Integrative rehabilitation of elderly stroke survivors: The design and evaluation of the BrightArm™

Purpose: To describe the development of the BrightArm upper extremity rehabilitation system, and to determine its clinical feasibility with older hemiplegic patients. Method: The BrightArm adjusted arm gravity loading through table tilting. Patients wore an arm support that sensed grasp strength and communicated wirelessly with a personal computer. Games were written to improve cognitive, psychosocial and the upper extremity motor function and adapted automatically to each patient. The system underwent feasibility trials spanning 6 weeks. Participants were evaluated pre-therapy, post-therapy, and at 6 weeks follow-up using standardized clinical measures. Computerized measures of supported arm reach and game performance were stored on a remote server. Results: Five participants had clinically significant improvements in their active range of shoulder movement, shoulder strength, grasp strength, and their ability to focus. Several participants demonstrated substantially higher arm function (measured with the Fugl-Meyer test) and two were less-depressed (measured with the Becks Depression Inventory, Second Edition). The BrightArm technology was well-accepted by the participants, who gave it an overall subjective rating of 4.1 on a 5 point Likert scale. Conclusions: Given these preliminary findings, it will be beneficial to evaluate the BrightArm through controlled clinical trials and to investigate its application to other clinical populations. Implications for Rehabilitation It is possible to improve arm function in older hemiplegic patients many years after stroke. Integrative rehabilitation through games combining cognitive (memory, focusing, executive function) and physical (arm movement, hand-eye coordination, grasping, dual-tasking) elements is enjoyable for this population. The severity of depression in the elderly can be reduced through virtual reality games, as long as games adapt to the patient, are winnable and provide rewards for success.

[1]  A. Mirelman,et al.  Effects of Training With a Robot-Virtual Reality System Compared With a Robot Alone on the Gait of Individuals After Stroke , 2009, Stroke.

[2]  Devin Fensterheim,et al.  The Rutgers Arm II Rehabilitation System—A Feasibility Study , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[3]  T. Platz,et al.  Reliability and validity of arm function assessment with standardized guidelines for the Fugl-Meyer Test, Action Research Arm Test and Box and Block Test: a multicentre study , 2005, Clinical rehabilitation.

[4]  C. Spence,et al.  Multisensory contributions to the perception of motion , 2003, Neuropsychologia.

[5]  H. Feys,et al.  Effect of a therapeutic intervention for the hemiplegic upper limb in the acute phase after stroke: a single-blind, randomized, controlled multicenter trial. , 1998, Stroke.

[6]  Andrea Turolla,et al.  Exercises for paretic upper limb after stroke: a combined virtual-reality and telemedicine approach. , 2009, Journal of rehabilitation medicine.

[7]  D. Reinkensmeyer,et al.  Arm-Training with T-WREX After Chronic Stroke: Preliminary Results of a Randomized Controlled Trial , 2007, 2007 IEEE 10th International Conference on Rehabilitation Robotics.

[8]  G. Lankhorst,et al.  Post-stroke depression and functional outcome: a cohort study investigating the influence of depression on functional recovery from stroke , 1999, Clinical rehabilitation.

[9]  F. Mackey,et al.  Examination of shoulder positioning after stroke: A randomised controlled pilot trial. , 2000, The Australian journal of physiotherapy.

[10]  G. Burdea,et al.  Motor Retraining in Virtual Reality: A Feasibility Study for Upper‐Extremity Rehabilitation in Individuals With Chronic Stroke , 2011 .

[11]  Réjean Hébert,et al.  Impact of Motor, Cognitive, and Perceptual Disorders on Ability to Perform Activities of Daily Living After Stroke , 2001, Stroke.

[12]  G. F. Hamilton,et al.  Measurement of grip strength: validity and reliability of the sphygmomanometer and jamar grip dynamometer. , 1992, The Journal of orthopaedic and sports physical therapy.

[13]  A. Hargens,et al.  Effects of dynamic and static handgrip exercises on hand and wrist volume , 2008, European Journal of Applied Physiology.

[14]  MSc DPhil Ian Palmer BSc Essential Java 3D fast , 2001, Essential Series.

[15]  Luciano Gamberini,et al.  Controlling Memory Impairment in Elderly Adults Using Virtual Reality Memory Training: A Randomized Controlled Pilot Study , 2010, Neurorehabilitation and neural repair.

[16]  Jeonghun Ku,et al.  A Virtual Reality System for the Assessment and Rehabilitation of the Activities of Daily Living , 2003, Cyberpsychology Behav. Soc. Netw..

[17]  Grant D. Huang,et al.  Robot-assisted therapy for long-term upper-limb impairment after stroke. , 2010, The New England journal of medicine.

[18]  R. H. Jebsen,et al.  An objective and standardized test of hand function. , 1969, Archives of physical medicine and rehabilitation.

[19]  Qinyin Qiu,et al.  Learning in a Virtual Environment Using Haptic Systems for Movement Re-Education: Can This Medium Be Used for Remodeling other Behaviors and Actions? , 2011, Journal of diabetes science and technology.

[20]  S. G. Nelson,et al.  Reliability of the Fugl-Meyer assessment of sensorimotor recovery following cerebrovascular accident. , 1983, Physical therapy.

[21]  Alexander W Dromerick,et al.  Estimating minimal clinically important differences of upper-extremity measures early after stroke. , 2008, Archives of physical medicine and rehabilitation.

[22]  S. Cavanagh,et al.  Grading Scales Used in the Management of Aneurysmal Subarachnoid Hemorrhage: A Critical Review , 2002, The Journal of neuroscience nursing : journal of the American Association of Neuroscience Nurses.

[23]  C. Patten,et al.  Exercise interventions for smokers with a history of alcoholism: exercise adherence rates and effect of depression on adherence. , 2003, Addictive behaviors.

[24]  Ralph H. B. Benedict,et al.  Hopkins Verbal Learning Test--Revised , 2013 .

[25]  E. D. de Haan,et al.  Cognitive Disorders in Acute Stroke: Prevalence and Clinical Determinants , 2007, Cerebrovascular Diseases.

[26]  A Väljamäe,et al.  Filling-in visual motion with sounds. , 2008, Acta psychologica.

[27]  R. Härkönen,et al.  Accuracy of the Jamar dynamometer. , 1993, Journal of hand therapy : official journal of the American Society of Hand Therapists.

[28]  Christopher J. Ferguson,et al.  Gender, Video Game Playing Habits and Visual Memory Tasks , 2008 .

[29]  Jacqueline Kerr,et al.  Exergames for subsyndromal depression in older adults: a pilot study of a novel intervention. , 2010, The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry.

[30]  Philippe Coiffet,et al.  Virtual Reality Technology , 2003, Presence: Teleoperators & Virtual Environments.

[31]  Michael D. Justiss,et al.  Grip Strength in the Frail Elderly , 2004, American journal of physical medicine & rehabilitation.

[32]  C. S. Green,et al.  Action video game modifies visual selective attention , 2003, Nature.

[33]  Soha Saleh,et al.  Robotically facilitated virtual rehabilitation of arm transport integrated with finger movement in persons with hemiparesis , 2011, Journal of NeuroEngineering and Rehabilitation.

[34]  Birgitta Lindmark,et al.  Self-efficacy in relation to impairments and activities of daily living disability in elderly patients with stroke: a prospective investigation. , 2003, Journal of rehabilitation medicine.

[35]  P. Feys,et al.  The Armeo Spring as training tool to improve upper limb functionality in multiple sclerosis: a pilot study , 2011, Journal of NeuroEngineering and Rehabilitation.