MIT develops smart clothing using tactile fabric perception for motion

2024-01-17

In recent years, wearable technology has made exciting breakthroughs, such as smartwatches that can monitor breathing and blood oxygen levels. But what if there is a wearable device that can detect your movements during sports activities or activities, and may even provide feedback on improving sports skills?

The smart clothing developed by MIT CSAIL can be used for sports training, rehabilitation, or health monitoring in elderly care institutions by measuring a person's movements and posture. Thisthe idea behind MIT's design of a new set of clothes, which uses special fibers to sense human movement through touch. In other aspects, researchers have shown that their clothing can actually determine certain things, such as whether someone is sitting, walking, or doing a specific posture.

A team from the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology said that their clothes can be used for exercise training and rehabilitation. With the patient's consent, they can even help passively monitor the health status of personnel in assistive care facilities and determine if someone has fallen or lost consciousness.

Researchers have developed a series of prototypes, ranging from socks and gloves to complete vests. The team's "tactile electronics" technology uses a combination of typical textile fibers and a small amount of customized functional fibers that can sense the pressure on the wearer. Unlike many existing wearable electronic devices, this team's design has a key advantage that their designs can be incorporated into traditional large-scale clothing production. Machine woven tactile textiles are soft, stretchable, breathable, and can take various forms.

Traditionally, it has been difficult to develop a large-scale wearable device that provides high-precision data on a large number of sensors. So researchers have developed a self correcting mechanism that uses self supervised machine learning algorithms to identify and adjust biases in certain sensors in the design. The team's clothing has a range of functions. Their socks predict movement by observing how different tactile sequences are associated with different postures when users transition from one posture to another. The full-size vest can also detect the wearer's posture, movement, and texture of the contact surface.

The author envisions a coach using this sensor to analyze people's postures and provide improvement suggestions. Experienced athletes can also use it to record their posture, so that beginners can learn from them. In the long run, they can even imagine that robots are no longer tactile blind spots, their skin can provide tactile sensing, just like us humans, can be trained to use wearable device data to learn different types of movements.

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