The provision of feedback through computer-based technology to promote self-managed post-stroke rehabilitation in the home

Abstract Purpose: Building on previous research findings, this article describes the development of the feedback interfaces for a Personalised Self-Managed Rehabilitation System (PSMrS) for home-based post-stroke rehabilitation using computer-based technology. Method: Embedded within a realistic evaluative methodological approach, the development of the feedback interfaces for the PSMrS involved the incorporation of existing and emerging theories and a hybrid of health and social sciences research and user-centred design methods. Results: User testing confirmed that extrinsic feedback for home-based post-stroke rehabilitation through computer-based technology needs to be personalisable, accurate, rewarding and measurable. In addition, user testing also confirmed the feasibility of using specific components of the PSMrS. Conclusions: A number of key elements are crucial for the development and potential utilisation of technology in what is an inevitable shift towards the use of innovative methods of delivering post-stroke rehabilitation. This includes the specific elements that are essential for the promotion of self-managed rehabilitation and rehabilitative behaviour change; the impact of the context on the mechanisms; and, importantly, the need for reliability and accuracy of the technology. Implications for Rehabilitation To promote independent self-managed post-stroke rehabilitation in the home, feedback needs to be personalisable, simplistic, rewarding and measurable. Specific elements of feedback are required to achieve improved performance, confidence and self-efficacy, and the reinforcement of rehabilitative behaviour change. The provision of feedback through technology needs to be reliable and accurate.

[1]  P. Langhorne,et al.  Motor recovery after stroke: a systematic review , 2009, The Lancet Neurology.

[2]  Anne Mandy,et al.  Changing self-efficacy in individuals following a first time stroke: preliminary study of a novel self-management intervention , 2009, Clinical rehabilitation.

[3]  Francesco Piccione,et al.  Reinforced Feedback in Virtual Environment Facilitates the Arm Motor Recovery in Patients after a Recent Stroke , 2007, 2007 Virtual Rehabilitation.

[4]  Jane Burridge,et al.  A pilot study to investigate the association between muscle activation patterns, wrist tracking performance and upper limb function in post-stroke hemiplegia , 2009 .

[5]  Huiru Zheng,et al.  Author ' s response to reviews Title : Stroke patients ' utilisation of extrinsic feedback from computer-based technology in the home : a realistic evaluation , 2013 .

[6]  S. Spaulding,et al.  Motor Learning and the Use of Videotape Feedback After Stroke , 2007, Topics in stroke rehabilitation.

[7]  Adri Hartveld,et al.  Augmented Feedback and Physiotherapy Practice , 1996 .

[8]  Fiona Jones,et al.  Strategies to enhance chronic disease self-management: How can we apply this to stroke? , 2006, Disability and rehabilitation.

[9]  Huosheng Hu,et al.  The SMART project: A user led approach to developing applications for domiciliary stroke rehabilitation , 2006 .

[10]  Xin Feng,et al.  Potential of a suite of robot/computer-assisted motivating systems for personalized, home-based, stroke rehabilitation , 2007, Journal of NeuroEngineering and Rehabilitation.

[11]  Huiru Zheng,et al.  Stroke patients’ utilisation of extrinsic feedback from computer-based technology in the home: a multiple case study realistic evaluation , 2014, BMC Medical Informatics and Decision Making.

[12]  S. Brauer,et al.  Upper limb recovery after stroke: The stroke survivors' perspective , 2005, Disability and rehabilitation.

[13]  G. Wulf,et al.  Extrinsic feedback for motor learning after stroke: What is the evidence? , 2006, Disability and rehabilitation.

[14]  M. Woollacott,et al.  Motor Control: Translating Research into Clinical Practice , 2006 .

[15]  M. Levin,et al.  Virtual Reality in Stroke Rehabilitation: A Systematic Review of its Effectiveness for Upper Limb Motor Recovery , 2007, Topics in stroke rehabilitation.

[16]  Peter Robinson,et al.  Designing accessible technology , 2006, Universal Access in the Information Society.

[17]  Peter C. Wright,et al.  User-centered design for supporting the self-management of chronic illnesses: an interdisciplinary approach , 2009, PETRA '09.

[18]  Mark Hallett,et al.  Recent Advances in Stroke Rehabilitation , 2002, Neurorehabilitation and neural repair.

[19]  Lorie G. Richards,et al.  Movement-dependent stroke recovery: A systematic review and meta-analysis of TMS and fMRI evidence , 2008, Neuropsychologia.

[20]  M. Dijkers,et al.  Toward a taxonomy of rehabilitation interventions: Using an inductive approach to examine the "black box" of rehabilitation. , 2004, Archives of physical medicine and rehabilitation.

[21]  Elizabeth Kendall,et al.  Recovery following stroke: the role of self-management education. , 2007, Social science & medicine.

[22]  M. Levin,et al.  Systematic Review of the Evidence Does Provision of Extrinsic Feedback Result in Improved Motor Learning in the Upper Limb Poststroke ? , 2009 .

[23]  L. Turner-Stokes,et al.  The Depression Intensity Scale Circles (DISCs): a first evaluation of a simple assessment tool for depression in the context of brain injury , 2005, Journal of Neurology, Neurosurgery & Psychiatry.

[24]  Kerstin Tham,et al.  Characteristics of physiotherapy sessions from the patient's and therapist's perspective , 2004, Disability and rehabilitation.

[25]  Jack Parker,et al.  A review of the evidence underpinning the use of visual and auditory feedback for computer technology in post-stroke upper-limb rehabilitation , 2011, Disability and rehabilitation. Assistive technology.

[26]  Huiru Zheng,et al.  Developing a personalised self-management system for post stroke rehabilitation; utilising a user-centred design methodology , 2014, Disability and rehabilitation. Assistive technology.

[27]  K. Lorig,et al.  Self-management education: History, definition, outcomes, and mechanisms , 2003, Annals of behavioral medicine : a publication of the Society of Behavioral Medicine.

[28]  Derick T Wade,et al.  Somatosensory recovery: A longitudinal study of the first 6 months after unilateral stroke , 2007, Disability and rehabilitation.

[29]  Peter Robinson,et al.  Designing inclusive interactions , 2013, Universal Access in the Information Society.

[30]  H. Krebs,et al.  Effects of Robot-Assisted Therapy on Upper Limb Recovery After Stroke: A Systematic Review , 2008, Neurorehabilitation and neural repair.

[31]  Susan Michie,et al.  Developing and Evaluating Complex Interventions , 2015 .

[32]  L. Kalra,et al.  Recent advances in stroke rehabilitation 2006. , 2007, Stroke.

[33]  J. Krakauer Motor learning: its relevance to stroke recovery and neurorehabilitation. , 2006, Current opinion in neurology.

[34]  Michelle J. Johnson,et al.  Advances in upper limb stroke rehabilitation: a technology push , 2011, Medical & Biological Engineering & Computing.

[35]  Jack Parker,et al.  An Investigation into Stroke Patients’ Utilisation of Feedback from Computer-based Technology , 2010 .

[36]  P. Verschure,et al.  New Technologies and Concepts for Rehabilitation in the Acute Phase of Stroke: A Collaborative Matrix , 2007, Neurodegenerative Diseases.

[37]  S. McEwen,et al.  Exploring the feasibility and efficacy of a telehealth stroke self-management programme: a pilot study. , 2009, Physiotherapy Canada. Physiotherapie Canada.

[38]  C. Wolfe,et al.  Cost-Effectiveness of Stroke Unit Care Followed by Early Supported Discharge , 2009, Stroke.

[39]  C. Mathers,et al.  Preventing stroke: saving lives around the world , 2007, The Lancet Neurology.

[40]  C Ballinger,et al.  Unpacking the black box of therapy – a pilot study to describe occupational therapy and physiotherapy interventions for people with stroke , 1999, Clinical rehabilitation.

[41]  Fadhel Kaboub Realistic Evaluation , 2004 .

[42]  W. Harwin,et al.  The effect of the GENTLE/s robot-mediated therapy system on arm function after stroke , 2008, Clinical rehabilitation.

[43]  R. Magill Motor learning and control : concepts and applications , 2004 .

[44]  Richard A. Schmidt,et al.  Motor learning and performance : a situation-based learning approach , 2008 .

[45]  Huiru Zheng,et al.  Developing and testing a telerehabilitation system for people following stroke: issues of usability , 2010 .

[46]  Afsane Riazi,et al.  Self-efficacy and self-management after stroke: a systematic review , 2011, Disability and rehabilitation.