Funding body: Cultural Institute at King's College London / Crafts Council
Funding amount: £8,000
The project was a collaboration between research academics and artists, with an aim build a soft, e-textile garment in which motion and electrophysiological sensors are combined to gain signals from a wearer's movement. Our goal was to design and fabricate both the circuits of the system, as well as parts of the sensors themselves, through embroidery and stitching of conductive thread. These were to form a series of beautiful, textile prototypes that could monitor and collect data from the muscles below the garment. In doing so, we also aimed to extend the practice of both partners, through use of new materials and fabrication approaches and incorporation of aesthetics and function.
During this project numerous sensor designed were created (e.g., embroidered electrodes for electromyographic (EMG) sensing, textile mounts for inertial measurement units), as well as working to solve problems in their fabrication (e.g., how to affix electronic components to textiles, how to form even, raised pads of thread for electrodes). Samples were tested and incorperated into technical designs of supporting circuitry (including flexible printed circuit board design) and PC and microprocessor software was developed for gathering and communicating data for use. To this extent working prototype sensors were produced capable of measuring limb movement and muscle activity, and we demonstrated the first use of embroided EMG sensing in control of a robotic device.
Continuing on from this project, the sensors developed have found continued use in the lab are are currently being used for a number of projects including analysing gait in runners, and low-cost prostesis control.
Articles:
- Future Wearables: Intelligent Leggings Measure Muscle Fatigue in
Runners - MIT Technology Review
https://www.technologyreview.com/s/600908/future-wearables-intelligent-leggings-measure-muscle-fatigue-in-runners/
Publications:
- Wearable embroidered muscle activity sensing device for the human
upper leg, Manero, R. B. R., Shafti, A., Michael, B., Grewal, J.,
Fernandez, J. L. R., Althoefer, K. & Howard, M. J. 13 Oct 2016, IEEE
Engineering in Medicine and Biology Society, EMBS (2015)
- Learning Predictive Movement Models from Fabric-mounted Wearable
Sensors, Michael, B. & Howard, M. J. W. IEEE Transactions on Neural
Systems and Rehabilitation Engineering (2015)
- Eliminating Motion Artifacts from Fabric-mounted Wearable Sensors,
Michael, B. & Howard, M., IEEE International Conference on Humanoid
Robots. , (2014)
