Smart Clothes Measure your Movements
09 April 2021: In recent years there have been exciting breakthroughs in wearable technologies, like smartwatches that can monitor your breathing and blood oxygen levels. But what about a wearable that can detect how you move as you do a physical activity or play a sport, and could potentially even offer feedback on how to improve your technique?
And, as a major bonus, what if the wearable were something you’d actually already be wearing, like a shirt of a pair of socks ? That’s the idea behind a new set of MIT-designed clothing that use special fibers to sense a person’s movement via touch. Among other things, the researchers showed that their clothes can actually determine things like if someone is sitting, walking, or doing particular poses. For further information see the IDTechEx report on E-textiles and Smart Clothing 2020-2030: Technologies, Markets and Players.
The group from MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) says that their clothes could be used for athletic training and rehabilitation. With patients’ permission they could even help passively monitor the health of residents in assisted-care facilities and determine if, for example, someone has fallen or is unconscious.
Molex
The researchers have developed a range of prototypes, from socks and gloves to a full vest. The team’s “tactile electronics” use a mix of more typical textile fibers alongside a small amount of custom-made functional fibers that sense pressure from the person wearing the garment.
According to CSAIL graduate student Yiyue Luo, a key advantage of the team’s design is that, unlike many existing wearable electronics, theirs can be incorporated into traditional large-scale clothing production. The machine-knitted tactile textiles are soft, stretchable, breathable and can take a wide range of forms.
“Traditionally it’s been hard to develop a mass-production wearable that provides high-accuracy data across a large number of sensors,” says Luo, lead author on a new paper about the project that is appearing in this month’s edition of Nature Electronics. “When you manufacture lots of sensor arrays, some of them will not work and some of them will work worse than others, so we developed a self-correcting mechanism that uses a self-supervised machine learning algorithm to recognize and adjust when certain sensors in the design are off base.”
The team’s clothes have a range of capabilities. Their socks predict motion by looking at how different sequences of tactile footprints correlate to different poses as the user transitions from one pose to another. The full-sized vest can also detect the wearers’ pose, activity and the texture of the contacted surfaces.
Source: www.printedelectronicsworld.com
