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Smart Textiles

Machine learning body movements with SeamSleeve

Garments sense and capture movements much more accurately than is possible using current phones and smart watches.

16th July 2024

Innovation in Textiles
 |  United Kingdom

Medical/Hygiene, Sports/​Outdoor

In the ongoing SeamSleeve project involving researchers from the Universities of Bath and Bristol in the UK, harmless low voltages are being passed through conductive threads which are stitched into garment seams to create electrical circuits. Their resistance changes with the movement of the wearer’s body.

This development opens up new possibilities to make digital clothing that could enhance exercise, physiotherapy and rehabilitation.

“Our research focuses on integrating technology into everyday clothing to track the effectiveness of physiotherapy exercises done at home,” explains Dr Adwait Sharma of the Department of Computer Science at University of Bath.  “Doing these exercises correctly to recover from injuries is crucial, but it’s difficult to know if you’re doing them properly alone. Our SeamSleeve technology helps address this challenge by enabling physiotherapists to monitor the progress remotely. The technology could be particularly beneficial for conditions like Multiple Sclerosis, where monitoring movement is essential. We’ve successfully developed a working system based on machine learning to track 12 different arm exercises using SeamSleeve.”

According to Sharma, current fitness trackers often don’t provide enough detail for physiotherapy. SeamSleeve is unique in that it covers the entire arm, allowing it to capture important movement data.

“We’re excited by the opportunity for clothing manufacturers to implement our designs in sleeves and other garment seams,” adds Professor Mike Fraser from the University of Bristol’s School of Computer Science. “We’ve shown that common overlocked seams in standard garment constructions can do a good job of sensing movement. The design avoids the need for a separate power source by pairing the seam with a charging coil, drawing the energy wirelessly from a mobile phone placed in the pocket. This means advanced motion sensing garments could be made without altering existing manufacturing processes.

“We have also shown that smartphone apps using advanced artificial intelligence techniques can use this movement data to match body movement to specific postures or gestures such as physiotherapeutic exercises.”

www.bath.ac.uk

www.bristol.ac.uk

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