MIT creates clothes that can sense movement via touch
April 02, 2021 - United States Of America
Scientists at Massachusetts Institute of Technology have designed clothes that can sense a person’s movement via touch. These can determine whether someone is sitting, walking, or doing particular poses. The team says that these clothes could be used for athletic training and rehabilitation, and even to monitor health of those in assisted-care facilities.
The clothing uses special fibres to sense a person’s movement via touch. The research has been carried out at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL). The scientists say 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.
The team has 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 fibres alongside a small amount of custom-made functional fibres 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 of the paper being published in 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 recognise 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.
The scientists feel a coach can use the sensor to analyse people’s postures and give suggestions on improvement. It could also be used by an experienced athlete to record their posture so that beginners can learn from them. In the long term, they even imagine that robots could be trained to learn how to do different activities using data from the wearables.
“Imagine robots that are no longer tactilely blind, and that have ‘skins’ that can provide tactile sensing just like we have as humans,” says Wan Shou, a postdoc at CSAIL. “Clothing with high-resolution tactile sensing opens up a lot of exciting new application areas for researchers to explore in the years to come.”
The research was partially funded by Toyota Research Institute.
The clothing uses special fibres to sense a person’s movement via touch. The research has been carried out at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL). The scientists say 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.
The team has 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 fibres alongside a small amount of custom-made functional fibres 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 of the paper being published in 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 recognise 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.
The scientists feel a coach can use the sensor to analyse people’s postures and give suggestions on improvement. It could also be used by an experienced athlete to record their posture so that beginners can learn from them. In the long term, they even imagine that robots could be trained to learn how to do different activities using data from the wearables.
“Imagine robots that are no longer tactilely blind, and that have ‘skins’ that can provide tactile sensing just like we have as humans,” says Wan Shou, a postdoc at CSAIL. “Clothing with high-resolution tactile sensing opens up a lot of exciting new application areas for researchers to explore in the years to come.”
The research was partially funded by Toyota Research Institute.