A low cost kinect-based virtual rehabilitation system for inpatient rehabilitation of the upper limb in patients with subacute stroke

Background: We designed this study to prove the efficacy of the low-cost Kinect-based virtual rehabilitation (VR) system for upper limb recovery among patients with subacute stroke. Methods: A double-blind, randomized, sham-controlled trial was performed. A total of 23 subjects with subacute stroke (<3 months) were allocated to sham (n = 11) and real VR group (n = 12). Both groups participated in a daily 30-minute occupational therapy for upper limb recovery for 10 consecutive weekdays. Subjects received an additional daily 30-minute Kinect-based or sham VR. Assessment was performed before the VR, immediately and 1 month after the last session of VR. Fugl-Meyer Assessment (FMA) (primary outcome) and other secondary functional outcomes were measured. Accelerometers were used to measure hemiparetic upper limb movements during the therapy. Results: FMA immediately after last VR session was not different between the sham (46.8 ± 16.0) and the real VR group (49.4 ± 14.2) (P = .937 in intention to treat analysis). Significant differences of total activity counts (TAC) were found in hemiparetic upper limb during the therapy between groups (F2,26 = 4.43; P = .22). Real VR group (107,926 ± 68,874) showed significantly more TACs compared with the sham VR group (46,686 ± 25,814) but there was no statistical significance between real VR and control (64,575 ± 27,533). Conclusion: Low-cost Kinect-based upper limb rehabilitation system was not more efficacious compared with sham VR. However, the compliance in VR was good and VR system induced more arm motion than control and similar activity compared with the conventional therapy, which suggests its utility as an adjuvant additional therapy during inpatient stroke rehabilitation.

[1]  A. Eagger Rehabilitation , 1960 .

[2]  A. Fugl-Meyer,et al.  The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance. , 1975, Scandinavian journal of rehabilitation medicine.

[3]  S. Brunnstrom,et al.  Brunnstrom's Movement Therapy in Hemiplegia: A Neurophysiological Approach , 1992 .

[4]  R. Hébert,et al.  Validation of the Box and Block Test as a measure of dexterity of elderly people: reliability, validity, and norms studies. , 1994, Archives of physical medicine and rehabilitation.

[5]  Fd Rose,et al.  Transfer of Training from Virtual to Real Environments , 1998 .

[6]  R. Nudo,et al.  Effects of Repetitive Motor Training on Movement Representations in Adult Squirrel Monkeys: Role of Use versus Learning , 2000, Neurobiology of Learning and Memory.

[7]  Ruth Dundas,et al.  Estimates of the Prevalence of Acute Stroke Impairments and Disability in a Multiethnic Population , 2001, Stroke.

[8]  J. P. Miller,et al.  Methods for a Multisite Randomized Trial to Investigate the Effect of Constraint-Induced Movement Therapy in Improving Upper Extremity Function among Adults Recovering from a Cerebrovascular Stroke , 2003, Neurorehabilitation and neural repair.

[9]  D. Corbett,et al.  Efficacy of Rehabilitative Experience Declines with Time after Focal Ischemic Brain Injury , 2004, The Journal of Neuroscience.

[10]  Gitendra Uswatte,et al.  Ambulatory monitoring of arm movement using accelerometry: an objective measure of upper-extremity rehabilitation in persons with chronic stroke. , 2005, Archives of physical medicine and rehabilitation.

[11]  E. Taub,et al.  Constraint-induced movement therapy: characterizing the intervention protocol. , 2006, Europa medicophysica.

[12]  Han Young Jung,et al.  Development of the Korean Version of Modified Barthel Index (K-MBI): Multi-center Study for Subjects with Stroke , 2007 .

[13]  J. Kleim,et al.  Principles of experience-dependent neural plasticity: implications for rehabilitation after brain damage. , 2008, Journal of speech, language, and hearing research : JSLHR.

[14]  Yo-Sung Ho,et al.  High-Resolution Depth Map Generation by Applying Stereo Matching Based on Initial Depth Informaton , 2008, 2008 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video.

[15]  D. Reisman,et al.  Observation of amounts of movement practice provided during stroke rehabilitation. , 2009, Archives of physical medicine and rehabilitation.

[16]  J. Verbunt,et al.  Assessment of arm activity using triaxial accelerometry in patients with a stroke. , 2011, Archives of physical medicine and rehabilitation.

[17]  L. Teixeira-Salmela,et al.  Upper extremity function in stroke subjects: relationships between the international classification of functioning, disability, and health domains. , 2011, Journal of hand therapy : official journal of the American Society of Hand Therapists.

[18]  Andrea Turolla,et al.  The effectiveness of reinforced feedback in virtual environment in the first 12 months after stroke. , 2011, Neurologia i neurochirurgia polska.

[19]  K. Chua,et al.  Recovery of upper limb dexterity in patients more than 1 year after stroke: Frequency, clinical correlates and predictors. , 2011, NeuroRehabilitation.

[20]  C. English,et al.  How Physically Active Are People with Stroke in Physiotherapy Sessions Aimed at Improving Motor Function? A Systematic Review , 2012, Stroke research and treatment.

[21]  R. Teasell,et al.  Inpatient rehabilitation following stroke: amount of therapy received and associations with functional recovery , 2012, Disability and rehabilitation.

[22]  Radu Horaud,et al.  High-resolution depth maps based on TOF-stereo fusion , 2012, 2012 IEEE International Conference on Robotics and Automation.

[23]  Jeanette Lee,et al.  Temporal recovery and predictors of upper limb dexterity in the first year of stroke: a prospective study of patients admitted to a rehabilitation centre. , 2013, NeuroRehabilitation.

[24]  Courtney G. E. Hilderman,et al.  Virtual Reality Therapy for Adults Post-Stroke: A Systematic Review and Meta-Analysis Exploring Virtual Environments and Commercial Games in Therapy , 2014, PloS one.

[25]  Lara A. Boyd,et al.  Is More Better? Using Metadata to Explore Dose–Response Relationships in Stroke Rehabilitation , 2014, Stroke.

[26]  M. Schwab,et al.  Finding an optimal rehabilitation paradigm after stroke: enhancing fiber growth and training of the brain at the right moment , 2014, Front. Hum. Neurosci..

[27]  Michael Arens,et al.  Low-cost commodity depth sensor comparison and accuracy analysis , 2014, Security and Defence.

[28]  Peter Eisert,et al.  High-resolution depth for binocular image-based modeling , 2014, Comput. Graph..

[29]  M. Levin,et al.  Emergence of Virtual Reality as a Tool for Upper Limb Rehabilitation: Incorporation of Motor Control and Motor Learning Principles , 2014, Physical Therapy.

[30]  Yeongae Yang,et al.  Effect of computerized cognitive rehabilitation program on cognitive function and activities of living in stroke patients , 2015, Journal of physical therapy science.

[31]  Ramesh Raskar,et al.  Polarized 3D: High-Quality Depth Sensing with Polarization Cues , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[32]  Robert Teasell,et al.  Efficacy and safety of non-immersive virtual reality exercising in stroke rehabilitation (EVREST): a randomised, multicentre, single-blind, controlled trial , 2016, The Lancet Neurology.

[33]  Sungmin Cho,et al.  Upper-Limb Function Assessment Using VBBTs for Stroke Patients , 2016, IEEE Computer Graphics and Applications.

[34]  C. English,et al.  Additional weekend therapy may reduce length of rehabilitation stay after stroke: a meta-analysis of individual patient data. , 2016, Journal of physiotherapy.

[35]  Geoffroy Saussez,et al.  Rehabilitation of Motor Function after Stroke: A Multiple Systematic Review Focused on Techniques to Stimulate Upper Extremity Recovery , 2016, Front. Hum. Neurosci..

[36]  K. Kong,et al.  Efficacy of a Virtual Reality Commercial Gaming Device in Upper Limb Recovery after Stroke: A Randomized, Controlled Study , 2016, Topics in stroke rehabilitation.

[37]  Anders Grunnet-Jepsen,et al.  Intel RealSense Stereoscopic Depth Cameras , 2017, CVPR 2017.

[38]  Domen Novak,et al.  Comparison of two difficulty adaptation strategies for competitive arm rehabilitation exercises , 2017, 2017 International Conference on Rehabilitation Robotics (ICORR).

[39]  L. Ada,et al.  Structure and feasibility of extra practice during stroke rehabilitation: A systematic scoping review , 2017, Australian occupational therapy journal.

[40]  B. Lange,et al.  Virtual reality for stroke rehabilitation. , 2015, The Cochrane database of systematic reviews.

[41]  Pablo Celnik,et al.  A Short and Distinct Time Window for Recovery of Arm Motor Control Early After Stroke Revealed With a Global Measure of Trajectory Kinematics , 2017, Neurorehabilitation and neural repair.

[42]  C. Dean,et al.  Feasibility of a Nurse-Led Weekend Group Exercise Program for People after Stroke , 2017, Stroke research and treatment.