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Novel methods for the evaluation of rehabilitation technologies

Stability of older people whilst using a walking aid

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.Instrumented rollator

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.

Assistive devices and attentional demands

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 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.

Functional task

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.

Characterizing the use of assistive devices

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 ( (4). We have also developed tools to characterise upper limb prosthesis use in the real world (5). Alix Chadwell was awarded the prize for Best Student Presentation for her work on monitoring prosthesis use, when she presented at the prestigious Myoelectric Controls Symposium, hosted by the University of New Brunswick, Canada.

Spiral Plots
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.

Our publications

  1. Costamagna E, Thies S, Kenney L, Howard D, Liu A, Ogden D. A generalizable methodology for stability assessment of walking aid users. Med Eng Phys 2017, 47: 167-175.
  2. Sobuh MM, Kenney LP, Galpin AJ, Thies SB, McLaughlin J, Kulkarni J, Kyberd P. Visuomotor behaviours when using a myoelectric prosthesis. J Neuroeng Rehabil 2014 23;11:72.
  3. Preece SJ, Goulermas JY, Kenney LPJ, Howard D. A comparison of feature extraction methods for the classification of dynamic activities from accelerometer data. IEEE Trans Biomed Eng 2009; 56(3):871-9.
  4. Cheng T, Kenney L, Amor J, Thies S, Costamagna E, James C, Holloway C. Characterisation of rollator use using inertial sensors.  IET Healthcare Letters 2016; 3(4):303-309.
  5. Chadwell A., Kenney L, Granat M, Thies S, Head J, Galpin A. Visualisation of upper limb activity using spirals - A new approach to the assessment of daily prosthesis usage. Pros Orthot Int 2017 :309364617706751.