The main limitation of the clinical based study was the low number of patients recruited into the study (n=6), and subsequently the relatively low number of system uses (n=13). This made it difficult to draw robust conclusions about the influence of therapists’ predisposition to using technology and their actual use of the system. TAM was chosen for this study due to its longstanding evidence base and ease of administration. However, a number of other measures have built on TAM’s success e.g. USUAT, TAM2, and may be more inclusive of the social influences on technology acceptance (Holden & Karsh, 2010). The follow-on study to develop the next iteration of the UL FES Rehab Tool, will build on the authors’ findings to further explore the relationship between therapists behavioural intentions and system usage. The importance of including rehabilitation technologies in therapists’ undergraduate and post graduate education continues to be highlighted if rehabilitation technology is to become part of main stream clinical practice. Future studies could explore the amount and nature of rehabilitation technology that is included in therapist educational programmes in order to address this gap.
The low number of patients exposed to the system also restricted the ability to include the clinical setup time data into the data collected during the lab based testing. Future studies would allow sufficient time for therapists to use the system over a longer period of time, and will include collection of setup time data. Longitudinal studies that capture the realities of using rehabilitation technologies in clinical environments are urgently needed (Hughes et al, 2014). Observing technology usage in early supported discharge environments should also maximise patient recruitment
185 rates and avoid the situation whereby rapid discharge of patients from sub-acute settings makes access to patients problematic.
The clinical study did not utilise a standardised screening tool across both centres which made it difficult to compare patient recruitment rates, and the factors that influenced recruitment patterns. In the future a standardised screening tool will be adopted, to include recording not only patient characteristics, but also their duration of time receiving rehabilitation.
Although the therapists at centre A were very positive about the system, the prototype nature of the UL FES Rehab Tool with its numerous wires and sensors could have influenced therapists’ perception of the technology, particularly at centre B. Therapist have requested that future system be wireless wherever possible. Although the angle triggering system used in this study was an improvement on those used in a previous study (REAcH), further minor modifications could potentially improve the systems functional robustness. The future FES system plans to include biofeedback and patient outcome data to further enhance the benefits available to therapists and patients.
Finally, in cases where patients’ level of upper limb impairment was severe, the muscle activity generated by the FES Rehab Tool was insufficient to overcome the weight of the arm. This impacted on the systems’ ability to reduce the number of therapist required to effectively deliver FES assisted therapy. The next study will explore the use of a de-weighting system in order to maximise the potential of upper limb FES assisted therapy.
7.7 Conclusions
In spite of the prototype nature the UL FES Rehab Tool, it was able to effectively deliver FES assisted upper limb task oriented therapy to a range of stroke patients. The inclusion of biofeedback and clinical outcome data in the next generation of the UL FES Rehab Tool will further enhance its rehabilitation potential.
Although it was challenging to conduct usability evaluations in busy sub-acute clinical environments, where patient turn-over was rapid, the usability methods adopted proved to be invaluable in capturing objective and subjective feedback from therapists, and to some extent patients. This study was the first in the UK to use
186 usability observations to directly observe therapists actually using a complex rehabilitation technology in a sub-acute rehabilitation environment, and to attempt to examine the factors influencing system usage. It adds to the growing body of evidence that highlights the importance of capturing therapist characteristics and in particular their predisposition to using technology (Hughes et al, 2014; Liu et al 2014; Chen & Bode, 2011). These methods can be generalised to other studies seeking to explore the usability of new forms of rehabilitation technologies. Further examination of the best tools and methods to study the factors influencing usage are required. The model to predict setup time for the UL FES Rehab Tool is the first of its kind. Considering the scarcity of resources and the pressure on therapists to deliver rehabilitation programmes, continued development of this model would be advantageous and should help to inform rehabilitation technology usage.
187
8
Chapter 8.0: Summary of the thesis and future work
8.1 Discussion
8.1.1 Introduction
Chronic physical impairment of the hemiplegic upper limb occurs in an estimated 50- 70% of stroke patients (Gebruers et al., 2010). Patients place a high priority on regaining upper limb function (Barker & Brauer, 2005), however current therapy is insufficiently intensive (The Intercollegiate Stroke Working Party, 2014), often not task-oriented and hence poorly aligned with the evidence base. Functional electrical stimulation (FES) has the potential to not only increase the intensity of task-focused therapy (Hughes et al., 2010), but also provide certain unique features, notably direct excitation of lower motor neurons (Rushton, 2003). However, current FES systems are limited in their functionality and/or difficult to use. Systems are also poorly aligned to therapists’ ways of working and as a consequence uptake remains limited. The author’s PhD work ran in parallel with that of a fellow PhD student (Sun, 2014), both of which were aligned with a New and Emerging Assistive Technology (NEAT LO30) grant. Sun’s role was to write the software and develop engineering techniques for robust triggering of the FES system. The author’s role was the usability engineering work that informed the design of the GUI, and the laboratory and hospital based usability evaluation of the UL FES Rehab Tool.
This chapter will summarise the key points covered within the thesis, namely a review of the usability methods employed across all phases and how this compares with the current literature; a summary of the impact that the usability engineering approach had on the final FES system design, and how this has informed the subsequent NIHR i4i funded project; the importance of short setup time for devices and the advantages and challenges of implementing a model to predict setup time in a clinical setting; and finally the importance of education / training in rehabilitation technologies within undergraduate and post graduate curricula as a means of encouraging uptake of rehabilitation technology within main stream, clinical practice.