👉 Fuzzy-Based Sensor Fusion for Cognitive Load Assessment in Inclusive Manufacturing Strategies
At its core, this study looks at how we can make manufacturing environments more inclusive—starting from people with neurodiverse profiles like dyslexia (the easiest to simulate with healthy participants), and laying down the framework to help all types of neuroatypical operators.
We designed a system that uses wearable sensors to track things like heart rate, electrodermal activity, and eye movement while participants completed assembly tasks. Then we fed that data into a fuzzy logic model to estimate their cognitive load—basically, how mentally demanding each task was.
Oh, and yes—we used Duplo bricks for the assembly tasks. A great excuse to bring colourful plastic blocks into the lab and call it serious science. No regrets. ;-)
Some of what we found:
🧠 Cognitive load shoots up when no support is provided in text-heavy tasks
🔊 Audio instructions helped reduce this load noticeably
🤖 Robotic assistance actually led to lower and more stable mental effort than human help
🏭 And even neurotypical participants showed signs of overload when tasks became harder
This kind of research is all about pushing forward inclusive practices in real-world, practical ways—designing systems that help people think better, not harder.
Thanks to our brilliant team across Loughborough University and Politecnico di Torino for making this happen.