The discovery could mark a potential breakthrough for a range of technologies, including improving accuracy on personal health devices, such as Fitbits and smart watches, to enhancing motion capture for CGI movie characters.
It could also support health and medical research by making it easier to gather data on conditions affecting mobility such as Parkinson’s. The research is detailed in Nature Communications.
The research found that loose fabric can predict and capture the body’s movements with 40 per cent more accuracy and needing 80 per cent less data, than if a sensor were stuck to skin.
In a statement, co-author Dr Matthew Howard, a reader in engineering at KCL, said: “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 research found that loose fabric acts like a ‘mechanical amplifier, making movement easier to detect.
“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,” said Dr Howard.
According to KCL, this could bring smart clothing one step closer, with the potential to add sensors to buttons on shirts as a discrete alternative to existing devices.
The researchers also believe the findings have potential to transform the field of robotics research as well as automated technologies that use gesture-based control to turn on the lights or a tap.
Scientists tested sensors on a wide range of different fabrics with human and robot subjects undertaking a variety of different movements.
They compared results from the loose-fabric method with conventional motion sensors fixed to straps and tight-fitting garments, and found the fabric-based approach consistently identified movements faster, with greater accuracy, and using less data to generate predictions.
Looser fabric was also able to distinguish between very similar or subtle, barely detectable movements.
Co-author Dr Irene Di Giulio, senior lecturer in anatomy and biomechanics at KCL, 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.
“This breakthrough means we could 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, an expert in robotics research, believes this work could transform data collection on human mobility to develop better, smarter robots.
“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,” he explained.
“This research offers the possibility of attaching discreet sensors to everyday clothing, so we can start to collect the internet-scale of human behaviour data, needed to revolutionise the field of robotics.”