Run with your own twin digital athlete: smart wearables for sensing leg biomechanics in the wild

MSc assignment

Are you passionate about wearable technologies for sensing human movement? Are you interested in developing fully wearable technologies for sensing human biomechanics, out of constrained laboratory conditions and directly in the real world? Join us for an ambitious project across two faculties (ET and EECMS) and three research groups (RAM, BSS, BE) and the UT’s Robotics Centre.  

This is framed as part of the “Mission I.A.M.” initiative (link: www.mission-iam.com), which aims at creating a wearable tech that will monitor biomechanical health continuously during for ultra-marathon races in order to ultimately develop bionic legs that can be used anytime, anywhere, by anyone. We are now targeting developing a prototype ready to be used for the Marathon Des Sables, Jordan edition, on November 1-8, 2025 (https://www.halfmarathondessables.com/jordan). 

 

We will assemble a team of 3 MSc students who will work together over a period of 9 months for the development of (1) re-usable, durable and wearable muscle sensors, (2) minimal sensing setups, (3) digital human twins. 

 

MSc Student 1 – Development of a smart sportswear (e.g., sensorized shoe and socks)  

  • Develop custom re-usable, soft sensors for electro- and force-myography. We have gained experience in multiple previous projects to make customized / personalised flexible and wearable sensors by multi-material 3D printing (see e.g. this project).  
  • Use off the shelf electronics and integrate all sensors into the wearable sportwear, which will also include a processing unit for projects 2-3 algorithms e.g., Raspberry Pi 4.   

Contact: 

 

MSc Student 2 – Minimal off-the-shelf IMU set up for leg kinematics and kinetics 

Your work primarily under the supervision of Frank Wouda. 

You will: 

  • Use existing IMUs in combination with sensor fusion techniques. 
  • Implement sensor to segment calibration. 
  • Implement methods for estimation segment orientations using a small sensor set (e.g., data driven or biomechanically driven). 
  • Implement everything on an embedded system. 
  • Provide required input for project 3. 

Contact: 

 

 

MSc Student 3 – Real-time sensors-driven digital athletes  

You work primarily under the supervision of Massimo Sartori.  

You will: 

  • Use in-house numerical tools such as OpenSim and CEINMS to establish digital human twins i.e., models of the human musculoskeletal system that simulate how our muscles inyteract with our skeletal systemto make us move. 
  • Implement a simple digital human twin on an embedded system (Raspberry Pi). 
  • Use sensors and methods form projects 1-2 to calibrate and drive such digital humans.Validate models accuracy against ground truth data.  

Contact: 

 

Group descriptions: 

BSS: Biomedical Signals and Systems (BSS) is a multidisciplinary group based in Electrical Engineering, focussing on finding solutions for medical challenges via signal and system analysis. Advanced (ambulatory) sensor technology combined with our broad knowledge of the human body as a dynamic system enables (eHealth) technology to improve prevention, diagnosis, and treatment of sensory, motor and internal dysfunction in clinical and home/selfcare setting. Our research helps to improve the quality of life of elderly, people with chronic diseases and rehabilitation patients.

RAM: The Robotics and Mechatronics (RaM) group is active on both fundamental and application-driven topics in the field of robotics. We develop novel fundamental paradigms and physically based methodologies, which we then translate in the Lab into demonstrators and prototypes. The area of robot application is mostly in healthcare and inspection and maintenance. The research is embedded in the TechMed and DSI Institutes. In RAM the NIFTy (Nature Inspired Fabrication & Technology) focusses on the 3D printing of structures with embedded sensors and actuators. The RAM 3D print lab has an extensive array of 3D printers allowing to print from very soft to rather stiff materials. Electrical conductivity is provided by carbon black doped materials like thermoplastic poly urethane (TPU) or poly-lactic acid (PLA). The available 3D printers allow for up to 5 materials to be printed in one print. A more recent and explorative material we are working on is carbon black doped silicone.  

BE’s Neuro-Mechanical Modelling & Engineering Lab: We interface robotic technologies with the neuromuscular system to improve movement. We apply modelling and signal processing, in a translational way, to develop novel real-time bio-inspired assistive technologies. Our goal is to establish a roadmap for discovering fundamental principles of movement at the interface between humans and wearable robots ultimately for improving human health. Check out our pages:  

Robotics Centre: The Robotics Centre: a dynamic hub where research, education, innovation, and broad community intertwine. With our human-centered robotics approach we develop solutions for pressing challenges in healthcare, industry and 

society that improve life. Our innovation centre speeds up R&D through joint innovation roadmaps and consortia, accelerating breakthroughs. We innovate and collaborate with students, researchers, business partners, NGOs, governments, and the media to develop robotic solutions that truly benefit society.