. Jaap Buurke to develop a reduced wearable IMU set to measure movement quality after stroke. The study advanced the state of the art in measuring movement post stroke, and also extended the capabilities of wearable technology for this aspect. 

I was formally trained as a Biomedical Engineer during my Bachelor's and as an Electrical Engineer during my Master's. 


A Neuromechanical Model-Based Strategy to Estimate the Operator’s Payload in Industrial Lifting Tasks, 4644-4652. Feola, E., Refai, M. I., Costanzi, D., Sartori, M. & Calanca, A. Assistance With An Active And Soft Back-Support Exosuit To Unknown External Loads Via Model-Based Estimates Of Internal Lumbosacral Moments. Moya-Esteban, A., Sridar, S., Mohamed Refai, M. I., van der Kooij, H. & Sartori, M. into skeletal muscle biomechanics for design and control of lower-limb exoskeletons: A narrative review, 318-333. Mahdian, Z. S., Wang, H., Refai, M. I., Durandau, G. V., Sartori, M. & MacLean, R. Wearable sensing of movement quality after neurological disorders, Article 1156520. Mohamed Refai, M. I., van Beijnum, B. J. F., Buurke, J. H., Shull, P. B. & Veltink, P. H. fatigue tracking using electromyography driven musculoskeletal models. Refai, M. I. & Sartori, M.Does a Soft Actuated Back Exosuit Influence Multimodal Physiological Measurements and User Perception During an Industry Inspired Task?In 2023 International Conference on Rehabilitation Robotics, ICORR 2023. IEEE. Refai, M. I. M., Sridar, S., Govaerts, R., Chini, G., Varrecchia, T., Del Ferraro, S., Falcone, T., De Bock, S., Molinaro, V., Elprama, S. A., Jacobs, A., Ranavolo, A., De Pauw, K., van der Kooij, H. & Sartori, M.

Research profiles

Master courses                                                                                     

  • Biomechatronics (Course 201200133): Taught lectures on electromyography processing, neuromusculoskeletal modelling, robotic control interfaces, sensor fusion (Kalman Filtering), inertial navigation, and its applications in literature. Created assignments that applied these concepts, graded students, and conducted exams on this topic. 
  • Technology for Health (Course 201500222): Served as Capita Selecta Lecturer, and expert/instructor for the topic ‘Ambulatory sensing’ and evaluated final grant proposals.
  • Research Experiments in Databases and Information Retrieval (Course 201300074): Served as project supervisor. Instructed students with applying machine learning models on inertial data to classify activities such as reaching, and evaluated their final report.

Bachelor courses                                                                                  

  • Meten is Weten (To Measure is to Know; Course 202000840): Taught the Programming module. Students learnt how to use python from scratch and use it in other aspects of the course.
  • De Bewegende Mens en Gezondheidsrecht (The Moving Human and Health Law; Course 202000825): Instructor for the Motion Capture practical. Setup laboratory and drafted manual for equipment such as Qualisys motion tracker, Force plates, Delsys EMG systems, and Biodex dynamometer for Bachelor students. Will be involved in evaluating experimental protocols, and final course reports.
  • Biorobotics (Course 201800178): Coached and assisted students with programming embedded sensors using C# and MicroPython during their robot building project. 

Affiliated study programs

Courses academic year 2023/2024

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.

Courses academic year 2022/2023

Current projects


Soft Wearable Assistive Garments for Human Empowerment

The SWAG project is a multidisciplinary initiative in the field of soft robotics, focusing on the development of lower limb exosuits: soft wearable exoskeletal robots to empower the lower body and core. The project aims to replace traditional rigid materials found in exoskeletons, with high-strength, inflatable fabrics and sensing films to create smart, human-assistive, soft and lightweight garments. The envisioned exosuits will ensure user comfort and safety, while remaining virtually undetected, invisible under clothing due to their garment-like design. SWAG exosuits will empower humans in activities from occupational assistance to daily mobility, fitness and immersive entertainment. SWAG involves 13 partners from six EU countries and the UK, including leading academics, Research and Technology Organisations and two commercial partners.

Finished projects



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

The H2020-ICT10 project SOPHIA – Socio-physical Interaction Skills for Cooperative Human-Robot Systems in Agile Production – aims to create a new generation of core robotic technologies for socially cooperative human-robot systems. The objectives are to achieve a reconfigurable and resource-efficient production and improve human comfort and trust in automation, in hybrid human-plus-robot manufacturing environments. SOPHIA core intelligence will enable timely, natural, and human-in-command interactions between humans and robots on both social (e.g., geometric reasoning and situation assessment; knowledge models for human-robot mixed teams; natural and multi-modal dialogue; and human-aware task planning) and physical (e.g., sharing physical loads) levels, representing the new concept of socio-physical interaction. Additionally, the design and development of novel under-actuated wearable exoskeletons and collaborative robots with high payload and advanced loco-manipulation capacities are central to the mechatronics developments of the SOPHIA project. SOPHIA has a clear focus on standardization of its advanced technologies at a European level. It includes a large network of Digital Innovation Hubs for agile manufacturing (Trinity, DIH2, Flanders Make, DIH Umbria) and healthcare (DIHero) to ensure that its core technologies are “compliant by design” to standards in the field of human-robot interaction and collaboration.


University of Twente

Horst Complex (building no. 20), room W117
De Horst 2
7522 LW Enschede

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