The work of this group is undertaken under four closely connected, but broad, research themes.

Falls monitoring and falls prediction

Both the incidence of falls and the severity of the consequences increase with age. Current body-worn falls-alarms, which alert carers, suffer from poor detection rates. We have shown that a novel approach which is based on posture measurement leads to improved detection. Our aim is to investigate this approach in the elderly and also capture information on the type of fall and any potential recovery. Future work will focus on developing a deployable system and to use information on activity recorded prior to the fall to inform new falls prediction algorithms. This work has involved collaboration Four Seasons Healthcare and with the University of Ulm in Stuttgart.

Development of physical activity outcomes for clinical populations

Outcomes measures, based on physical activity patterns, are being developed to quantify the patterns of behaviour and the effectiveness of interventions in a wide range of clinical groups (including osteoarthritis, stroke and heart failure). These techniques are also being used to enhance our understanding of how physical behaviours in these populations can be affected by environmental and social factors. In this theme, we collaborate extensively with a range of clinical partners.

Physical behaviour and public health

Physical inactivity is a major risk factor for all-cause mortality, coronary heart disease, type 2 diabetes, and breast and colon cancers and physical inactivity is estimated to be responsible for 9% or premature mortality worldwide. The risk of a poor health outcome as a result of physical inactivity, or sedentary behaviour, is similar to the risk for smoking and obesity. However the constructs and definitions of physical activity and sedentary behaviour are ambiguous. The aim of this theme is to develop a model that can provide a unified framework for the terminology and constructs used and to apply this across range of fields from rehabilitation to public health. In addition we have been looking at accepted definitions and measurements of sedentary behaviour and testing this on population survey data. We are also planning an investigation of work based health interventions on physical behaviour.

Physical behaviour in people with dementia

Approximately two thirds of people with dementia live at home and one-third in residential care. With the increase in the ageing population, the number of people with dementia living in residential care is set to rise sharply. Current care home facilities will be unable to cope. We are currently looking at the use of body-worn sensors to monitor the physical behaviour patterns of person with dementia in their own home and use this information to make intelligent decisions about the person’s behaviour which could be communicated to carers and health care workers. This work is being conducted with Salford Institute for Dementia.

Lower limb prosthetics

For a number of years we have been working on methods to characterise the behaviour of prosthetic feet (1, 2), allowing us to identify one of the key problems with passive devices, their inability to provide the positive work seen at the anatomical ankle at push-off (3). This work formed the background to an EPSRC project led by Professor David Howard in which we further developed our analysis methods (4) and demonstrated the potential for hydraulic technology to enable controlled storage, transfer between joints, and return of energy in lower limb prostheses (5). Our results have encouraged us to pursue further work in this area and we are also exploring exploitation routes.

Rig for characterisation of amputee independent prosthesis properties (AIPP).

Upper limb prosthetics

We are taking a similar approach to the design and development of new upper limb prosthetic devices, focusing first on better understanding the problems with myoelectric prostheses. John Head’s PhD thesis investigated the role that poor socket fit can play in determining functional capability (6) and this work has been extended in Alix Chadwell’s PhD work (7).

Reaction time experimental setup used in Chadwell’s PhD.

Functional electrical stimulation

Our group has a long standing interest in the design and development of improved functional electrical stimulation systems. The work dates back to the late 1990s when Professor Laurence Kenney worked in the Netherlands on the development and evaluation of an implantable drop foot stimulator (8), later commercialised under the trade name StimUStep. Since then we have worked on two projects to develop new FES systems. In the first project we worked with the Sheffield team, led by Professor Tony Barker and Dr Ben Heller, on the design of an array-based stimulator with automated setup for dropfoot correction (9), believed to be the world’s first CE marked system of its kind. The first ever take-home study of such a device was led by our group (10) and showed that the technology can be used by patients without technical support. More recently we have been working with Odstock Medical to develop an upper limb functional electrical stimulation system to enable FES-supported functional task practice (11). Through a series of NIHR-funded projects we have progressed to the stage of a regulatory-approved trial of the system.

Upper limb FES system developed by in a collaboration between our group and Odstock Medical.

Advanced kinematics for characterisation of impairment and synthesis of robotic rehabilitation solutions

This area of interest builds on the expertise of our newest member, Dr Gouwu Wei. His background is in advanced robotics and he applies state-of-the-art kinematics to the analysis and synthesis of human movement. He is working to design and develop affordable institutional/domestic assistive robots and rehabilitation devices based on the concept of reconfigurability.

1. Major MJ, Kenney LP, Twiste M, Howard D. Stance phase mechanical characterization of transtibial prostheses distal to the socket: a review. J Rehabil Res Dev. 2012; 49(6):815-29.
2. Major MJ, Twiste M, Kenney LP, Howard D. The effects of prosthetic ankle stiffness on ankle and knee kinematics, prosthetic limb loading, and net metabolic cost of trans-tibial amputee gait. Clin Biomech (Bristol, Avon). 2014;29(1):98-104.
3. Gardiner J, Bari Z, Howard D, Kenney L Energy storage and return prosthetic feet have only marginally improved trans-tibial amputee gait efficiency compared to that with solid ankle cushioned heel feet. J Rehabil Res Dev. 2016;53(6):1133-1138.
4. Weinert-Aplina RA, HowardD, Twiste M, Jarvis HL, Bennett AN, Baker RJ. Energy flow analysis of amputee walking shows a proximally-directed transfer of energy in intact limbs, compared to a distally-directed transfer in prosthetic limbs at push-off. Med Eng Phys. 2017;39:73-82.
5. Gardiner J, Bari Z, Kenney L, Twiste M, Moser D, Zaheedi S, Howard D. Performance of optimised prosthetic ankle designs that are based on a hydraulic variable displacement actuator (VDA). IEEE Trans Neural Sys Rehabil Eng (in press).
6. Head JS, Howard D, Hutchins SW, Kenney L, Heath GH, Aksenov AY. The use of an adjustable electrode housing unit to compare electrode alignment and contact variation with myoelectric prosthesis functionality: A pilot study. Prosthet Orthot Int. 2016;40(1):123-8.
7. Chadwell A, Kenney L, Thies S, Galpin A, Head J. The reality of myoelectric prostheses: Understanding what makes these devices difficult for some users to control. Front Neurorobot 2016; 10:7.
8. Kenney L, Bultstra G, Buschman R, Taylor P, Mann G, Hermens H, et al. An implantable two channel drop foot stimulator: initial clinical results. Artif Organs. 2002;26(3):267-70.
9. Sha N, Kenney LP, Heller BW, Barker AT, Howard D, Moatamedi M. A finite element model to identify electrode influence on current distribution in the skin. Artif Organs. 2008;32(8):639-43.
10. Prenton S, Kenney LP, Stapleton C, Cooper G, Reeves ML, Heller BW, et al. Feasibility study of a take-home array-based functional electrical stimulation system with automated setup for current functional electrical stimulation users with foot-drop. Arch Phys Med Rehabil. 2014;95(10):1870-7.
11. Sun M, Kenney L, Smith C, Waring K, Luckie H, Liu A, Howard D. A novel method of using accelerometry for upper limb FES control. Med Eng Phys. 2016;38(11):1244-1250.

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.

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 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.

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 (http://www.aartbc.org/) (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.

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.