A Cognitive-Balance Control Training Paradigm Using Wii Fit to ...

4 downloads 0 Views 703KB Size Report
Oct 9, 2017 - Background and purpose: The impaired ability to maintain balance while performing higher-level cognitive tasks (cognitive-motor interference) ...
RESEARCH ARTICLES

A Cognitive-Balance Control Training Paradigm Using Wii Fit to Reduce Fall Risk in Chronic Stroke Survivors Savitha Subramaniam, PT, MS, Christina Wan-Ying Hui-Chan, PT, PhD, and Tanvi Bhatt, PT, PhD

Background and Purpose: The impaired ability to maintain balance while performing higher-level cognitive tasks (cognitive-motor interference) significantly predisposes stroke survivors to risk of falls. We investigated adherence and intervention-related effects of gaming to improve balance control and decrease cognitive-motor interference in stroke survivors. Methods: Community-dwelling individuals with hemiparetic stroke (N = 8) received balance control training using Wii Fit in conjunction with cognitive training for approximately 110 min/d for 5 consecutive days. Changes in balance and cognitive performance were evaluated by the limits of stability test performed under single-task (ST) and dual-task (DT) conditions. The outcome measures from the limits of stability test included reaction time and movement velocity of the center of pressure. The cognitive performance was quantified by the number of errors. The DT cost was computed for the balance and cognitive outcome measures using [(ST − DT)/ST × 100]. Adherence was assessed by change on the Intrinsic Motivation Inventory scores postintervention. No commercial party having a direct financial interest in the research findings reported here has conferred orwill confer. Results: Posttraining, reaction time cost in the forward direction improved from 31 ± 8.02 to ±8.7 ± 6.6. Similarly, movement velocity cost improved from 33.7 ± 12.3 to 11 ± 1. Cognitive cost also decreased from 47.9 ± 13.9 to 20 ± 18.8. There were similar improvements in the backward direction for all the outcome measures. Scores on the Intrinsic Motivation Inventory improved from 16.6 ± 1.3 to 23.5 ± 1.5. Discussion and Conclusions: The results demonstrate good adherence and evidence of clinical value of this high-intensity, shortduration protocol for reducing cognitive-motor interference and improving balance control in stroke survivors. Future studies should examine the dose-response effects and long-term changes of such DT training paradigm applied to improve fall efficacy. Department of Physical Therapy, University of Illinois at Chicago. No commercial party having a direct financial interest in the research findings reported here has conferred or will confer a benefit on the authors or on any organization with which the authors are associated. Supplemental digital content is available for this article. Direct URL citation appears in the printed text and is provided in the HTML and PDF versions of this article on the journal’s Web site (www.jnpt.org). The authors declare no conflicts of interest. Correspondence: Tanvi Bhatt, PT, PhD, Department of Physical Therapy, University of Illinois at Chicago, 1919, W Taylor St (M/C 898), Chicago, IL 60612 ([email protected]). C 2014 Neurology Section, APTA. Copyright  ISSN: 1557-0576/14/3804-0216 DOI: 10.1097/NPT.0000000000000056

216

Video Abstract available. See Video (Supplemental Digital Content 1, http://links.lww.com/JNPT/A80) for more insights from the authors. Key words: balance, balance and stroke, cognition, dual task (JNPT 2014;38: 216–225)

INTRODUCTION

S

troke is one of the major causes of adult disability, leading to dependence in activities of daily living, with more than 800 000 incidences per year.1,2 A stroke event causes a number of impairments that contribute toward poor balance,3 leading to a decreased functional status and increased disability.4 Forty percent to 70% of community-dwelling stroke survivors experience detrimental falls each year5 and tend to have 1.5 to 4 times higher risk of hip fracture than their healthy counterparts; with only less than 40% of those individuals regaining independent mobility. Falls thus not only affect activities of daily living but also hamper community reintegration.6 Recent studies7 demonstrate that virtual reality (VR) rehabilitation, in comparison with conventional methods, provides enhanced sensory feedback about movement characteristics and improves both motor task learning and execution.8 Virtual reality rehabilitation methods offer highly customizable, controllable, multimodal simulations that give the subject high levels of motivation and adherence and a strong sense of presence in the virtual environment.9,10 These methods could, potentially, allow more engaging forms of interventions to be accessed under reduced supervision, along with increased functional recovery.11 Despite the advantages, because of high costs, VR systems are still unavailable in many rehabilitation settings.12 Off-the-shelf, low-cost video gaming systems such as Wii Fit (Nintendo Co, Ltd. Kyoto, Japan) and Kinect (Microsoft, Inc., Redmond, WA, U.S.A) provide the stroke survivor a similar environment and effectiveness in balance rehabilitation compared with VR systems13 across various rehabilitation settings.9,14 For example, balance training using Wii Fit has been shown to result in significant improvements in static and dynamic balance control, which corresponds with functional improvements.13 Although balance control rehabilitation is fundamental, recent findings indicate that impairments in cognitive function poststroke may interfere with community mobility and reintegration. In persons with stroke performing a motor and cognitive task concurrently, if both the tasks share the same attentional resources (due to an overlap in structural cortical JNPT r Volume 38, October 2014

Copyright © 2014 Neurology Section, APTA. Unauthorized reproduction of this article is prohibited.

JNPT r Volume 38, October 2014

Dual-Task Training Paradigm

networks15 ) or if they are limited (due to age-related deterioration or pathologically compromised central nervous system16 ), performance on either one or both of the tasks is reduced (cognitive-motor interference). Because of the stroke-induced cortical lesion, there is a decrease in capacity of processing resources and the cognitive-motor interference is significantly greater,17 especially while performing the physical task concurrently with a cognitive task that challenges working memory or executive abilities.18 These findings suggest that integrating cognitive-motor rehabilitation might be crucial in addressing balance recovery among chronic stroke survivors. Although dual-task (DT) training (training in performance of motor task with a concurrent cognitive task) in various populations such as older adults,19 persons with Parkinson disease,18 and persons with traumatic brain injury21 has been very promising in improving balance control, there is little research on effects of such rehabilitation in stroke survivors. Recent research demonstrates that rehabilitation strategies with DT might produce an efficient integration of the 2 tasks22 and “automate” the performance of the primary motor task,23 providing resources to focus on other tasks.24,25 In this study, we examined a novel and cost-effective cognitive-motor training paradigm, comprising Wii Fit gaming performed in conjunction with various higher-order cognitive tasks, to lay the foundation for a multidimensional treatment paradigm. This could subsequently be translated into a home therapy program, contributing to economical health care management. The purpose of this study was to investigate the adherence and intervention-induced effects of such training in improving intentional balance control under DT conditions. We hypothesized that there would be a significant decrease, in both balance and cognitive costs, when comparing post- with pretraining values, along with significantly greater scores on Intrinsic Motivation Inventory (IMI) postintervention.

METHODS Subjects Eight ambulatory adults with self-reported chronic hemiparetic stroke were recruited after obtaining informed consent, approved by institutional review board of the University of Illinois. Demographics of the stroke subjects are shown in Table 1.

Subject Eligibility Subjects with hemiparetic stroke (>6 months, without any presence of aphasia) as confirmed by participants’ physi-

cian were included. They were required to have the ability to stand independently for at least 5 minutes without the use of an assistive device and no incidence of falls in last 6 months. Participants with cognitive deficits, as measured by the Short Orientation-Memory-Concentration test of cognitive impairment (ie, >8), were excluded.26 Short Orientation-MemoryConcentration is also positively correlated with screening tests for aphasia, suggesting that individuals with higher score on the Short Orientation-Memory-Concentration test would show worse language functioning.27 Subjects’ mean ± SD disability status, quantified using the Modified Rankin Scale, ranged from mild to moderate disability (2.62 ± 0.51) (Table 1). Three of the subjects reported having slipped during their activities of daily living but were able to regain balance with external support. Participants with other neurological (eg, Parkinson disease, vestibular deficits, peripheral neuropathy, or unstable epilepsy) and musculoskeletal disorders were excluded. Individuals with cardiovascular disorders as assessed by resting heart rate (>85% of age-predicted maximal) and resting oxygen saturation (50% of the variance due to intervention, indicating large practical significance.

DISCUSSION The results supported our hypothesis that there would be a significant decrease in both balance and cognitive costs posttraining, suggesting an improvement in these functions and corresponding decrease in cognitive-motor interference. Furthermore, as hypothesized, subjects’ adherence to intervention

 C 2014 Neurology Section, APTA

Copyright © 2014 Neurology Section, APTA. Unauthorized reproduction of this article is prohibited.

219

Subramaniam et al

JNPT r Volume 38, October 2014

Figure 2. Change in pre- and posttraining scores of individual subject performance under dual-task condition on the limits of stability test for reaction time (RT) in seconds (A and B), movement velocity (MV) in degrees per second (C and D), maximum excursion (MXE) in percentage, and directional control (DC) in percentage. The left panel represents the forward (Fwd) direction (A, C, E, and G), and the right panel represents the backward (Bwd) direction (B, D, F, and H).

220

 C 2014 Neurology Section, APTA

Copyright © 2014 Neurology Section, APTA. Unauthorized reproduction of this article is prohibited.

JNPT r Volume 38, October 2014

Dual-Task Training Paradigm

Figure 3. Means and standard deviations for the pre- and posttraining costs (in percentage) for reaction time (RT) cost (A and B), movement velocity (MV) cost (C and D), maximum excursion (MXE) cost (E and F), directional control (DC) (G and H). The cost for each variable represents the difference in performance on the limits of stability test between single-task and dual-task conditions. The left panel represents the forward (Fwd) direction (A, C, E, and G) and the right panel represents the backward (Bwd) direction (B, D, F, and H).

was maintained and postintervention motivation was significantly greater. There was a significant improvement in training-induced performance on the Wii Fit game scores, suggesting that subjects acquired the ability to successfully execute the balancerelated requirements of the gaming tasks: weight shifting, sym-

metric foot stepping, controlled movements near the limits of stability, and adequate attention, memory, and decisionmaking skills. In addition, the game scores (results) on each trial provided performance feedback to the subjects, which may have facilitated their decision making for improving performance on subsequent trials.42 This reinforcement could

 C 2014 Neurology Section, APTA

Copyright © 2014 Neurology Section, APTA. Unauthorized reproduction of this article is prohibited.

221

JNPT r Volume 38, October 2014

Subramaniam et al

Figure 4. Pre- and posttraining scores (correct responses) for individual subjects for the counting backward (CB) task under dual-task condition for the (A) forward (Fwd) and (B) backward (Bwd) directions. The means and standard deviations of the cognitive (Cog) cost in percentage are also presented for the (C) forward and (D) backward directions. The cognitive cost represents the difference between the single-task (seated only) and dual-task conditions.

be particularly important for adherence to therapeutic activities in community-dwelling stroke survivors with reduced motivation levels for rehabilitation programs.9,14 Significantly improved scores on the IMI postintervention further lend support to the aforementioned findings. Better performance on the games indeed translated to an improvement in balance control under DT conditions. Postintervention, subjects decreased DT cost in temporal (reaction time), spatial (movement velocity, maximum excursion, and directional control), and cognitive abilities, indicating improved performance in these functions. These improvements could have been a result of better allocation of cognitive resources, which might have further facilitated attentional control when performing cognitive tasks concurrently with balance activities. Recent research recommends VR training to promote improved integration of motor and cognitive skills for improving physical function.43 However, other evidence indicates that although VR interfaces allow for improved body awareness, movement processing, and overall motor skill acquisition, they do not provide sufficient cognitive stimulation for addressing higher-order functions such as working memory and executive abilities.44,45 In fact, some studies have discussed the difficulties in transferring cognitive skills trained by video games to real tasks.46,47 This study thus explored a combined cognitive-motor training paradigm, consisting of behavioral training focused on improving higher-order cognitive skills along with balance skills.

222

Table 2. The Means (and Standard Deviations) for the Wii Fit Balance Gaming Scores for Day 1, Day 3, and Day 5

Table tilt Tightrope Soccer Balance bubble a b

Day 1

Day 3

Day 5

19.41 (3.97) 21.66 (6.44) 9.58 (2.84) 72.91 (16.65)

31.95 (8.21) 23.37 (10) 11.95 (3.14) 139 (68.10)

35.66 (5.16)a 33.37 (5.42)a 13.20 (1.79)a 135.12 (30.19)b

P < 0.05, between day 1 and day 5. P < 0.01, between day 1 and day 5.

Until recently, cognitive training and its influence on motor behavior received little attention. A decline in cognitive function was related to irreversible structural changes associated with aging or pathology, rather than a clinical symptom that could benefit from rehabilitation.48,49 A recent study by Chapman et al50 has demonstrated significant plasticityinduced improvements in cortical activations after a 12-week, 1 h/wk, cognitive training intervention in a group of older adults. The study demonstrated significant gains in resting state activation and increased connectivity and structural integrity in the default mode network (a brain system that corresponds to task introspection and active in the absence of focused task performance) and the central executive network (regions of the brain active while performing executive functions). We believe that DT training utilized in this study challenged higher-order functions including working memory and semantic memory, which could have led to greater provision of attentional  C 2014 Neurology Section, APTA

Copyright © 2014 Neurology Section, APTA. Unauthorized reproduction of this article is prohibited.

JNPT r Volume 38, October 2014

Dual-Task Training Paradigm

Table 3. Means (and Standard Deviations) of Pre- and Postintervention Scores for the Secondary Outcome Measures Mean (SD)

BBS (/56) TUG, s IMI (/25)

Pretest

Posttest

P

46.5 (3.46) 20.28 (2.4) 16.875 (1.35)

49.12 (3.13) 17.42 (1.39) 23.62 (1.30)

0.001 0.001 0.000

Abbreviations: BBS, Berg Balance Scale; IMI, Intrinsic Motivation Inventory; TUG, Timed Up and Go.

resources toward improving both balance control and cognitive performance while performing these tasks concurrently. Given the gradual and progressive decline in working memory, especially in the chronic stages poststroke, such training could have significant impacts to slow this decline. Recovering from stroke involves relearning complex balance tasks requiring stability and mobility in the presence of motor and cognitive deficits. Individuals with stroke therefore use greater attentional resources to perform activities previously performed skillfully. In other words, these activities will be performed at an associative or cognitive stage as opposed to autonomous stage.14 When the benefits of movement automation are lost, balance control can be expected to be more vulnerable to cognitive distractions (cognitive-motor interference), subsequently increasing the risk of falls.51,52 Consequently, the central element of successful cognitive-motor rehabilitation for stroke survivors should be designed to compensate for damaged cortical regions through the activation of compensatory reserves. Also, as balance control centers in the brainstem are postulated to be influenced by descending cortical inputs, addressing practice-induced plasticity changes in these networks may decrease cognitive-motor interference and improve DT capacity.18,24,53 Interventions should therefore focus on higher-order cognitive functions such as working memory and executive function,18 and provide physical activities with decision-making opportunities to facilitate the complex cognitive processing required for community living.24 Improved performance posttraining, as indicated by a decrease in both balance and cognitive costs, suggests that DT rehabilitation challenging higher-order functions could promote automaticity of the DT performance. Although the entire intervention was conducted over a week, the overall dosage of approximately 9 hours of training is similar to many other protocols that are spread over longer durations. Also, recent rehabilitation research has shown the importance of high-intensity, short-duration training in improving functional recovery in people who have had a stroke.14,53,54 The post-intervention improvement of 2.6 for the Berg Balance Scale and 2.9s for the Timed up and Go test, were greater or equal to the minimal detectable change of 2.5 for Berg Balance Scale and 2.9s for Timed Up and Go test respectively established for people with chronic stroke. This suggests that the post-intervention change in outcome measures could indeed be a meaningful clinical change that can lower fall-risk in this population. These results further support to shorter-term

effects of such high-intensity training protocols, lend further support to shorter-term effects of such high-intensity training protocols.55 While most current literature on adherence to participation includes intervention durations ranging from a few months to years, our study duration was only for a week. To have a wider application of this approach in stroke survivors, future studies should explore dosage requirements for individuals at different stages of recovery, specifically addressing long-term adherence to the protocol and retention of traininginduced changes. Overall, the effect sizes in our study resulted in >50% of the variance due to intervention, indicating medium to large improvement in both balance and cognitive costs. Similar effects were also seen in the gaming scores, Berg Balance Scale, Timed Up and Go, and Intrinsic Motivation Inventory scores post-training. This indicates relevant clinical significance and promotes the importance of integrating this paradigm into a clinical treatment program and assessing it’s efficacy for translation into a home therapy program.

Limitations The present study design did not provide any estimation of learning or maturation trends during pretest due to the lack of interrupted time-series design. However, previous literature on reliability studies for the limits of stability test demonstrates no learning effects when the test is used for assessment once the patient is sufficiently familiarized with the procedure prior to data collection.29,56,57 Thus, as part of our study design, we provided 2 familiarization trials before the actual testing, ensuring that the test was highly reliable and did not have any maturation trends during the balance testing. Furthermore, baseline tests were done on day 1, followed by the intervention phase from day 4 to day 8, and postintervention assessment performed on day 11 to ensure a sufficient time interval between preassessment, intervention, and postassessment. The lack of control group in the study might pose a threat to its internal validity. However, the study protocol was designed to address this limitation. It was ensured that the training games selected for intervention used a wide range of balance control mechanisms, such as lateral weight shifting (Soccer and Tightrope game), and controlling the displacement and variability of their center of pressure within their existing base of support (Table tilt and balance bubble). Further to minimize the threat to internal validity, the pre- and postassessments were, however, conducted on the limits of stability test specifically in the forward and backward directions. Similarly, the cognitive task used for the DT assessment was different than the tasks used for training. Furthermore, subjects did not participate in any other physical activity or therapeutic interventions other than carrying on their typical activities of daily living. The pre- and postassessment sessions were performed at the same time of the day. Nonetheless, future studies should also compare balance improvements between equal doses of Wii Fit training with and without dual tasking to determine whether the improvement in balance control is purely due to the DT gaming paradigm or due to the high-intensity Wii Fit training session.

 C 2014 Neurology Section, APTA

Copyright © 2014 Neurology Section, APTA. Unauthorized reproduction of this article is prohibited.

223

Subramaniam et al

CONCLUSIONS The dual-task training paradigm proposed in this study could effectively promote the ability to maintain optimal function on balance and cognitive tasks under challenging ‘real life’ circumstances without compromising compliance to the practice schedule. Further studies with larger sample sizes are needed to assess efficacy of this intervention for potential translation into a clinical treatment program.

ACKNOWLEDGMENTS The authors thank the American Heart Association, National Affiliate, for the Scientific Development Grant (PI, Dr Bhatt). The authors also thank Kaitlyn Reinwald for editing the manuscript, Tejal Kajrolkar for assisting with the data collection, and Prakruti Patel for her thoughtful comments on the manuscript. REFERENCES 1. Grimby G, Andren E, Daving Y, Wright B. Dependence and perceived difficulty in daily activities in community-living stroke survivors 2 years after stroke: a study of instrumental structures. Stroke. 1998;29(9):18431849. 2. Mathers C, Boerma T. The Global Burden of Disease. Geneva, Switzerland: World Health Organization; 2004. 3. Gresham GE, Fitzpatrick TE, Wolf PA, McNamara PM, Kannel WB, Dawber TR. Residual disability in survivors of stroke—the Framingham study. New Engl J Med. 1975;293(19):954-956. 4. Mol VJ, Baker CA. Activity intolerance in the geriatric stroke patient. Rehabil Nurs. 1991;16(6):337-343. 5. Belgen B, Beninato M, Sullivan PE, Narielwalla K. The association of balance capacity and falls self-efficacy with history of falling in community-dwelling people with chronic stroke. Arch Phys Med Rehabil. 2006;87(4):554-561. 6. Baseman S, Fisher K, Ward L, Bhattacharya A. The relationship of physical function to social integration after stroke. J Neurosci Nurs. 2010;42(5):237-244. 7. Deutsch JE MM, Kafri M, Ranky R, Sivak M, Mavroidis C, Lewis JA. Feasibility of virtual reality augmented cycling for health promotion of people poststroke. J Neurol Phys Ther. 2013;37(3):118-124. 8. Todorov E, Shadmehr R, Bizzi E. Augmented feedback presented in a virtual environment accelerates learning of a difficult motor task. J Mot Behav. 1997;29(2):147-158. 9. Celinder D, Peoples H. Stroke patients’ experiences with Wii Sports(R) during inpatient rehabilitation. Scand J Occup Ther. 2012;19(5):457-463. 10. Moreira MC, de Amorim Lima AM, Ferraz KM, Benedetti Rodrigues MA. Use of virtual reality in gait recovery among post stroke patients—a systematic literature review. Disabil Rehabil Assist Technol. 2013;8(5): 357-362. 11. Rand D KR, Weiss PT. The Sony PlayStation II EyeToy: low-cost virtual reality for use in rehabilitation. J Neurol Phys Ther. 2008;32(4):155-163. 12. Cho KH, Lee KJ, Song CH. Virtual-reality balance training with a videogame system improves dynamic balance in chronic stroke patients. Tohoku J Exp Med. 2012;228(1):69-74. 13. Lange B, Flynn S, Proffitt R, Chang C-Y, Rizzo AS. Development of an interactive game-based rehabilitation tool for dynamic balance training. Top Stroke Rehabil. 2010;17(5):345-352. 14. Saposnik G, Mamdani M, Bayley M, et al. Effectiveness of Virtual Reality Exercises in STroke Rehabilitation (EVREST): rationale, design, and protocol of a pilot randomized clinical trial assessing the Wii gaming system. Int J Stroke. 2010;5(1):47-51. 15. Lundin-Olsson L, Nyberg L, Gustafson Y. Attention, frailty, and falls: the effect of a manual task on basic mobility. J Am Geriatr Soc. 1998;46(6):758-761. 16. Montero-Odasso M, Verghese J, Beauchet O, Hausdorff JM. Gait and cognition: a complementary approach to understanding brain function and the risk of falling. J Am Geriatr Soc. 2012;60(11):2127-2136.

224

JNPT r Volume 38, October 2014

17. Plummer P, Eskes G, Wallace S, et al. Cognitive-motor interference during functional mobility after stroke: state of the science and implications for future research. Arch Phys Med Rehabil. 2013;94(12):2565-2574. 18. Cicerone KD, Dahlberg C, Kalmar K, et al. Evidence-based cognitive rehabilitation: recommendations for clinical practice. Arch Phys Med Rehabil. 2000;81(12):1596-1615. 19. Theill N, Schumacher V, Adelsberger R, Martin M, Jancke L. Effects of simultaneously performed cognitive and physical training in older adults. Arch Phys Med Rehabil. 2000;81(12):1596-1615. 20. Fok P, Farrell M, McMeeken J. The effect of dividing attention between walking and auxiliary tasks in people with Parkinson’s disease. Hum Mov Sci. 2012;31(1):236-246. 21. Fritz NE, Basso DM. Dual-task training for balance and mobility in a person with severe traumatic brain injury: a case study. J Neurol Phys Ther. 2013;37:37-43. 22. Glasauer S, Stein A, G¨unther AL, Flanagin VL, Jahn K, Brandt T. The effect of dual tasks in locomotor path integration. Ann N Y Acad Sci. 2009;1164:201-205. 23. Ruthruff E, Van Selst M, Johnston JC, Remington R. How does practice reduce dual-task interference: integration, automatization, or just stageshortening? Psychol Res. 2006;70(2):125-142. 24. Robertson IH, Murre JM. Rehabilitation of brain damage: brain plasticity and principles of guided recovery. Psychol Bull. 1999;125(5): 544-575. 25. Collette F, Van der Linden M. Brain imaging of the central executive component of working memory. Neurosci Biobehav Rev. 2002;26(2): 105-125. 26. Katzman R, Brown T, Fuld P, Peck A, Schechter R, Schimmel H. Validation of a short Orientation-Memory-Concentration Test of cognitive impairment. Am J Psychiatry. 1983;140(6):734-739. 27. AI-Khawaja I, Wade D, Collin CF. Bedside screening for aphasia: a comparison of two methods. J Neurol. 1996(243):201-204. R System Limits of Stabil28. NeuroCom. The NeuroCom Smart EquiTest ity Test—Clinical Interpretation Guide. Clackamas, OR: NeuroCom; 2009. 29. Clark S, Rose DJ. Evaluation of dynamic balance among communitydwelling older adult fallers: a generalizability study of the limits of stability test. Arch Phys Med Rehabil. 2001;82(4):468-474. 30. Chien CW, Hu M-H, Tang P-F, Sheu C-F, Hsieh CL. A comparison of psychometric properties of the smart balance master system and the postural assessment scale for stroke in people who have had mild stroke. Arch Phys Med Rehabil. 2007;88(3):374-380. 31. Liston RA, Brouwer BJ. Reliability and validity of measures obtained from stroke patients using the Balance Master. Arch Phys Med Rehabil. 1996;77(5):425-430. 32. Wallmann HW. Comparison of elderly nonfallers and fallers on performance measures of functional reach, sensory organization, and limits of stability. J Gerontol A Biol Sci Med Sci. 2001;56(9):M580-M583. 33. Au-Yeung SS, Ng JT, Lo SK. Does balance or motor impairment of limbs discriminate the ambulatory status of stroke survivors? Am J Phys Med Rehabil. 2003;82(4):279-283. 34. Alonte A GK, Brenneman SK. Relationship of scores on the Berg Balance Scale to results of the limits of stability portion of the Smart Balance R suite of tests. Neurol Rep. 1995:19:22-23. Master 35. Allison LK, Rose DJ. The relationship between postural control system impairments and disabilities in older adults. Phys Ther. 1998;78:5. 36. Unsworth N, Engle RW. The nature of individual differences in working memory capacity: active maintenance in primary memory and controlled search from secondary memory. Psychol Rev. 2007;114(1):104-132. 37. Medalia A, Saperstein A. The role of motivation for treatment success. Schizophr Bull. 2011;37(2):122-128. 38. Ryan RM, Connell JP, Plant RW. Emotions in non-directed text learning. Learn Individ Diff. 1990(2):1-17. 39. Plant RW, Ryan RM. Intrinsic motivation and the effects of selfconsciousness, self-awareness, and ego-involvement: an investigation of internally-controlling styles. J Pers Soc Psychol. 1985(53):435-449. 40. McAuley E, Duncan T, Tammen VV. Psychometric properties of the Intrinsic Motivation Inventory in a competitive sport setting: a confirmatory factor analysis. Res Q Exerc Sport. 1989;60(1):48-58. 41. Bock O. Dual-task costs while walking increase in old age for some, but not for other tasks: an experimental study of healthy young and elderly persons. J Neuroeng Rehabil. 2008;5:27.

 C 2014 Neurology Section, APTA

Copyright © 2014 Neurology Section, APTA. Unauthorized reproduction of this article is prohibited.

JNPT r Volume 38, October 2014

42. Brown P, Chen CC, Wang S, et al. Involvement of human basal ganglia in offline feedback control of voluntary movement. Curr Biol. 2006;16(21):2129-2134. 43. Kim BR, Chun MH, Kim LS, Park JY. Effect of virtual reality on cognition in stroke patients. Ann Rehabil Med. 2011;35(4):450-459. 44. Pompeu JE, Mendes FA, Silva KG, et al. Effect of Nintendo Wiibased motor and cognitive training on activities of daily living in patients with Parkinson’s disease: a randomised clinical trial. Physiotherapy. 2012;98(3):196-204. 45. dos Santos Mendes FA, Pompeu JE, Modenesi Lobo A, et al. Motor learning, retention and transfer after virtual-reality-based training in Parkinson’s disease—effect of motor and cognitive demands of games: a longitudinal, controlled clinical study. Physiotherapy. 2012;98(3): 217-223. 46. Basak C, Boot WR, Voss MW, Kramer AF. Can training in a real-time strategy video game attenuate cognitive decline in older adults? Psychol Aging. 2008;23(4):765-777. 47. Boot WR, Basak C, Erickson KI, et al. Transfer of skill engendered by complex task training under conditions of variable priority. Acta Psychol (Amst). 2010;135(3):349-357. 48. Reuter-Lorenz PA, Lustig C. Brain aging: reorganizing discoveries about the aging mind. Curr Opin Neurobiol. 2005;15(2): 245-251. 49. Mahncke HW, Bronstone A, Merzenich MM. Brain plasticity and functional losses in the aged: scientific bases for a novel intervention. Prog Brain Res. 2006;157:81-109.

Dual-Task Training Paradigm

50. Chapman SB, Aslan S, Spence JS, et al. Neural mechanisms of brain plasticity with complex cognitive training in healthy seniors [published online ahead of print August 28, 2013]. Cereb Cortex. doi:10.1093/cercor/bht234. 51. Barra J, Bray A, Sahni V, Golding JF, Gresty MA. Increasing cognitive load with increasing balance challenge: recipe for catastrophe. Exp Brain Res. 2006;174(4):734-745. 52. Broglio SP, Tomporowski PD, Ferrara MS. Balance performance with a cognitive task: a dual-task testing paradigm. Med Sci Sports Exerc. 2005;37(4):689-695. 53. Liepert J, Bauder H, Wolfgang HR, Miltner WH, Taub E, Weiller C. Treatment-induced cortical reorganization after stroke in humans. Stroke. 2000;31(6):1210-1216. 54. Combs SA, Miller EW. Effects of a short burst of gait training with body weight-supported treadmill training for a person with chronic stroke: a single-subject study. Physiother Theory Pract. 2011;27(3): 223-230. 55. Maeda N, Kato J, Shimada T. Predicting the probability for fall incidence in stroke patients using the Berg Balance Scale. J Int Med Res. 2009;37(3):697-704. 56. Clark S, Rose DJ, Fujimoto K. Generalizability of the limits of stability test in the evaluation of dynamic balance among older adults. Arch Phys Med Rehabil. 1997;78(10):1078-1084. 57. Rose DJ, McKillop J. Assessment of balance and mobility functions: a reference study based on the Balance Master. 1998. Located at: NeuroCom, Inc, Clackamas, OR.

 C 2014 Neurology Section, APTA

Copyright © 2014 Neurology Section, APTA. Unauthorized reproduction of this article is prohibited.

225