The vast majority of biomechanics research concerned with gait stability has been on unassisted walking. This is surprising, given the high prevalence of walking aid use in the most vulnerable (older old), and because walking with a frame differs significantly from unassisted walking in a number of ways. These include the need to coordinate the movements of the device together with body and foot movements, and significant changes to the base of support over the ‘gait cycle’, both of which make the direct use of unassisted stability measures inappropriate. Through a series of internally and externally funded projects, we have developed a new and objective approach and associated instrumentation to characterising the stability of users of walking aids (1). To date three types of instrumented walking frames (“Smart Walkers”) have been developed and are currently used to assess walking aid users inside the lab and also in their own environment. The work is led by Dr Sibylle Thies, and supported by the PhD Pathways-to-Excellence student Eleonora Costamagna and postdoctoral researcher Alex Bates.
Instrumentation used for stability assessment of 4-wheeled rollator use, including "smart" rollator with integrated load cells, pressure sensing insoles inside the user's shoes, and 3D position tracking of relative foot-frame distance.
In a collaboration with Audrey Bowen (University of Manchester) we explored the question of whether FES to correct drop following stroke impacts on the attentional demands of walking http://usir.salford.ac.uk/29356/. We also work with psychologist (Dr. Adam Galpin), and a Cognitive Neuroscientist, (Dr. Emma Gowen, University of Manchester) to develop improved tools for the evaluation of upper limb prostheses. Specifically, we have used gaze tracking technology to understand patterns of visual attention while using upper limb prostheses (2) and are now carrying out work to characterise embodiment of prostheses.
Example screen shot from gaze tracking system video of a prosthesis user performing a functional task. Note the visual attention to the hand, shown by the location of the red circle.
As our work focuses on restoring functional movement capabilities, we have developed a range of tools based on wearable sensors to better evaluate these devices. Much of the early work, in collaboration with Liverpool University’s Dr Yannis Goulermas, focused on characterising the movement of the person themselves (3). More recently, and in recognition that the ultimate value of an assistive device to the user is reflected in how often and in which circumstances they choose to use their device, we have developed tools to capture this information. We are partners in a £1.8million EPSRC-funded project with University of Warwick, UCL and a number of other universities to develop a system for monitoring of assistive device use (http://www.aartbc.org/) (4). We have also developed tools to characterise upper limb prosthesis use in the real world (5).
Example spiral plots of data collected over 7 consecutive days from 3 axis accelerometers, one worn on each wrist. Plots A and B show data from anatomically intact participants. Plots C and D show data from two users of myoelectric prostheses. More details are available here.