In collaboration with other colleagues at Nottingham Trent University and the University of Nottingham, the ATRG have published a new research article ‘Classifying gait alterations using an instrumented smart sock and deep learning’. The article describes the measurement of gait using two sock that incorporate a series of three E-yarns embedded with accelerometers each. Machine learning was then used to identify gait patterns linked to different movement disorders. Such a sock may prove to be useful for clinicians to monitor gait pattern alterations remotely during gait rehabilitation. The article was published in the IEEE Sensors Journal and is available here.
Manufacturing Electronic Yarns 