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Journal of Motor Behavior Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/vjmb20
Effect of Wii-Based Balance Training on Corticomotor Excitability Post Stroke a
b
Oluwabunmi Omiyale , Charles R. Crowell & Sangeetha Madhavan a
a
Department of Physical Therapy, University of Illinois at Chicago
b
Department of Psychology, University of Notre Dame, Indiana Published online: 25 Nov 2014.
To cite this article: Oluwabunmi Omiyale, Charles R. Crowell & Sangeetha Madhavan (2014): Effect of Wii-Based Balance Training on Corticomotor Excitability Post Stroke, Journal of Motor Behavior, DOI: 10.1080/00222895.2014.971699 To link to this article: http://dx.doi.org/10.1080/00222895.2014.971699
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Journal of Motor Behavior, Vol. 0, No. 0, 2015 Copyright © Taylor & Francis Group, LLC
RESEARCH ARTICLE
Effect of Wii-Based Balance Training on Corticomotor Excitability Post Stroke Oluwabunmi Omiyale1, Charles R. Crowell2, Sangeetha Madhavan1
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1 Department of Physical Therapy, University of Illinois at Chicago. 2Department of Psychology, University of Notre Dame, Indiana.
ABSTRACT. The objective was to examine the effectiveness of a 3-week balance training program using the Nintendo Wii Fit gaming system (Nintendo Wii Sports, Nintendo, Redmond, WA) on lower limb corticomotor excitability and other clinical measures in chronic stroke survivors. Ten individuals diagnosed with ischemic stroke with residual hemiparesis received balance training using the Wii Fit for 60 min/day, three times/week, for three weeks. At the end of training, an increase in interhemispheric symmetry of corticomotor excitability of the tibialis anterior muscle representations was noted (n D 9). Participants also showed improvements in reaction time, time to perform the Dual TimedUp-and-Go test, and balance confidence. The training-induced balance in corticomotor excitability suggests that this Wii-based balance training paradigm has the potential to influence neural plasticity and thereby functional recovery.
et al., 2010; Wang et al., 2012). The few functional magnetic resonance imaging (fMRI) studies examining the effects of VR training poststroke have reported blood oxygen level–dependent (BOLD) related changes in cortical activity accompanying the behavioral improvements in chronic stroke survivors (Jang et al., 2005; Orihuela-Espina et al., 2013; You et al., 2005). But it remains unclear if Wii-based balance training influences cortical activation in a similar manner. Hence, in this study we examined the influence of Wii-based balance training on corticomotor excitability of the lower limb motor cortex in chronic stroke survivors.
Keywords: stroke, Nintendo Wii Fit, corticomotor excitability, transcranial magnetic stimulation, balance
Method Participants
G
aming systems using virtual reality (VR) have begun to gain popularity as an adjuvant to standardized care in many neurological populations including stroke (Bateni, 2012; Deutsch et al., 2011; Esculier et al., 2012; Holden & Dyar, 2002; Nitz et al., 2010; Mouawad et al., 2011). The increasing popularity of these systems is because of the stimulating and fun environments these systems provide to sustain participant’s interest and motivation. They also incorporate a range of games specific to a motor skill (such as balance or upper limb coordination) increasing variability and context of practice, thereby serving as a useful tool for motor learning. The Nintendo Wii Fit (Nintendo Wii Sports, Nintendo, Redmond, WA) is a simple and affordable mode of VR gaming technology, and is an excellent alternative to some of the more expensive VR systems. Balance training using the Wii Fit gaming system is reported to improve balance and self-perceived confidence in older adults and individuals with Parkinson’s disease (Agmon et al., 2011; Bateni, 2012; Esculier et al., 2012). Despite the increasing number of applications using the Wii Fit balance board for neurorehabilitation, there remains a paucity of research directly investigating the neural mechanisms supporting its use in stroke rehabilitation. There is evidence to suggest that interhemispheric asymmetry of corticomotor excitability likely contributes to motor impairments following stroke (Madhavan et al., 2010; Rossini et al., 2003; Serrien et al., 2004). Further evidence for this finding can be found in training studies where posttraining improvements in lower limb motor function are associated with a decrease in the excitability of the nonlesioned M1 or an increase in the excitability of the lesioned M1 (Everaert
Ten individuals (six men, four women; M age D 57.3 § 8.5 years) who suffered ischemic stroke (time since stroke D 4.4 § 2.25 years), with residual hemiparetic gait deficits participated in the study. To be included in the study, participants had to be at least six months poststroke, have residual hemiparetic gait impairments demonstrated by abnormal gait pattern or 10 m walk time exceeding agematched walk time by at least 2 s, and able to stand unaided for 10 min. In addition, participants had to have no contraindications to transcranial magnetic stimulation (TMS), which included metal implants in the head, cardiac pacemakers, unexplained headaches, personal or family history of seizures, concussion in the previous six months, fractures or abnormality of the skull, medications likely to alter cortical excitability, and currently pregnant (Rossi et al., 2009). Participants reported no other significant medical history, and had well-managed hypertension (blood pressure ˂ 160/90). Study Design We used a pretest and posttest experimental design. The protocol was approved by the local institutional review board, and the participants provided written informed consent. The study design included a balance training intervention using the Wii Fit for a total of 60 min/day, three times/ week for three weeks. Pre- and postmeasurements included Correspondence address: Sangeetha Madhavan, University of Illinois Chicago, Department of Physical Therapy, 1919 W Taylor Street, Room 447, Chicago, IL 60613, USA. e-mail: [email protected] 1
O. Omiyale, C. R. Crowell, & S. Madhavan
assessment of tibialis anterior (TA) corticomotor excitability using TMS, functional assessments such as body weight distribution, postural limits of stability, and performance on the Wii soccer heading Game. Clinical outcome measures included the Timed-Up-and-Go (TUG) test, Dual TUG tests, Berg Balance Scale (BBS; Berg, Wood-Dauphinee, & Williams, 1995), gait speed using the GaitRite (CIR Systems, Inc., Sparta, NJ), and a self-reported Activities-Specific Balance Confidence (ABC; Botner, Miller, & Eng, 2005) questionnaire. Postassessments were done within 48 hr of completion of training.
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Training Intervention The training intervention consisted of the Wii Fit games such as ski slalom, table tilt, penguin slide, tight rope, and balance rope for 60 min, three times/week for three weeks (see Table 1 for details). All the games were performed while standing on the Wii Fit balance board. Four of the five games were chosen during each session and the order of the games was changed to keep the training from becoming tedious. The participants were supervised and trained by a physical therapist to ensure safety. A 5-min rest was given after every 15 min of training or as requested by the participant. Perceived exertion of the participants was assessed using the Borg’s Rating of Perceived Exertion (RPE) scale (Borg, 1998) during each rest period. Blood pressure and heart rate of the participants were monitored before, during, and after each training session. Experimental Procedures Transcranial magnetic stimulation. To evaluate the corticomotor excitability of the nonparetic and paretic TA
muscle representation, we applied TMS over each lower limb M1 at increasing intensities and the resulting motor evoked potentials (MEPs) were used to obtain recruitment curves. We used single pulse TMS at 0.25 Hz delivered using a Magstim 200 stimulator (Magstim, Dyfed, Wales, UK) via a double-cone coil (diameter 110 mm) to induce a posteroanterior cortical current. The participants were seated comfortably, and given visual feedback of each TA muscle activity during TMS, while they maintained a tonic contraction that represented 10% maximum voluntary isometric contraction (MVIC). Surface Ag ⁄ AgCl electrodes were used to record electromyographic (EMG) activity of the TA. EMG data were sampled at 2000 Hz, amplified (1000£), and band-pass filtered (10–500 Hz) with a Delsys EMG system (Bagnoli EMG system, Delsys, Boston, MA). EMG data were recorded with Spike2 software. At the start of the TMS session, a linen cap was tied tightly to the participant’s head. The vertex was marked on the cap marking the intersection between the line from the nasion and occipital protuberance, and the line joining the two tragi. Two positions, 1 cm posterior and 1.5 cm left of the vertex, and 1 cm posterior and 1.5 cm right of the vertex, were marked on the cap. These positions have been shown to be the optimal position (hot spot) for the TMS coil to elicit MEPs in the TA muscle (Madhavan et al., 2011; Madhavan et al., 2010). Careful detailed distance recordings were made from the nasion, inion, and bilateral pretragus to the vertex taken to ensure that the stimulated spot was the same from pretest to posttest. The center of the two coil windings was located on the marked positions over the lesioned and nonlesioned motor cortex (M1) to generate contralateral responses from the paretic leg and the nonparetic TA muscle, respectively. Responses were obtained at fixed TMS
TABLE 1. Description of the Wii Fit Games Used for Training Wii Fit game
Game description
Training goal
Ski slalom
The gamer skis downhill on a fixed path between poles while shifting body weight from right to left and vice versa. The gamer is penalized for each pole hit, or for not skiing within the path marked by the poles. The penalties increase the total time taken to complete the task. The gamer, standing on an unstable platform, attempts to direct a ball into a hole by shifting body weight in all directions. The gamer attempts to catch virtual fish by shifting weight laterally. The gamer walks through a virtual rope by shifting his weight laterally from left to right and vice versa. The gamer glides through a virtual river by avoiding the virtual bees and walls of the river by moving his body weight from forward, right and left.
Static balance, attention, and coordination.
Table tilt Penguin slide Tight rope Balance bubble
2
Static balance and motor response. Static balance, attention, and choice motor response. Static balance, attention and motor coordination Static balance, attention, and motor coordination.
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Wii Training on Corticomotor Excitability
intensities corresponding to 30%, 35%, 40%, 45%, 50%, 55%, 60%, and 70% maximum stimulator output (MSO) to calculate a recruitment curve. The rationale for using fixed stimulation sites and fixed TMS intensities is based on our previous experience (Madhavan et al., 2011; Madhavan et al., 2010), and the present research question. We did not seek to identify the hot spot per se, and we did not want to assess changes in hotspot locality or the center of gravity of a MEP amplitude map. Moreover, the paretic limb TA threshold to TMS is often too high for MEPs to emerge from background EMG activity. Finding the hot spot and estimating active motor threshold using the traditional protocol is therefore problematic. An alternative would have been to mirror the nonlesioned TA hotspot locality onto the lesioned hemisphere. However, we did not consider this approach to be more accurate than our fixed locality approach. To assess the excitability of TA, recruitment curves were calculated from EMG amplitude in a window when a MEP would be expected and normalized to an equivalent-sized window of background EMG. This allows increases in motor unit firing to be detected in the absence of a large clearly defined MEP. Importantly, our approach allows recruitment curves to be calculated for a lower range of stimulus intensities than would be required if only MEPs that emerged clearly from background were analyzed. When a double cone coil is used, participants often do not tolerate TMS intensities above 70%. Therefore, a modest range of intensities was chosen. We did not plan to fix a sigmoid line of best fit, but preferred to estimate the slope of the steep component of the curve using a linear fit. This might have been less sensitive to small changes in recruitment curve slope, but we were prepared to sacrifice sensitivity in favor of the utility of our protocol. Six MEPs were obtained for each muscle at each intensity from the stimulation spot on the contralateral hemisphere. The recruitment curves were recorded at baseline (PRE) and after three weeks of training (POST). We examined training induced change in corticomotor excitability by comparing interhemispheric symmetry of corticomotor excitability PRE and POST training. Static center of pressure distribution and dynamic weight shifting. The Wii Fit balance board was interfaced to customized WeHab software (WeHab, University of Notre Dame, IN) to test lateral symmetry of a subject’s stance and dynamic ability to shift weight in the lateral and anteriorposterior directions. The WeHab software is a tool developed by researchers at the University of Notre Dame to incorporate the COP data from the Wii Fit balance board to test postural stability (Kennedy et al., 2013; Kennedy et al., 2011). The Wii Fit balance board has been shown to have good validity and reliability for measuring standing balance (intraclass correlation coefficient D 0.66–0.94; Clark et al., 2010). Lateral body weight distribution on each limb was assessed with the participant in standing position with eyes open and closed for 30 s (two trials each). Symmetry of 2015, Vol. 0, No. 0
lateral COP distribution was measured by calculating a ratio of the absolute value of the average COP lateral position of the paretic limb over the nonparetic limb. A value of 1 indicates equal weight bearing on both limbs. Dynamic weight shifting tested the ability of the participant to displace their center of pressure (COP) in eight target directions without losing balance (Figure 1). As each target appeared on the screen, the participant was instructed to move their COP as quickly as possible towards the target location, and maintain the COP for 5 s within each target. Reaction time (RT), the time in seconds between the appearance of the target and the participant’s first movement (i.e., when COP deviated more than five standard deviations from the mean), and the total time to complete the task (TT), the time in seconds from the appearance of the target until the participants successfully placed their COP in the target for a continuous 5 s, was recorded. Soccer heading test. Motor response, attention and coordination of the participants were tested using the soccer heading game on the Wii Fit prior to each training session. This game was chosen because it does not have multiple levels making interpretation of scores simpler, and was primarily used as a measure of performance in an untrained Wii game. In this game, the participant controlled a virtual player’s head by shifting his or her COP on the balance board to the left or right. The objective of the game was to head the soccer balls coming at the player from the left or right while avoiding other flying distractor objects. Scores were automatically computed by the Wii software based on the number of balls headed and number of objects avoided. Performance on this game was tested prior to every training session. Clinical outcome measures. Clinical outcome measures assessed included the TUG and Dual TUG tests (TUGcalendar and TUGcount), BBS, self-selected gait speed using the GaitRite, and the ABC (see Table 2 for details). Data Analyses All MEPs were imported and analyzed using the Spike2 software (Cambridge Electronic Design, Cambridge, UK). Onset and offset latencies of large MEPs of the TA muscle in response to higher TMS intensities were visually marked to create latency windows. A window of identical width was set to measure the background EMG activity of the TA muscle. These windows were used for all intensities. If the MEPs were not distinct (in the case of the paretic muscle), the onset and offset latencies of the nonparetic TA with an additional latency of 5 ms was used to define the windows for the paretic muscle. Normalized MEP area, defined as the ratio of the MEP area to the EMG background area, was calculated (Madhavan et al., 2011; Madhavan et al., 2010). The normalized MEPs recorded for six trials at each TMS intensity were averaged. The averaged MEP areas were then plotted against the corresponding stimulation intensities to 3
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O. Omiyale, C. R. Crowell, & S. Madhavan
FIGURE 1. Visual schematic of the dynamic weight shifting test. The dark gray circles depict the target regions. The small light grey circle depicts the participant’s center of pressure (COP). The participant was instructed to place her COP within the target in the order of its appearance (as shown by the numbers). Each target circle stayed until the patient was able to place her COP within the circle for 5 s continuously. Reaction time (RT), the time in seconds between the appearance of the target and the patient’s first movement, and the total time to complete the task (TT), the time in seconds from the appearance of the cursor until the participant successfully placed the cursor in the target for 5 s was recorded.
produce a recruitment curve. As we chose not to stimulate at intensities that elicit maximum MEPs, we used a conservative linear fit for the resultant recruitment curve rather than a Boltzmann fit, accepting the likelihood of not detecting a difference in slope. The slope of the steepest region (i.e., rate of change) was calculated to estimate the excitability (gain) for each hemisphere. A physiological measure of
interhemispheric symmetry of corticomotor excitability was calculated as follows (Madhavan et al., 2011): InterhemisphericSymmetry D PareticSlope=NonpareticSlope: This ratio yields a value between 0 and 1 where values close to 1 indicate balance in interhemispheric symmetry of
TABLE 2. Clinical Outcomes Outcome measure
Assessed function and description
Timed-up-and-go (TUG) test
Mobility, dynamic balance and walking ability. Time taken by the individual to rise from a chair, walk 3 m, turn around, walk back to the chair, and sit down. Measured in seconds. Mobility, dynamic balance and walking ability during dual tasks. In the TUGcal test, the individual had to complete the TUG while saying the calendar months from the back audibly. In the TUGcount test, individuals were asked to complete the TUG test while counting backward by threes from 100. Measured in seconds. Static and dynamic balance. The individual had to complete four simple balance-related tasks, ranging from standing up from a sitting position, to standing on one foot. A possible score of 56 on 14 items. Self-selected gait speed in centimeters per second. Measured using the GaitRite instrumented walkway. Balance confidence. Measures individual’s self-perception of performing 16 functional ambulatory activities without falling. Maximum score is 100%.
Dual TUG test: TUGcal TUGcount
Berg Balance Scale
Gait speed Activity-specific balance confidence
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TABLE 3. Participant Data
Participant
Age (years)
Gender
Lesioned hemisphere
Time after stroke (years)
MMSE
Gait speed (cm/s)
TUG
BBS
ABC
58 57 63 73 60 55 41 60 48 58
M M M F M F F F M M
L R L L L L R L R L
2 11 7.6 25 2.1 6.3 2.8 4 16 9
30 28 30 30 30 30 29 29 30 30
81.7 46.9 86.7 48.9 58.5 79.46 67.7 64.8 64.9 49.8
13.0 20.0 11.7 16.1 21.5 11.2 19.6 53.5 20.7 22.6
56 43 56 50 55 53 55 39 53 56
82.1 59.3 71.2 59.3 50.6 80.0 62.5 42.5 81.8 69.3
1 2 3 4 5 6 7 8 9 10
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Note. F D female; M D male; R D right; L D left; MMSE D Mini-Mental State Examination; TUG D Timed-Up-and-Go test; BBS D Berg Balance Scale; ABC D Activity-Specific Balance Confidence Questionnaire.
corticomotor excitability. Lateral body weight distribution, RT, and TT were imported from the WeHab software. Gait speeds were imported from the GaitRite. PRE to POST changes in clinical outcome measures were calculated.
TT, and gait speeds PRE- and POST. The Wilcoxon signed rank test was used to examine changes in TUG, BBS, and ABC scores.
Results Statistical Analyses Statistical analyses were performed using SPSS 19 (IBM, Chicago, IL), with an a priori level of significance set at p .05 for all comparisons. Paired Student’s t tests were used to compare differences in paretic and nonparetic slopes, interhemispheric symmetry, lateral body weight distribution, RT,
All participants completed the three-week training program with 100% adherence and no adverse events. We excluded one participant from the MEP analyses because of his inability to attend the TMS session within two days posttraining due to unavailability of personal transportation. Seven of 10 participants used an assistive device for
FIGURE 2. Representative examples from one participant showing nonparetic (A) and paretic (B) TA recruitment curves. The baseline (PRE) session is represented by the open symbols and the posttraining (POST) session is represented by filled symbols. The x-axis denotes the fixed stimulation intensities as a%MSO and the y-axis denotes the normalized MEP area. Note that the slope of the nonparetic TA decreases from PRE to POST (from 0.20 to 0.009) and the slope of the paretic TA increased from PRE to POST (from 0.003 to 0.015).
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FIGURE 3. Comparison of training induced changes in TMS measurements. The gray bars represent PRE and POST values of between hemisphere corticomotor excitability symmetry (paretic slope/nonparetic slope). The dark triangles reprsent the slopes of the MEP recruitment curves obtained from the nonparetic TA. The dark squares reprsent the slopes of the MEP recruitment curves obtained from the paretic TA. The primary y-axis (left) corresponds to the values of interhemispheric symmetry. The secondary y-axis corresponds to the values of slopes of the recruitment curves. All data points are an average of nine subjects and error bars correspond to standard errors. The POST interhemispheric symmetry was significantly different from the PRE (*p < .05).
ambulation (walker or quad cane). Three out of 10 participants used lower extremity bracing (two solid ankle foot orthosis [AFO], one walk aide). Participant demographic data is represented in Table 3 .
FIGURE 4. Individual subject data showing changes in interhemispheric symmetry between baseline (PRE) and posttraining (POST) sessions.
Wii Fit Game Play All participants verbally reported that they enjoyed the training intervention. No assistive devices were used during training. Two of the three participants who used bracing did not feel comfortable removing their AFO, and wore the brace during training. The other participant removed bracing during training but used the usual bracing and assistive device for both PRE and POST testing sessions for safety purposes. No adverse changes in heart rate and blood pressure were noted during the training. Patients reported RPE between 0 and 5 (of 10) during training. Training induced changes in TMS recruitment curves (Figures 2, 3, and 4): Representative example from one par-
TABLE 4. Static COP Distribution and Dynamic Weight Shifting
Static center of pressure distribution Eyes open Body weight distribution (paretic;%) Body weight distribution (nonparetic;%) Body weight symmetry (paretic/nonparetic) Eyes closed Body weight distribution (paretic;%) Body weight distribution (nonparetic;%) Body weight symmetry (paretic/nonparetic) Dynamic weight shifting Reaction time (s) Time to complete task (s)
Pre
Post
46.8 § 3.38 53.2 § 3.38 0.89 § 0.12
47.4 § 4.18 52.6 § 4.18 0.91 § 0.14
46.3 § 3.25 53.7 § 3.25 0.87 § 0.11
47.6 § 3.49 52.4 § 3.49 0.92 § 0.12
26.4 § 23.24 46.9 § 16.51
12.9 § 6.95* 57.6 § 43.01
Note. All values are M § SD of 10 subjects. * p < .05.
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TABLE 5. Clinical Outcome Measures Clinical outcome measure Timed Up and Go (TUG) (s) Dual Timed Up and Go (s) TUGcal TUGcount Berg Balance Scale Self-selected gait speed (cm/s) Activity-specific balance confidence (%)
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*
PRE
POST
21.0 § 12.18
19.4 § 9.10
22.9 § 14.67 25.6 § 17.77 51.6 § 5.97 64.9 § 16.14 65.9 § 13.49
22.0 § 14.45 22.4 § 14.88* 53.6 § 2.95 67.4 § 18.05 73.4 § 13.32*
p < .05.
ticipant showing changes in recruitment curves is shown in Figure 2. There was a significant increase (»87%) in interhemispheric symmetry (p D .005) from PRE (0.37) to POST (0.70; Figure 3). This was demonstrated by a significant decrease in the slope of the nonparetic recruitment curve from 21.1 to 12.4 (p D .04). The paretic slope increased from 7.0 to 8.9 but this difference was not significant (p D .77). Individual data for changes in interhemispheric symmetry of corticomotor excitability are shown in Figure 4.
1987; Dickstein, 2008). There was a nonsignificant increase in body weight distribution after training (Table 4). Dynamic Weight Shifting A significant decrease (»13.5%) in POST RT was noted (p D .03). The time to complete the task was not affected POST (Table 4). Wii Soccer Game
Static COP Distribution All participants demonstrated relatively symmetrical body weight distribution before training (»46%; Dettmann et al.,
Participants showed a significant improvement in scores (»188%, p D .001; Figure 5). Although the participants did not train on this game, it is possible that a practice effect
FIGURE 5. Test scores from the Wii soccer heading game. The soccer heading game was used as a testing instrument prior to each training session. All data points are an average of 10 subjects and error bars correspond to standard errors. The POST time point was significantly different from PRE (*p < .05).
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might have occurred as this was test game was administered at the beginning of each training session. Clinical Outcome Measures No training based change in self-selected gait speeds and BBS scores were observed (Table 5). Among the three TUG tests performed, there was a significant change in the Dual TUGcount test, which involved counting backwards by 3 s from 100. Participants showed a significant decrease in the time to perform the TUGcount test (3.2 s, 12%, p D .009). A significant increase in self-perceived balance confidence (11%, p D .008), tested with the ABC questionnaire, was reported after training.
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Discussion The purpose of this study was to examine the effectiveness of Wii-based balance training on the excitability of the descending corticomotor pathways poststroke. The chronic stroke survivors who participated in this study showed moderate improvements in interhemispheric symmetry of corticomotor excitability after the three-week training intervention. This improvement in interhemispheric symmetry was accompanied by improvements in dynamic balance (as measured by the dynamic weight shifting and Dual TUGcount tests), and increased perception of confidence to perform activities that require balance. However, we did not observe any significant changes in the other clinical tests such as TUG, Dual TUGcalendar, BBS, and gait speed. This is the first study to report changes in corticomotor excitability using TMS, following a long-term Wii-based balance training intervention poststroke. We observed that this change in interhemispheric symmetry was a result of a decrease in the slope of the nonparetic TA. Although this is contrasting to motor learning studies that have consistently demonstrated improvements in corticomotor excitability following learning (Perez et al., 2004; Rosenkranz et al., 2007; Smyth et al., 2010), this is not a surprising finding in the stroke model. After stroke, cortical excitability of the lesioned hemisphere is decreased and excitability of the nonlesioned hemisphere is increased, possibly due to impaired transcallosal inhibition (TCI). There is reduced inhibition from the lesioned to the nonlesioned hemisphere and abnormally high inhibition from nonlesioned to lesioned hemisphere (Murase et al., 2004; Stinear et al., 2008; Traversa et al., 1998). Moreover, a balance of hemispheric excitability is associated with improved poststroke motor recovery (Rossini et al., 2003; Ward, 2005). Numerous studies have tried to redress this asymmetry using neuromodulatory tools that downregulate the nonlesioned hemisphere in an effort to upregulate the excitability of the lesioned hemisphere (Boggio et al., 2007; Khedr et al., 2005; Takeuchi et al., 2008). This model of restoring hemispheric excitability may explain some of our results. The decrease in nonlesioned corticomotor excitability following the Wii-based balance training in the present study could 8
potentially be due to increased TCI from the lesioned hemisphere as a result of motor training. More detailed TMS measurements, such as intracortical inhibition and facilitation, are needed to confirm the previous observation, and to better understand the neural circuits affected by the Wiibased balance training. The present findings are also in agreement with the few studies that have examined fMRIrelated changes in cortical activation following virtual reality training (You, Jang, Kim, Hallett, et al., 2005; You, Jang, Kim, Kwon, et al., 2005). These previous studies reported that VR training shifted aberrant ipsilateral primary sensorimotor cortices (SMCs) activation toward the contralateral SMC. Similarly, in the present study we found a training-induced balance in corticomotor excitability, suggesting that cortical circuits involved in plastic changes within the motor cortex benefit from the Wii-based balance intervention. Wii-based balance training allows for a higher number of task-specific repetitions, which is necessary for neural reorganization (Lang et al., 2009), and also encourages a problem solving approach to achieve an accurate behavioral response, which is an integral aspect of motor learning (Shumway-Cook & Woollacott, 2012). The results of this study can be compared to other studies that have shown similar improvements in corticomotor excitability following training on skilled motor learning tasks or after intensive use of the paretic limb in stroke survivors (Carey et al., 2004; Liepert et al., 1998; Perez et al., 2004). The mechanisms involved in these plastic changes within the motor cortex still remain unclear. Many studies support the view that modulation of the short latency intracortical inhibitory circuits likely are a main contributor to changes in brain plasticity (Butefisch et al., 2006; Classen et al., 1999; Jacobs & Donoghue, 1991; Liepert et al., 1998; Pascual-Leone et al., 1994). The training-induced changes in corticomotor excitability also may occur due to increased coherence between visual input and motor performance (Paz et al., 2003; Roche & O’Mara, 2003). Augmented visual and auditory feedback has been suggested to enhance motor learning (Sigrist et al., 2013). Studies using VR training have also suggested that training with VR helps facilitate internalization of motor representation, thereby promoting new motor cortical networks via M1 mirror neuronal circuits (Holden & Dyar, 2002; You, Jang, Kim et al., 2005). Another possible explanation for the induced neuroplastic change could be due to the constant weighing of the sensory feedback to the brain by the cerebellar-cortical loop in order to process inputs and effect appropriate postural responses during balance training (Jacobs & Horak, 2007). The changes in corticomotor excitability that accompanied the Wii-based balance training suggest that this type of training could be potentially considered as a priming paradigm prior to motor rehabilitation. Motor priming is a relatively new concept in the treatment for gait impairments. Current research focusing on using priming techniques is Journal of Motor Behavior
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Wii Training on Corticomotor Excitability
exploring the effects of brain stimulation, pharmacological drugs, and movement based priming as candidate adjuvants to therapy. Training with the Wii Fit would fall into the latter category of movement-based priming, which includes repetitive performance of bilateral or unilateral movements, mirror symmetric active or passive movements, or any type of exercise including aerobic and isometric exercises (Cauraugh & Summers, 2005; McDonnell et al., 2013; Stinear & Byblow, 2004). In this article, we propose that training with the Wii Fit, in addition to modulating cortical excitability, could also be used potentially to exploit the inherent tendency for synchronization among homologous muscles. Lang et al. (2009) suggested that the amount of time or amount of task specific practice currently provided during stroke rehabilitation is insufficient to produce adequate neural changes for maximum recovery. Therefore, for maximum recovery to be achieved, it is beneficial for participants to be involved in some form of practice outside the clinic targeted at improving their motor skills. In this regard, the Nintendo Wii Fit or similar gaming systems that are cost effective may serve as a feasible adjuvant to stroke rehabilitation. Some of the other functional changes in our study included completion of the Dual TUGcount test in a reduced time as well as decreased reaction time in dynamic weight shifting. These improvements might be due to increased prioritization to attention demanding tasks that may involve cortical involvement in gait control (Beauchet & Berrut, 2006). In addition, the participants reported an increase in perception of confidence during activities of daily living that involved balance. To successfully complete all gaming tasks, participants were required to shift their body weight in all planes potentially encouraging activation of ankle strategies as well as hip and trunk movement and control. This may also explain the improvements in the participant’s dynamic balance activities and perception of fear of falling. This increase in balance confidence is consistent with several studies using the Wii Fit in the elderly population and in those with Parkinson’s disease (Agmon et al., 2011; Esculier et al., 2012). Study Limitations The findings in this report have several caveats. First, the generalizations of the results of this study are limited by the small homogenous sample. Accordingly, the present outcomes will need to be confirmed in future studies with a larger, more heterogeneous cohort. Nonetheless, statistically significant pre–post outcomes were obtained in this study. Second, the participants had varying functional levels, which were not systematically categorized. Moreover, individuals with lower levels of function were not well represented among the present participants. Third, the present study did not include a comparison control group. Fourth, the fixedsite TMS stimulation method used to measure corticomotor excitability is a technical limitation. It is possible that we 2015, Vol. 0, No. 0
may not have found the true optimal location of the TA, which might have shifted following stroke or intervention. We deliberately chose a procedure that would rapidly and reliably measure changes in MEP excitability, while minimizing potential for internal variability or subject fatigue. The significant difference in interhemispheric symmetry observed in our present study may have been underestimated by this conservative fixed stimulation technique. Finally, in order for the Wii Fit balance training intervention to truly function as a movement priming technique, the balance priming should be provided in combination with gait training to fully exploit its potentially beneficial effects. Conclusions We present evidence that training with the Nintendo Wii Fit has the potential to modulate corticomotor excitability post stroke, thereby enhancing motor learning as well as facilitating neural changes needed to achieve maximum functional recovery. In addition, the Wii Fit also positively influenced functional outcomes such as dynamic balance and balance confidence. Because of its ability to modulate neural plasticity, we propose that Wii Fit training could serve as a movement priming adjuvant to rehabilitation. It is necessary to identify affordable, realistic interventions that allow clinicians to employ evidence-based approaches incorporating the mechanisms of motor control research. Future studies will be needed to replicate the present findings in similar populations with larger samples. REFERENCES Agmon, M., Perry, C. K., Phelan, E., Demiris. G., & Nguyen, H. Q. (2011). A pilot study of Wii Fit exergames to improve balance in older adults. Journal of Geriatric Physical Therapy, 34, 161–167. Bateni, H. (2012). Changes in balance in older adults based on use of physical therapy vs the Wii Fit gaming system: a preliminary study. Physiotherapy, 98, 211–216. Beauchet, O., & G. Berrut (2006). Gait and dual-task: definition, interest, and perspectives in the elderly. Psychologie Neuropsychiatrie Vieillissement, 4, 215–225. Berg, K., Wood-Dauphinee, S., & Williams, J. I. (2005). The Balance Scale: reliability assessment with elderly residents and patients with an acute stroke. Scandinavian Journal of Rehabilitation Medicine, 27(1), 27–36. Boggio, P. S., Nunes, A., Rigonatti, S. P., Nitsche, M. A., PascualLeone, A., & Fregni. F. (2007). Repeated sessions of noninvasive brain DC stimulation is associated with motor function improvement in stroke patients. Restorative Neurology and Neuroscience, 25, 123–129. Borg, G. (1998). Borg’s Perceived Exertion and Pain Scales. Champaign, IL: Human Kinetics. Botner, E. M., Miller, W. C., & Eng, J. J. (2005). Measurement properties of the Activities-specific Balance Confidence Scale among individuals with stroke. Disability and Rehabilitation Medicine, 27(4), 156–163. Butefisch, C. M., Kleiser, R., & Seitz, R. J. (2006). Post-lesional cerebral reorganisation: Evidence from functional neuroimaging and transcranial magnetic stimulation. Journal of Physiology-Paris 99(4–6): 437–454. 9
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Wang, R. Y., Tseng, H. Y., Tseng, H. Y., Liao, K. K., Wang, C. J., Lai, K. L., & Yang, Y.R. (2012). rTMS combined with task-oriented training to improve symmetry of interhemispheric corticomotor excitability and gait performance after stroke: A randomized trial. Neurorehabilitation and Neural Repair, 26, 222–230. Ward, N. S. (2005). Mechanisms underlying recovery of motor function after stroke. Postgraduate Medical Journal, 81, 510–514. You, S. H., Jang, S. H., Kim, Y. H., Hallett, M., Ahn, S. H., Kwon, Y. H., . . . Lee, M. Y. (2005). Virtual reality-induced cortical reorganization and associated locomotor recovery in chronic stroke: An experimenter-blind randomized study. Stroke, 36, 1166–1171. You, S. H., Jang, S. H., Kim, Y. H., Kwon, Y. H., Barrow, I., & Hallett, M. (2005). Cortical reorganization induced by virtual reality therapy in a child with hemiparetic cerebral palsy. Developmental Medicine and Child Neurology, 47, 628–635.
Received May 27, 2014 Revised August 7, 2014 Accepted September 28, 2014
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Journal of Motor Behavior Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/vjmb20
Effect of Wii-Based Balance Training on Corticomotor Excitability Post Stroke a
b
Oluwabunmi Omiyale , Charles R. Crowell & Sangeetha Madhavan a
a
Department of Physical Therapy, University of Illinois at Chicago
b
Department of Psychology, University of Notre Dame, Indiana Published online: 25 Nov 2014.
To cite this article: Oluwabunmi Omiyale, Charles R. Crowell & Sangeetha Madhavan (2014): Effect of Wii-Based Balance Training on Corticomotor Excitability Post Stroke, Journal of Motor Behavior, DOI: 10.1080/00222895.2014.971699 To link to this article: http://dx.doi.org/10.1080/00222895.2014.971699
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Journal of Motor Behavior, Vol. 0, No. 0, 2015 Copyright © Taylor & Francis Group, LLC
RESEARCH ARTICLE
Effect of Wii-Based Balance Training on Corticomotor Excitability Post Stroke Oluwabunmi Omiyale1, Charles R. Crowell2, Sangeetha Madhavan1
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1 Department of Physical Therapy, University of Illinois at Chicago. 2Department of Psychology, University of Notre Dame, Indiana.
ABSTRACT. The objective was to examine the effectiveness of a 3-week balance training program using the Nintendo Wii Fit gaming system (Nintendo Wii Sports, Nintendo, Redmond, WA) on lower limb corticomotor excitability and other clinical measures in chronic stroke survivors. Ten individuals diagnosed with ischemic stroke with residual hemiparesis received balance training using the Wii Fit for 60 min/day, three times/week, for three weeks. At the end of training, an increase in interhemispheric symmetry of corticomotor excitability of the tibialis anterior muscle representations was noted (n D 9). Participants also showed improvements in reaction time, time to perform the Dual TimedUp-and-Go test, and balance confidence. The training-induced balance in corticomotor excitability suggests that this Wii-based balance training paradigm has the potential to influence neural plasticity and thereby functional recovery.
et al., 2010; Wang et al., 2012). The few functional magnetic resonance imaging (fMRI) studies examining the effects of VR training poststroke have reported blood oxygen level–dependent (BOLD) related changes in cortical activity accompanying the behavioral improvements in chronic stroke survivors (Jang et al., 2005; Orihuela-Espina et al., 2013; You et al., 2005). But it remains unclear if Wii-based balance training influences cortical activation in a similar manner. Hence, in this study we examined the influence of Wii-based balance training on corticomotor excitability of the lower limb motor cortex in chronic stroke survivors.
Keywords: stroke, Nintendo Wii Fit, corticomotor excitability, transcranial magnetic stimulation, balance
Method Participants
G
aming systems using virtual reality (VR) have begun to gain popularity as an adjuvant to standardized care in many neurological populations including stroke (Bateni, 2012; Deutsch et al., 2011; Esculier et al., 2012; Holden & Dyar, 2002; Nitz et al., 2010; Mouawad et al., 2011). The increasing popularity of these systems is because of the stimulating and fun environments these systems provide to sustain participant’s interest and motivation. They also incorporate a range of games specific to a motor skill (such as balance or upper limb coordination) increasing variability and context of practice, thereby serving as a useful tool for motor learning. The Nintendo Wii Fit (Nintendo Wii Sports, Nintendo, Redmond, WA) is a simple and affordable mode of VR gaming technology, and is an excellent alternative to some of the more expensive VR systems. Balance training using the Wii Fit gaming system is reported to improve balance and self-perceived confidence in older adults and individuals with Parkinson’s disease (Agmon et al., 2011; Bateni, 2012; Esculier et al., 2012). Despite the increasing number of applications using the Wii Fit balance board for neurorehabilitation, there remains a paucity of research directly investigating the neural mechanisms supporting its use in stroke rehabilitation. There is evidence to suggest that interhemispheric asymmetry of corticomotor excitability likely contributes to motor impairments following stroke (Madhavan et al., 2010; Rossini et al., 2003; Serrien et al., 2004). Further evidence for this finding can be found in training studies where posttraining improvements in lower limb motor function are associated with a decrease in the excitability of the nonlesioned M1 or an increase in the excitability of the lesioned M1 (Everaert
Ten individuals (six men, four women; M age D 57.3 § 8.5 years) who suffered ischemic stroke (time since stroke D 4.4 § 2.25 years), with residual hemiparetic gait deficits participated in the study. To be included in the study, participants had to be at least six months poststroke, have residual hemiparetic gait impairments demonstrated by abnormal gait pattern or 10 m walk time exceeding agematched walk time by at least 2 s, and able to stand unaided for 10 min. In addition, participants had to have no contraindications to transcranial magnetic stimulation (TMS), which included metal implants in the head, cardiac pacemakers, unexplained headaches, personal or family history of seizures, concussion in the previous six months, fractures or abnormality of the skull, medications likely to alter cortical excitability, and currently pregnant (Rossi et al., 2009). Participants reported no other significant medical history, and had well-managed hypertension (blood pressure ˂ 160/90). Study Design We used a pretest and posttest experimental design. The protocol was approved by the local institutional review board, and the participants provided written informed consent. The study design included a balance training intervention using the Wii Fit for a total of 60 min/day, three times/ week for three weeks. Pre- and postmeasurements included Correspondence address: Sangeetha Madhavan, University of Illinois Chicago, Department of Physical Therapy, 1919 W Taylor Street, Room 447, Chicago, IL 60613, USA. e-mail: [email protected] 1
O. Omiyale, C. R. Crowell, & S. Madhavan
assessment of tibialis anterior (TA) corticomotor excitability using TMS, functional assessments such as body weight distribution, postural limits of stability, and performance on the Wii soccer heading Game. Clinical outcome measures included the Timed-Up-and-Go (TUG) test, Dual TUG tests, Berg Balance Scale (BBS; Berg, Wood-Dauphinee, & Williams, 1995), gait speed using the GaitRite (CIR Systems, Inc., Sparta, NJ), and a self-reported Activities-Specific Balance Confidence (ABC; Botner, Miller, & Eng, 2005) questionnaire. Postassessments were done within 48 hr of completion of training.
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Training Intervention The training intervention consisted of the Wii Fit games such as ski slalom, table tilt, penguin slide, tight rope, and balance rope for 60 min, three times/week for three weeks (see Table 1 for details). All the games were performed while standing on the Wii Fit balance board. Four of the five games were chosen during each session and the order of the games was changed to keep the training from becoming tedious. The participants were supervised and trained by a physical therapist to ensure safety. A 5-min rest was given after every 15 min of training or as requested by the participant. Perceived exertion of the participants was assessed using the Borg’s Rating of Perceived Exertion (RPE) scale (Borg, 1998) during each rest period. Blood pressure and heart rate of the participants were monitored before, during, and after each training session. Experimental Procedures Transcranial magnetic stimulation. To evaluate the corticomotor excitability of the nonparetic and paretic TA
muscle representation, we applied TMS over each lower limb M1 at increasing intensities and the resulting motor evoked potentials (MEPs) were used to obtain recruitment curves. We used single pulse TMS at 0.25 Hz delivered using a Magstim 200 stimulator (Magstim, Dyfed, Wales, UK) via a double-cone coil (diameter 110 mm) to induce a posteroanterior cortical current. The participants were seated comfortably, and given visual feedback of each TA muscle activity during TMS, while they maintained a tonic contraction that represented 10% maximum voluntary isometric contraction (MVIC). Surface Ag ⁄ AgCl electrodes were used to record electromyographic (EMG) activity of the TA. EMG data were sampled at 2000 Hz, amplified (1000£), and band-pass filtered (10–500 Hz) with a Delsys EMG system (Bagnoli EMG system, Delsys, Boston, MA). EMG data were recorded with Spike2 software. At the start of the TMS session, a linen cap was tied tightly to the participant’s head. The vertex was marked on the cap marking the intersection between the line from the nasion and occipital protuberance, and the line joining the two tragi. Two positions, 1 cm posterior and 1.5 cm left of the vertex, and 1 cm posterior and 1.5 cm right of the vertex, were marked on the cap. These positions have been shown to be the optimal position (hot spot) for the TMS coil to elicit MEPs in the TA muscle (Madhavan et al., 2011; Madhavan et al., 2010). Careful detailed distance recordings were made from the nasion, inion, and bilateral pretragus to the vertex taken to ensure that the stimulated spot was the same from pretest to posttest. The center of the two coil windings was located on the marked positions over the lesioned and nonlesioned motor cortex (M1) to generate contralateral responses from the paretic leg and the nonparetic TA muscle, respectively. Responses were obtained at fixed TMS
TABLE 1. Description of the Wii Fit Games Used for Training Wii Fit game
Game description
Training goal
Ski slalom
The gamer skis downhill on a fixed path between poles while shifting body weight from right to left and vice versa. The gamer is penalized for each pole hit, or for not skiing within the path marked by the poles. The penalties increase the total time taken to complete the task. The gamer, standing on an unstable platform, attempts to direct a ball into a hole by shifting body weight in all directions. The gamer attempts to catch virtual fish by shifting weight laterally. The gamer walks through a virtual rope by shifting his weight laterally from left to right and vice versa. The gamer glides through a virtual river by avoiding the virtual bees and walls of the river by moving his body weight from forward, right and left.
Static balance, attention, and coordination.
Table tilt Penguin slide Tight rope Balance bubble
2
Static balance and motor response. Static balance, attention, and choice motor response. Static balance, attention and motor coordination Static balance, attention, and motor coordination.
Journal of Motor Behavior
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Wii Training on Corticomotor Excitability
intensities corresponding to 30%, 35%, 40%, 45%, 50%, 55%, 60%, and 70% maximum stimulator output (MSO) to calculate a recruitment curve. The rationale for using fixed stimulation sites and fixed TMS intensities is based on our previous experience (Madhavan et al., 2011; Madhavan et al., 2010), and the present research question. We did not seek to identify the hot spot per se, and we did not want to assess changes in hotspot locality or the center of gravity of a MEP amplitude map. Moreover, the paretic limb TA threshold to TMS is often too high for MEPs to emerge from background EMG activity. Finding the hot spot and estimating active motor threshold using the traditional protocol is therefore problematic. An alternative would have been to mirror the nonlesioned TA hotspot locality onto the lesioned hemisphere. However, we did not consider this approach to be more accurate than our fixed locality approach. To assess the excitability of TA, recruitment curves were calculated from EMG amplitude in a window when a MEP would be expected and normalized to an equivalent-sized window of background EMG. This allows increases in motor unit firing to be detected in the absence of a large clearly defined MEP. Importantly, our approach allows recruitment curves to be calculated for a lower range of stimulus intensities than would be required if only MEPs that emerged clearly from background were analyzed. When a double cone coil is used, participants often do not tolerate TMS intensities above 70%. Therefore, a modest range of intensities was chosen. We did not plan to fix a sigmoid line of best fit, but preferred to estimate the slope of the steep component of the curve using a linear fit. This might have been less sensitive to small changes in recruitment curve slope, but we were prepared to sacrifice sensitivity in favor of the utility of our protocol. Six MEPs were obtained for each muscle at each intensity from the stimulation spot on the contralateral hemisphere. The recruitment curves were recorded at baseline (PRE) and after three weeks of training (POST). We examined training induced change in corticomotor excitability by comparing interhemispheric symmetry of corticomotor excitability PRE and POST training. Static center of pressure distribution and dynamic weight shifting. The Wii Fit balance board was interfaced to customized WeHab software (WeHab, University of Notre Dame, IN) to test lateral symmetry of a subject’s stance and dynamic ability to shift weight in the lateral and anteriorposterior directions. The WeHab software is a tool developed by researchers at the University of Notre Dame to incorporate the COP data from the Wii Fit balance board to test postural stability (Kennedy et al., 2013; Kennedy et al., 2011). The Wii Fit balance board has been shown to have good validity and reliability for measuring standing balance (intraclass correlation coefficient D 0.66–0.94; Clark et al., 2010). Lateral body weight distribution on each limb was assessed with the participant in standing position with eyes open and closed for 30 s (two trials each). Symmetry of 2015, Vol. 0, No. 0
lateral COP distribution was measured by calculating a ratio of the absolute value of the average COP lateral position of the paretic limb over the nonparetic limb. A value of 1 indicates equal weight bearing on both limbs. Dynamic weight shifting tested the ability of the participant to displace their center of pressure (COP) in eight target directions without losing balance (Figure 1). As each target appeared on the screen, the participant was instructed to move their COP as quickly as possible towards the target location, and maintain the COP for 5 s within each target. Reaction time (RT), the time in seconds between the appearance of the target and the participant’s first movement (i.e., when COP deviated more than five standard deviations from the mean), and the total time to complete the task (TT), the time in seconds from the appearance of the target until the participants successfully placed their COP in the target for a continuous 5 s, was recorded. Soccer heading test. Motor response, attention and coordination of the participants were tested using the soccer heading game on the Wii Fit prior to each training session. This game was chosen because it does not have multiple levels making interpretation of scores simpler, and was primarily used as a measure of performance in an untrained Wii game. In this game, the participant controlled a virtual player’s head by shifting his or her COP on the balance board to the left or right. The objective of the game was to head the soccer balls coming at the player from the left or right while avoiding other flying distractor objects. Scores were automatically computed by the Wii software based on the number of balls headed and number of objects avoided. Performance on this game was tested prior to every training session. Clinical outcome measures. Clinical outcome measures assessed included the TUG and Dual TUG tests (TUGcalendar and TUGcount), BBS, self-selected gait speed using the GaitRite, and the ABC (see Table 2 for details). Data Analyses All MEPs were imported and analyzed using the Spike2 software (Cambridge Electronic Design, Cambridge, UK). Onset and offset latencies of large MEPs of the TA muscle in response to higher TMS intensities were visually marked to create latency windows. A window of identical width was set to measure the background EMG activity of the TA muscle. These windows were used for all intensities. If the MEPs were not distinct (in the case of the paretic muscle), the onset and offset latencies of the nonparetic TA with an additional latency of 5 ms was used to define the windows for the paretic muscle. Normalized MEP area, defined as the ratio of the MEP area to the EMG background area, was calculated (Madhavan et al., 2011; Madhavan et al., 2010). The normalized MEPs recorded for six trials at each TMS intensity were averaged. The averaged MEP areas were then plotted against the corresponding stimulation intensities to 3
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O. Omiyale, C. R. Crowell, & S. Madhavan
FIGURE 1. Visual schematic of the dynamic weight shifting test. The dark gray circles depict the target regions. The small light grey circle depicts the participant’s center of pressure (COP). The participant was instructed to place her COP within the target in the order of its appearance (as shown by the numbers). Each target circle stayed until the patient was able to place her COP within the circle for 5 s continuously. Reaction time (RT), the time in seconds between the appearance of the target and the patient’s first movement, and the total time to complete the task (TT), the time in seconds from the appearance of the cursor until the participant successfully placed the cursor in the target for 5 s was recorded.
produce a recruitment curve. As we chose not to stimulate at intensities that elicit maximum MEPs, we used a conservative linear fit for the resultant recruitment curve rather than a Boltzmann fit, accepting the likelihood of not detecting a difference in slope. The slope of the steepest region (i.e., rate of change) was calculated to estimate the excitability (gain) for each hemisphere. A physiological measure of
interhemispheric symmetry of corticomotor excitability was calculated as follows (Madhavan et al., 2011): InterhemisphericSymmetry D PareticSlope=NonpareticSlope: This ratio yields a value between 0 and 1 where values close to 1 indicate balance in interhemispheric symmetry of
TABLE 2. Clinical Outcomes Outcome measure
Assessed function and description
Timed-up-and-go (TUG) test
Mobility, dynamic balance and walking ability. Time taken by the individual to rise from a chair, walk 3 m, turn around, walk back to the chair, and sit down. Measured in seconds. Mobility, dynamic balance and walking ability during dual tasks. In the TUGcal test, the individual had to complete the TUG while saying the calendar months from the back audibly. In the TUGcount test, individuals were asked to complete the TUG test while counting backward by threes from 100. Measured in seconds. Static and dynamic balance. The individual had to complete four simple balance-related tasks, ranging from standing up from a sitting position, to standing on one foot. A possible score of 56 on 14 items. Self-selected gait speed in centimeters per second. Measured using the GaitRite instrumented walkway. Balance confidence. Measures individual’s self-perception of performing 16 functional ambulatory activities without falling. Maximum score is 100%.
Dual TUG test: TUGcal TUGcount
Berg Balance Scale
Gait speed Activity-specific balance confidence
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TABLE 3. Participant Data
Participant
Age (years)
Gender
Lesioned hemisphere
Time after stroke (years)
MMSE
Gait speed (cm/s)
TUG
BBS
ABC
58 57 63 73 60 55 41 60 48 58
M M M F M F F F M M
L R L L L L R L R L
2 11 7.6 25 2.1 6.3 2.8 4 16 9
30 28 30 30 30 30 29 29 30 30
81.7 46.9 86.7 48.9 58.5 79.46 67.7 64.8 64.9 49.8
13.0 20.0 11.7 16.1 21.5 11.2 19.6 53.5 20.7 22.6
56 43 56 50 55 53 55 39 53 56
82.1 59.3 71.2 59.3 50.6 80.0 62.5 42.5 81.8 69.3
1 2 3 4 5 6 7 8 9 10
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Note. F D female; M D male; R D right; L D left; MMSE D Mini-Mental State Examination; TUG D Timed-Up-and-Go test; BBS D Berg Balance Scale; ABC D Activity-Specific Balance Confidence Questionnaire.
corticomotor excitability. Lateral body weight distribution, RT, and TT were imported from the WeHab software. Gait speeds were imported from the GaitRite. PRE to POST changes in clinical outcome measures were calculated.
TT, and gait speeds PRE- and POST. The Wilcoxon signed rank test was used to examine changes in TUG, BBS, and ABC scores.
Results Statistical Analyses Statistical analyses were performed using SPSS 19 (IBM, Chicago, IL), with an a priori level of significance set at p .05 for all comparisons. Paired Student’s t tests were used to compare differences in paretic and nonparetic slopes, interhemispheric symmetry, lateral body weight distribution, RT,
All participants completed the three-week training program with 100% adherence and no adverse events. We excluded one participant from the MEP analyses because of his inability to attend the TMS session within two days posttraining due to unavailability of personal transportation. Seven of 10 participants used an assistive device for
FIGURE 2. Representative examples from one participant showing nonparetic (A) and paretic (B) TA recruitment curves. The baseline (PRE) session is represented by the open symbols and the posttraining (POST) session is represented by filled symbols. The x-axis denotes the fixed stimulation intensities as a%MSO and the y-axis denotes the normalized MEP area. Note that the slope of the nonparetic TA decreases from PRE to POST (from 0.20 to 0.009) and the slope of the paretic TA increased from PRE to POST (from 0.003 to 0.015).
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FIGURE 3. Comparison of training induced changes in TMS measurements. The gray bars represent PRE and POST values of between hemisphere corticomotor excitability symmetry (paretic slope/nonparetic slope). The dark triangles reprsent the slopes of the MEP recruitment curves obtained from the nonparetic TA. The dark squares reprsent the slopes of the MEP recruitment curves obtained from the paretic TA. The primary y-axis (left) corresponds to the values of interhemispheric symmetry. The secondary y-axis corresponds to the values of slopes of the recruitment curves. All data points are an average of nine subjects and error bars correspond to standard errors. The POST interhemispheric symmetry was significantly different from the PRE (*p < .05).
ambulation (walker or quad cane). Three out of 10 participants used lower extremity bracing (two solid ankle foot orthosis [AFO], one walk aide). Participant demographic data is represented in Table 3 .
FIGURE 4. Individual subject data showing changes in interhemispheric symmetry between baseline (PRE) and posttraining (POST) sessions.
Wii Fit Game Play All participants verbally reported that they enjoyed the training intervention. No assistive devices were used during training. Two of the three participants who used bracing did not feel comfortable removing their AFO, and wore the brace during training. The other participant removed bracing during training but used the usual bracing and assistive device for both PRE and POST testing sessions for safety purposes. No adverse changes in heart rate and blood pressure were noted during the training. Patients reported RPE between 0 and 5 (of 10) during training. Training induced changes in TMS recruitment curves (Figures 2, 3, and 4): Representative example from one par-
TABLE 4. Static COP Distribution and Dynamic Weight Shifting
Static center of pressure distribution Eyes open Body weight distribution (paretic;%) Body weight distribution (nonparetic;%) Body weight symmetry (paretic/nonparetic) Eyes closed Body weight distribution (paretic;%) Body weight distribution (nonparetic;%) Body weight symmetry (paretic/nonparetic) Dynamic weight shifting Reaction time (s) Time to complete task (s)
Pre
Post
46.8 § 3.38 53.2 § 3.38 0.89 § 0.12
47.4 § 4.18 52.6 § 4.18 0.91 § 0.14
46.3 § 3.25 53.7 § 3.25 0.87 § 0.11
47.6 § 3.49 52.4 § 3.49 0.92 § 0.12
26.4 § 23.24 46.9 § 16.51
12.9 § 6.95* 57.6 § 43.01
Note. All values are M § SD of 10 subjects. * p < .05.
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TABLE 5. Clinical Outcome Measures Clinical outcome measure Timed Up and Go (TUG) (s) Dual Timed Up and Go (s) TUGcal TUGcount Berg Balance Scale Self-selected gait speed (cm/s) Activity-specific balance confidence (%)
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*
PRE
POST
21.0 § 12.18
19.4 § 9.10
22.9 § 14.67 25.6 § 17.77 51.6 § 5.97 64.9 § 16.14 65.9 § 13.49
22.0 § 14.45 22.4 § 14.88* 53.6 § 2.95 67.4 § 18.05 73.4 § 13.32*
p < .05.
ticipant showing changes in recruitment curves is shown in Figure 2. There was a significant increase (»87%) in interhemispheric symmetry (p D .005) from PRE (0.37) to POST (0.70; Figure 3). This was demonstrated by a significant decrease in the slope of the nonparetic recruitment curve from 21.1 to 12.4 (p D .04). The paretic slope increased from 7.0 to 8.9 but this difference was not significant (p D .77). Individual data for changes in interhemispheric symmetry of corticomotor excitability are shown in Figure 4.
1987; Dickstein, 2008). There was a nonsignificant increase in body weight distribution after training (Table 4). Dynamic Weight Shifting A significant decrease (»13.5%) in POST RT was noted (p D .03). The time to complete the task was not affected POST (Table 4). Wii Soccer Game
Static COP Distribution All participants demonstrated relatively symmetrical body weight distribution before training (»46%; Dettmann et al.,
Participants showed a significant improvement in scores (»188%, p D .001; Figure 5). Although the participants did not train on this game, it is possible that a practice effect
FIGURE 5. Test scores from the Wii soccer heading game. The soccer heading game was used as a testing instrument prior to each training session. All data points are an average of 10 subjects and error bars correspond to standard errors. The POST time point was significantly different from PRE (*p < .05).
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might have occurred as this was test game was administered at the beginning of each training session. Clinical Outcome Measures No training based change in self-selected gait speeds and BBS scores were observed (Table 5). Among the three TUG tests performed, there was a significant change in the Dual TUGcount test, which involved counting backwards by 3 s from 100. Participants showed a significant decrease in the time to perform the TUGcount test (3.2 s, 12%, p D .009). A significant increase in self-perceived balance confidence (11%, p D .008), tested with the ABC questionnaire, was reported after training.
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Discussion The purpose of this study was to examine the effectiveness of Wii-based balance training on the excitability of the descending corticomotor pathways poststroke. The chronic stroke survivors who participated in this study showed moderate improvements in interhemispheric symmetry of corticomotor excitability after the three-week training intervention. This improvement in interhemispheric symmetry was accompanied by improvements in dynamic balance (as measured by the dynamic weight shifting and Dual TUGcount tests), and increased perception of confidence to perform activities that require balance. However, we did not observe any significant changes in the other clinical tests such as TUG, Dual TUGcalendar, BBS, and gait speed. This is the first study to report changes in corticomotor excitability using TMS, following a long-term Wii-based balance training intervention poststroke. We observed that this change in interhemispheric symmetry was a result of a decrease in the slope of the nonparetic TA. Although this is contrasting to motor learning studies that have consistently demonstrated improvements in corticomotor excitability following learning (Perez et al., 2004; Rosenkranz et al., 2007; Smyth et al., 2010), this is not a surprising finding in the stroke model. After stroke, cortical excitability of the lesioned hemisphere is decreased and excitability of the nonlesioned hemisphere is increased, possibly due to impaired transcallosal inhibition (TCI). There is reduced inhibition from the lesioned to the nonlesioned hemisphere and abnormally high inhibition from nonlesioned to lesioned hemisphere (Murase et al., 2004; Stinear et al., 2008; Traversa et al., 1998). Moreover, a balance of hemispheric excitability is associated with improved poststroke motor recovery (Rossini et al., 2003; Ward, 2005). Numerous studies have tried to redress this asymmetry using neuromodulatory tools that downregulate the nonlesioned hemisphere in an effort to upregulate the excitability of the lesioned hemisphere (Boggio et al., 2007; Khedr et al., 2005; Takeuchi et al., 2008). This model of restoring hemispheric excitability may explain some of our results. The decrease in nonlesioned corticomotor excitability following the Wii-based balance training in the present study could 8
potentially be due to increased TCI from the lesioned hemisphere as a result of motor training. More detailed TMS measurements, such as intracortical inhibition and facilitation, are needed to confirm the previous observation, and to better understand the neural circuits affected by the Wiibased balance training. The present findings are also in agreement with the few studies that have examined fMRIrelated changes in cortical activation following virtual reality training (You, Jang, Kim, Hallett, et al., 2005; You, Jang, Kim, Kwon, et al., 2005). These previous studies reported that VR training shifted aberrant ipsilateral primary sensorimotor cortices (SMCs) activation toward the contralateral SMC. Similarly, in the present study we found a training-induced balance in corticomotor excitability, suggesting that cortical circuits involved in plastic changes within the motor cortex benefit from the Wii-based balance intervention. Wii-based balance training allows for a higher number of task-specific repetitions, which is necessary for neural reorganization (Lang et al., 2009), and also encourages a problem solving approach to achieve an accurate behavioral response, which is an integral aspect of motor learning (Shumway-Cook & Woollacott, 2012). The results of this study can be compared to other studies that have shown similar improvements in corticomotor excitability following training on skilled motor learning tasks or after intensive use of the paretic limb in stroke survivors (Carey et al., 2004; Liepert et al., 1998; Perez et al., 2004). The mechanisms involved in these plastic changes within the motor cortex still remain unclear. Many studies support the view that modulation of the short latency intracortical inhibitory circuits likely are a main contributor to changes in brain plasticity (Butefisch et al., 2006; Classen et al., 1999; Jacobs & Donoghue, 1991; Liepert et al., 1998; Pascual-Leone et al., 1994). The training-induced changes in corticomotor excitability also may occur due to increased coherence between visual input and motor performance (Paz et al., 2003; Roche & O’Mara, 2003). Augmented visual and auditory feedback has been suggested to enhance motor learning (Sigrist et al., 2013). Studies using VR training have also suggested that training with VR helps facilitate internalization of motor representation, thereby promoting new motor cortical networks via M1 mirror neuronal circuits (Holden & Dyar, 2002; You, Jang, Kim et al., 2005). Another possible explanation for the induced neuroplastic change could be due to the constant weighing of the sensory feedback to the brain by the cerebellar-cortical loop in order to process inputs and effect appropriate postural responses during balance training (Jacobs & Horak, 2007). The changes in corticomotor excitability that accompanied the Wii-based balance training suggest that this type of training could be potentially considered as a priming paradigm prior to motor rehabilitation. Motor priming is a relatively new concept in the treatment for gait impairments. Current research focusing on using priming techniques is Journal of Motor Behavior
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exploring the effects of brain stimulation, pharmacological drugs, and movement based priming as candidate adjuvants to therapy. Training with the Wii Fit would fall into the latter category of movement-based priming, which includes repetitive performance of bilateral or unilateral movements, mirror symmetric active or passive movements, or any type of exercise including aerobic and isometric exercises (Cauraugh & Summers, 2005; McDonnell et al., 2013; Stinear & Byblow, 2004). In this article, we propose that training with the Wii Fit, in addition to modulating cortical excitability, could also be used potentially to exploit the inherent tendency for synchronization among homologous muscles. Lang et al. (2009) suggested that the amount of time or amount of task specific practice currently provided during stroke rehabilitation is insufficient to produce adequate neural changes for maximum recovery. Therefore, for maximum recovery to be achieved, it is beneficial for participants to be involved in some form of practice outside the clinic targeted at improving their motor skills. In this regard, the Nintendo Wii Fit or similar gaming systems that are cost effective may serve as a feasible adjuvant to stroke rehabilitation. Some of the other functional changes in our study included completion of the Dual TUGcount test in a reduced time as well as decreased reaction time in dynamic weight shifting. These improvements might be due to increased prioritization to attention demanding tasks that may involve cortical involvement in gait control (Beauchet & Berrut, 2006). In addition, the participants reported an increase in perception of confidence during activities of daily living that involved balance. To successfully complete all gaming tasks, participants were required to shift their body weight in all planes potentially encouraging activation of ankle strategies as well as hip and trunk movement and control. This may also explain the improvements in the participant’s dynamic balance activities and perception of fear of falling. This increase in balance confidence is consistent with several studies using the Wii Fit in the elderly population and in those with Parkinson’s disease (Agmon et al., 2011; Esculier et al., 2012). Study Limitations The findings in this report have several caveats. First, the generalizations of the results of this study are limited by the small homogenous sample. Accordingly, the present outcomes will need to be confirmed in future studies with a larger, more heterogeneous cohort. Nonetheless, statistically significant pre–post outcomes were obtained in this study. Second, the participants had varying functional levels, which were not systematically categorized. Moreover, individuals with lower levels of function were not well represented among the present participants. Third, the present study did not include a comparison control group. Fourth, the fixedsite TMS stimulation method used to measure corticomotor excitability is a technical limitation. It is possible that we 2015, Vol. 0, No. 0
may not have found the true optimal location of the TA, which might have shifted following stroke or intervention. We deliberately chose a procedure that would rapidly and reliably measure changes in MEP excitability, while minimizing potential for internal variability or subject fatigue. The significant difference in interhemispheric symmetry observed in our present study may have been underestimated by this conservative fixed stimulation technique. Finally, in order for the Wii Fit balance training intervention to truly function as a movement priming technique, the balance priming should be provided in combination with gait training to fully exploit its potentially beneficial effects. Conclusions We present evidence that training with the Nintendo Wii Fit has the potential to modulate corticomotor excitability post stroke, thereby enhancing motor learning as well as facilitating neural changes needed to achieve maximum functional recovery. In addition, the Wii Fit also positively influenced functional outcomes such as dynamic balance and balance confidence. Because of its ability to modulate neural plasticity, we propose that Wii Fit training could serve as a movement priming adjuvant to rehabilitation. It is necessary to identify affordable, realistic interventions that allow clinicians to employ evidence-based approaches incorporating the mechanisms of motor control research. Future studies will be needed to replicate the present findings in similar populations with larger samples. REFERENCES Agmon, M., Perry, C. K., Phelan, E., Demiris. G., & Nguyen, H. Q. (2011). A pilot study of Wii Fit exergames to improve balance in older adults. Journal of Geriatric Physical Therapy, 34, 161–167. Bateni, H. (2012). Changes in balance in older adults based on use of physical therapy vs the Wii Fit gaming system: a preliminary study. Physiotherapy, 98, 211–216. Beauchet, O., & G. Berrut (2006). Gait and dual-task: definition, interest, and perspectives in the elderly. Psychologie Neuropsychiatrie Vieillissement, 4, 215–225. Berg, K., Wood-Dauphinee, S., & Williams, J. I. (2005). The Balance Scale: reliability assessment with elderly residents and patients with an acute stroke. Scandinavian Journal of Rehabilitation Medicine, 27(1), 27–36. Boggio, P. S., Nunes, A., Rigonatti, S. P., Nitsche, M. A., PascualLeone, A., & Fregni. F. (2007). Repeated sessions of noninvasive brain DC stimulation is associated with motor function improvement in stroke patients. Restorative Neurology and Neuroscience, 25, 123–129. Borg, G. (1998). Borg’s Perceived Exertion and Pain Scales. Champaign, IL: Human Kinetics. Botner, E. M., Miller, W. C., & Eng, J. J. (2005). Measurement properties of the Activities-specific Balance Confidence Scale among individuals with stroke. Disability and Rehabilitation Medicine, 27(4), 156–163. Butefisch, C. M., Kleiser, R., & Seitz, R. J. (2006). Post-lesional cerebral reorganisation: Evidence from functional neuroimaging and transcranial magnetic stimulation. Journal of Physiology-Paris 99(4–6): 437–454. 9
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Wang, R. Y., Tseng, H. Y., Tseng, H. Y., Liao, K. K., Wang, C. J., Lai, K. L., & Yang, Y.R. (2012). rTMS combined with task-oriented training to improve symmetry of interhemispheric corticomotor excitability and gait performance after stroke: A randomized trial. Neurorehabilitation and Neural Repair, 26, 222–230. Ward, N. S. (2005). Mechanisms underlying recovery of motor function after stroke. Postgraduate Medical Journal, 81, 510–514. You, S. H., Jang, S. H., Kim, Y. H., Hallett, M., Ahn, S. H., Kwon, Y. H., . . . Lee, M. Y. (2005). Virtual reality-induced cortical reorganization and associated locomotor recovery in chronic stroke: An experimenter-blind randomized study. Stroke, 36, 1166–1171. You, S. H., Jang, S. H., Kim, Y. H., Kwon, Y. H., Barrow, I., & Hallett, M. (2005). Cortical reorganization induced by virtual reality therapy in a child with hemiparetic cerebral palsy. Developmental Medicine and Child Neurology, 47, 628–635.
Received May 27, 2014 Revised August 7, 2014 Accepted September 28, 2014
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