A study from King's College London has found that tracking devices attached to loose clothing measure human movement more accurately than those placed on tight-fitting suits or straps. The findings, published in Nature Communications, may impact the development of personal health devices and improve motion capture technology for industries such as film and robotics.
Researchers discovered that loose fabric can predict and record body movements with 40% greater accuracy while requiring 80% less data compared to sensors fixed directly on the skin. This suggests potential improvements for technologies like fitness trackers and smart watches, as well as applications in healthcare research for conditions that affect mobility.
Dr Matthew Howard, a co-author of the study and reader in engineering at King's College London, explained: "When we think about technology that tracks movement - like a Fitbit on your wrist or the suits actors wear to play CGI characters - we had thought that the sensors need to be tight against the body to produce the most accurate results. The common belief is that if a sensor is loose, the data will be 'noisy' or messy."
"However, our research has proven over multiple experiments that loose, flowing clothing actually makes motion tracking significantly more accurate. Meaning, we could move away from 'wearable tech' that feels like medical equipment and toward 'smart clothing' - like a simple button or pin on a dress - that tracks your health while you feel completely natural going about your day."
The study found that loose fabric acts as a "mechanical amplifier," making it easier for sensors to detect movement. Dr Howard added: "when you start to move your arm, a loose sleeve doesn't just sit there; it folds, billows, and shifts in complex ways - reacting more sensitively to the movements than a tighter fitting sensor."
This approach could make wearable health monitoring less intrusive by embedding sensors into everyday items like shirt buttons instead of relying on bulky devices.
Dr Irene Di Giulio, senior lecturer in anatomy and biomechanics at King's College London and co-author of the study, said: "Sometimes, a patient's movements are too small for a tight wristband to catch and therefore we can't always get the most accurate data on how conditions like Parkinson's are affecting people's everyday lives."
"Through this approach we could 'amplify' people's movement, which will help capture them even when they are smaller than typical abled-bodied movements. This could allow us to track people in the comfort of their own homes or a care home, in their everyday clothing. It could become easier for doctors to monitor their patients, as well as medical researchers to gather vital data needed to inform our understanding of these conditions and develop new therapies including wearable technologies that cater for these kinds of disabilities."
Dr Howard noted further implications for robotics: "A lot of robotics research is about learning from human behaviour for robots to mimic, but to do this you need huge amounts of data collected from every day human movements, and not many people are willing to strap up in a Lycra suit and go about their daily business."
"This research offers the possibility of attaching discreet sensors to everyday clothing, so we can start to collect the internet-scale of human behavior data, needed to revolutionize the field of robotics."
