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.

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