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The effect of vibrotactile biofeedback of trunk sway on balance control in multiple sclerosis
Multiple Sclerosis and Related Disorders 8 (2016) 58–63
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Multiple Sclerosis and Related Disorders journal homepage: www.elsevier.com/locate/msard
The effect of vibrotactile biofeedback of trunk sway on balance control in multiple sclerosis R.P. van der Logt a,1, O. Findling b,c,1, H. Rust b, O. Yaldizli b, J.H.J. Allum a,n a
Division of Audiology and Neurootology, Department of ORL, University Hospital Basel, CH-4031 Basel, Switzerland Department of Neurology, University Hospital Basel, Switzerland c Department of Neurology, Cantonal Hospital Aarau, Switzerland b
art ic l e i nf o
a b s t r a c t
Article history: Received 11 November 2015 Received in revised form 9 April 2016 Accepted 1 May 2016
Background: Patients with multiple sclerosis (MS) suffer from diminished balance control due to slowed sensory conduction and possibly delayed central processing. Vibrotactile biofeedback of trunk sway has been shown to improve balance control in patients with peripheral and central vestibular disorders. Here, the effects of vibrotactile feedback training on trunk sway and a possible carry-over effect was measured in MS patients during stance and gait. Methods: Ten MS patients (mean age 46.8 77.7 years, 40% male) participated in a crossover study in which 7 different stance and gait tasks were trained with and without angle feedback for stance and angular velocity feedback for gait. An assessment sequence of 12 tasks was performed once before and twice after the training sequence. Trunk sway was measured with body-worn gyroscopes. Head mounted vibrotactile biofeedback of trunk sway was provided during one crossover training arm and the following second assessment sequence. Results: Biofeedback generally leads to a decrease in sway but an increase in sway angular velocities during some stance tasks compared to training without biofeedback. Biofeedback while walking eyes open resulted in a decreased sway angular velocity. The greatest changes were found in the pitch direction of trunk sway. Effects diminished after biofeedback was removed. Conclusions: This study showed that vibrotactile biofeedback of trunk sway beneficially effects stance and provides significant improvement in gait compared to training without biofeedback in MS patients. & 2016 Elsevier B.V. All rights reserved.
Keywords: Multiple sclerosis Balance control Trunk sway Vibrotactile biofeedback Stance Gait
1. Introduction Multiple sclerosis (MS) is a chronic autoimmune inflammatory disease of the central nervous system (CNS) which can affect sensory and motor systems. Balance impairment is one of the key symptoms of MS, which leads to unstable walking patterns and increases the risk of falling (Cameron and Lord, 2010; Kalron and Achiron, 2013; Mazumder et al., 2015). Furthermore, fear of falling can lead to a curtailment of activity, physiological deconditioning, and institutionalization (Kalron and Achiron, 2013; Mazumder et al., 2015). One form of balance impairment is caused by diminished proprioceptive sensory information from the lower legs which triggers and modulates balance corrections in reaction to unexpected perturbations while walking or standing (Bloem et al., 2000). Proprioceptive deficits in MS are the result of slowed n
Corresponding author. E-mail address: [email protected] (J.H.J. Allum). 1 Equal first authors.
http://dx.doi.org/10.1016/j.msard.2016.05.003 2211-0348/& 2016 Elsevier B.V. All rights reserved.
somatosensory conduction and impaired central integration due to demyelination and axonal loss (Cameron and Lord, 2010; Cameron et al., 2008; Frohman et al., 2006). Diminished proprioceptive information leads to increased compensating movement in pelvis and shoulders to maintain balance during stance, as observed in lower-leg proprioceptive loss patients by the greater sway at the pelvis and shoulders while standing quiet with eyes closed on a firm support surface (Horlings et al., 2008, 2009a). Thus a similar balance deficit can be expected in MS patients. Clinically, MS is classified in different subtypes (Lublin and Reingold, 1996). Most of the patients ( 85%) have relapsing-remitting MS (RRMS) characterised by the relapses at disease onset. Relapses are subacute new symptoms or exacerbation of old symptoms which recover mostly partially within weeks. In contrast to this, in people with primary progressive MS (PPMS) the disease starts without relapses but with a continuous progression of disability. Relapses are possible later on but in general less frequently than in RRMS. Within 15 years most of the RRMS patients develop secondary progression with less relapse frequency and predominantly continuous progression of disability which is called secondary progressive MS. Deficits in balance affect about
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75% of all patients with MS and can occur in all clinical subtypes (Missaoui and Thoumie, 2009; McDonald et al., 2001). Thus all MS patient groups could presumably benefit from techniques which improve balance control. The effect of balance biofeedback on body sway has been explored in different modalities, including feedback of trunk linear acceleration, trunk angular position or velocity (Davis et al., 2010; Dozza et al., 2005; Hegeman et al., 2005; Verhoeff et al., 2009). Such biofeedback has been proven to have an effect on improving balance for healthy people (Verhoeff et al., 2009; Huffman et al., 2010a; Janssen et al., 2009), patients with either peripheral or central vestibular balance deficits (Basta et al., 2008; Dozza et al., 2007; Nanhoe-Mahabier et al., 2012). For stance and gait tasks differences in trunk sway angles and velocities improvements are observed (Kalron and Achiron, 2013; Verhoeff et al., 2009). For patients with balance deficits, the differential effect of position versus velocity vibrotactile biofeedback on stance and gait, respectively, is largely unknown. However, for normal subjects, position feedback is more effective for stance and velocity feedback more effective for gait (Janssen et al., 2009; Huffman et al., 2010b). MS patients tend to have relatively worse gait balance control compared to that of stance (Fanchamps et al., 2012). Therefore, the aim of this study was to investigate the effects of vibrotactile (VT) biofeedback training on MS patients during stance and gait tasks while receiving position and velocity feedback, respectively. We expected a greater improvement in gait based on the greater improvement observed with velocity biofeedback in young controls (Janssen et al., 2009). Additionally, this study investigated whether using a VT biofeedback system yielded a more beneficial carryover effect for MS patients once the VT biofeedback was removed. All results were compared with the effect of the same training but without VT feedback.
2. Methods 2.1. Subjects Ten MS patients (6 RRMS, 2 PPMS and 2 secondary progressive MS) were included in the study (mean age 46.8 77.7 years, 40% male, mean EDSS score at first test 3.9 71.7, median EDSS score 4.0. Range 2.5–6.0). Patients were excluded from the study if they were unable to walk without walking aids, had orthopaedic problems or other diseases/disabilities than MS that could affect their balance. All participants provided written informed consent to participate before the experiment started. The study was approved (026–2014 EKNZ) by the Ethical Committee NW Switzerland (responsible for the University Hospital Basel) and carried out according to the Declaration of Helsinki. 2.2. Experimental setup All 10 MS patients were enrolled in a crossover study design with a minimum two-week interval between the measurement days of each crossover arm. Two additional patients dropped out after their first visit due to scheduling conflicts. Patients were randomly assigned to a starting crossover arm with or without VT biofeedback. Patients performed assessment and training sequences consisting of stance and gait tasks while trunk sway was measured with a SwayStar™ device (Balance International Innovations GmbH, Switzerland). This device measures the angular velocities of the trunk in the pitch (anterior - posterior) and roll (medial lateral) planes using two gyroscopes mounted near the body's centre of mass (Allum and Carpenter, 2005), in the centre of the lower back at vertebral level L3-L5. An elasticated belt was used to
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Table 1 List of assessment and training tasks in the order tasks were performed within these sequences. Assessment tasks Standing 1 leg eyes open (20 s) Standing 2 legs eyes closed (20 s) Standing 2 legs eyes open on foam (20 s) Standing 1 leg eyes open on foam (20 s) Standing 2 legs eyes closed on foam (20 s) Tandem stance eyes open (20 s) Walking 8 tandem steps eyes open Tandem stance eyes closed (20 s) Walking 8 tandem steps eyes closed Walking over barriers Walking 8 m eyes open Walking 3 m eyes closed Training tasks Standing 2 legs eyes closed (20 s) 3x Standing 1 leg eyes open on foam (20 s) 3x Standing 2 legs eyes closed on foam (20 s) 3x Tandem stance eyes closed (20 s) 3x Walking 8 tandem steps eyes open 3x Walking 3 m eyes closed 3x Walking 8 m eyes open 3x
Order of sequences: First assessment ↓ Training sequence ↓ Second assessment ↓ Third assessment
The assessment sequence was repeated twice after the training sequence. For the measurement arm with VT biofeedback patients also received VT biofeedback during the second assessment. The results of the 2nd and 3rd assessment with and without VT biofeedback were compared with the results of the 1st assessment.
strap the attached Swaystar™ system around the patients’ waist. The SwayStar™ device has been validated in a number of studies in MS patients (Fanchamps et al., 2012; Findling et al., 2011; Corporaal et al., 2013). For the measurements, patients removed their shoes to avoid measurement variations due to shoe types. Patients performed the assessment sequence three times and the training sequence of trial protocols once per crossover arm on the same day with sufficient breaks between sequences to avoid fatigue. Trials were always performed at the same time of day (generally mornings) for each patient to avoid diurnal differences in fatigue levels affecting the results. The training sequence was performed after the first assessment sequence. The order of tasks within the assessment and training sequences is listed in Table 1. A BalanceFreedom™ add-on to SwayStar™ was used to provide patients direction-specific VT feedback during the training sequence and during the second assessment sequence if patients were in the investigational arm with VT feedback. This head mounted device is connected to the SwayStar™ and uses eight vibrotactile actuators spaced at 45 degree to indicate the direction of sway once a threshold of sway angle or velocity was exceeded. Task-specific biofeedback thresholds for angle (used during stance tasks) and angular velocity (used during gait protocols) were set at 90% of the 90% range results acquired during the first pre-training assessment sequence from each patient. Patients were requested to reduce sway as much as possible during the training and subsequent assessment sequences. When receiving VT biofeedback of trunk sway, they were requested to avoid activating the VT transducers and if these were activated to move away from the direction indicated by the feedback. A 5–10 min break took place between all assessment and training sequences. Assessment sequences consisted of 12 tasks and the training sequence included 7 of these tasks, 4 stance and 3 gait tasks (see Table 1). Tasks were stopped when a patient lost balance or completed the task. Stance tasks were performed maximally for 20 seconds. For 2-legged stance tasks (except tandem stance), participants stood on a foam or firm surfaces with their feet shoulder width apart and their arms hanging next to their body. They were asked to stand as quiet as possible and asked not to talk during the trials. For eyes open stance tasks,
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Table 2A Effect of vibrotactile biofeedback training. Task
ΔRA in deg (SEM)
S1EO S2EC S2EOF S1EOF S2ECF TSEO W8TSEO TSEC W8TSEC WOB W8MEO W3MEC
2.92 0.07 0.20 2.99 0.26 2.01 3.11 0.78 2.94 2.29 0.31 0.92
(3.36)* (0.14) (0.24) (1.66)* (0.19) (0.97)* p¼ 0.04 (1.33)* (1.48) (2.18) (1.43)* (0.28) (0.48)
ΔRV in deg/s (SEM) 1.13 0.66 1.01 10.65 0.15 3.06 4.22 6.32 4.05 2.20 3.78 2.52
ΔPA in deg (SEM)
(7.80)* (0.21)* p ¼0.017 (0.62) (6.84)* (0.55)* (3.73)* (2.61)* (3.67) (3.11) (4.31) (2.94) (1.84) *
1.15 0.12 0.56 0.95 0.45 0.87 2.29 3.55 2.35 1.28 0.26 1.24
(3.15)* (0.17) (0.58) (1.72) (0.36)* (1.19) * (1.36)* (2.91)* (1.04) p ¼ 0.050 (1.32)* (0.51) (1.28)
ΔPV in deg/s (SEM) 13.43 1.36 2.01 0.57 0.27 0.66 3.21 9.59 2.32 5.48 13.87 5.24
(9.28)* (0.26)* p¼ 0.005 (0.64)*p ¼ 0.005 (2.87)* (0.69)* (2.66)* (2.50)* (4.23)* p ¼0.04 (2.56) (4.25) (6.03) p ¼0.022 (3.61)*
Results are given in increase (positive) or decrease (negative) in trunk sway variable for the second (first post-training) assessment with VT biofeedback compared to the first (pre-training) assessment without biofeedback. Grey shaded values indicate a significant change between pre and post-training measurements for which p values are provided. Bold values indicate a significant difference between training conditions (none versus with VT biofeedback). Task abbreviations are listed in the methods section. R stands for roll A for angle, V for angular velocity, P for pitch, Δ for increase or decrease. * ¼ First assessment (pre-training) showed a significant difference between patients and 20 healthy age- and gender-matched controls – data from (Huffman et al., 2010b; Findling et al., 2011). Healthy control measures were not available for the W8TSEC task.
patients were instructed to fixate on a point at eye height 5 m away. All tasks were demonstrated to the patients. During all tasks a spotter stood next to the patient to support them in case balance was lost. 2.3. Assessment sequence Five stance tasks were performed first: standing on one leg with eyes open (S1EO); standing on two legs with eyes closed (S2EC); standing on two legs with eyes open on foam (S2EOF); standing on one leg with eyes open on foam (S1EOF); standing on two legs eyes closed on foam (S2ECF). Next, tandem stance (TSEO) and walking eight tandem steps (W8TSEO) were performed with eyes open and afterwards these two tasks were performed with eyes closed (TSEC, W8TSEC). Then patients were asked to walk over a set of low (24 cm) barriers spaced one meter apart (WOB). Finally, patients walked eight meters with eyes open (W8MEO) and three meters with eyes closed (W3MEC). The first assessment sequence was used to set VT thresholds individually. The second assessment which took place after training was used to assess the combined effect of VT feedback during training and during the assessment and the third assessment which was without VT feedback was used to assess the carry-over effect VT feedback during training and the prior assessment. 2.4. Training sequence For the training sequence, tasks were executed three consecutive times. This sequence consisted of: standing two legs eyes closed (S2EC); standing one leg eyes open on foam (S1EOF); standing two legs eyes closed on foam (S2EOF); tandem stance eyes closed (TSEC); walking eight tandem steps eyes open (W8TSEO); walking three meters eyes closed (W3MEC); walking eight meters eyes open (W8MEO). The tasks comprising assessment and training sequences are listed in Table 1. 2.5. Data analysis SwayStar™ measurements for the 90% range of pitch (P) and roll (R) sway angle (A) and the 90% range of pitch and roll sway angular velocity (V) for each task were examined as outcome measures. The duration until task completion or loss of balance for every task was the fifth outcome measure. A Wilcoxon signed-rank test was performed using SPSS (IBM SPSS statistics 20, Chicago, IL, USA) to compare the results of the pre-training assessment with
the second assessment sequence (with and without biofeedback) and the third assessment sequence (no biofeedback). A Wilcoxon signed-rank test was used because of the sample size. The third trial of each task during the training sequence was used to assess the direct training effect. To test whether vibrotactile feedback led to an increase or decrease in sway angle and sway angular velocity for all tasks within the assessment sequences, differences were computed for trunk sway between pre-training and the first posttraining assessments with biofeedback. These differences were formed for the arm with and without VT feedback. To determine if there was a difference in carry-over effects depending on the training condition (none or VT feedback) the second post-assessment sequence (3rd assessment) measures were compared with those of the first pre-training assessment. These differences were compared with a Wilcoxon signed-rank test to determine if a significant effect of vibrotactile biofeedback versus none occurred for each task. Given the problems associated with formally correcting for multiple comparisons (Perneger, 1998) we present results flagged using the conventional (p r0.05).
3. Results 3.1. Effects of vibrotactile biofeedback on stance tasks Although there was generally a reduction in trunk sway with VT feedback (Table 2A), not all of the changes were significant or significantly different from providing training without VT feedback. For the easier stance trials an increase in sway velocity was noted with VT feedback. For example, a significant increase in RV was observed during VT training sessions (p ¼0.013) and posttraining in second assessment trials with VT feedback on (p ¼0.017) for the S2EC task (Table 2A). Likewise, for the S2EOF task with VT feedback there was an increase in PV in the second assessment trial (p ¼0.005) compared to the first assessment. This increase significantly differed from the no-feedback S2EOF measurement (p ¼0.012). Biofeedback during tandem stance tasks led to variable results. TSEO showed a decrease in RA (p ¼ 0.037) during the second assessment compared to the pre-training assessment trial. The tandem stance task with closed eyes also led to a decrease in PV during the second assessment (p ¼ 0.036) and a carry-over effect occurred (p ¼0.028) during the third assessment trials. However, similar results were found during the training alone (no VT feedback) measurements.
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Fig. 1. Differences in RA, PA, RV and PV for training alone (no VT feedback) and VT feedback conditions for the W8MEO task. Δα: difference between pre-training assessment and training sequence. Δβ: difference between pre-training assessment and second assessment (post-training). Δγ: difference between pre-training assessment and third assessment trial (post training carry-over effect). *indicates significant difference between training conditions.
3.2. Effects of vibrotactile biofeedback on gait tasks During the W8MEO second assessment trial a significant decrease in PV was found (p ¼0.022), whereas the training alone (without VT feedback) measurement resulted in a small, insignificant increase. This resulted in a significant difference between feedback and training alone (p ¼ 0.036). These findings are shown in Fig. 1. 3.3. Training alone (without VT feedback) There was a general increase in trunk sway when training without VT feedback was provided (Table 2B). For example, training alone resulted in an increase in PV (p ¼0.017) during the S1EO second assessment. S2EC RV measures showed a decrease during post-training assessments, but this decrease was only significant during the training (p ¼0.017). Gait tasks did not show any significant differences in balance measures after training alone (no VT feedback). However, the duration of W8TSEO and WOB tasks decreased significantly during post-training assessment trials. These differences in duration are shown in Fig. 2.
4. Discussion 4.1. Effects of vibrotactile biofeedback training This study showed there is a significant difference in balance control when MS patients trained and were assessed with vibrotactile biofeedback compared to training and assessment
Table 2B Training alone effects. Task
ΔRA in deg (SEM)
ΔRV in deg/s (SEM)
ΔPA in deg (SEM)
ΔPV in deg/s (SEM)
S1EO S2EC S2EOF S1EOF S2ECF TSEO W8TSEO TSEC W8TSEC WOB W8MEO W3MEC
4.85 0.22 0.18 3.65 0.29 2.20 1.33 2.97 2.52 1.78 0.31 0.07
8.72 0.40 0.41 6.19 0.33 1.58 2.07 3.58 2.79 3.88 0.67 2.47
6.42 0.06 0.10 0.78 0.39 0.57 2.28 2.21 0.77 2.29 0.62 0.45
9.90 0.08 0.32 7.28 0.75 0.16 2.46 9.91 1.51 2.37 5.25 5.35
(4.08) (0.16) (0.13) (1.79) (0.54) (2.52) (1.62) (2.39) (1.26) (1.49) (0.68) (0.50)
(6.28) (0.41) (0.55) (7.48) (0.78) (4.00) (2.47) (3.54) (3.30) (3.32) (1.89) (2.68)
(4.23) (0.25) (0.30) (2.24) (0.60) (0.50) (2.52) (1.78) (2.27) (2.05) (0.41) (0.69)
(5.43) p ¼0.017 (0.27) (0.36) (7.54) (1.27) (2.27) (2.81) (7.22) (3.01) (5.22) (2.64) (3.52)
Results are given in increase or decrease in trunk sway variable for the second (first post-training) assessment compared to the first (pre-training assessment) Both without VT biofeedback. Grey shaded values indicate a significant change between pre and post-training measurements. Bold values indicate a significant difference between training conditions (none versus with VT biofeedback). These are the same measures indicated in Table 2A. Abbreviations are described in the legend for Table 2A.
without feedback. Although decreases in sway occurred in several tasks with feedback, many were not significant when compared to training and assessment without VT feedback. Our current result reinforce the point that devices that provide balance feedback during training and assessment sessions need to be tested by comparing with the effect of training and assessment without feedback and not by just examining the difference between a first
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14,0
Duraon in seconds
12,0
*
10,0
*
8,0
* *
6,0
W8TSEO
WOB
4,0
It is well-known that fatigue is a confounding factor for trials with MS patients. For example, fatigue increases for 6 min walking trials with EDSS scores (Leone et al., 2015). We attempted to avoid fatigue by providing patients with adequate rest periods of 5– 10 min between each assessment which lasted 10 min and after training. Nevertheless, lack of a strong carryover effect in this study may have been due to the confounding effect of fatigue. Differences between balance measures for the VT and no feedback protocol arms of this study would not be influenced by fatigue as these involved the same tasks and durations.
2,0
4.2. Training alone (without VT biofeedback)
0,0 First assessment Training
Secon d
Third assessment
Fig. 2. Mean durations (and SEM) of W8STEO and WOB for training alone without VT biofeedback. *Marks a significant difference (p o 0.05) with respect to the first assessment.
assessment without feedback to a second with feedback. As with normal subjects (Davis et al., 2010; Huffman et al., 2010b), providing balance feedback during training for stance tasks leads to an increase in sway velocity. For example, two-legged stance tasks with eyes closed on firm surface showed an increase in trunk angular velocity in the roll and pitch plane when biofeedback was given. The same reaction occurred during the standing on foam with eyes open task, where angular velocity was significantly enhanced in the pitch but not in the roll plane. In both tasks, enhancements differed from the results of the without feedback measurements. The increase in trunk angular velocity is possibly related to faster, shorter reactions of biofeedback compared to the reaction on losing balance for no feedback. In our previous studies on normal subjects (Davis et al., 2010; Huffman et al., 2010b), enhancement in angular velocities were accompanied by a decrease in trunk sway angle. Possibly the absence of a change in sway angle can be explained by the fact that MS-patients judged the correction amplitude incorrectly even with feedback due to a mismatch with available proprioceptive information. Interestingly, given the difficulties MS patients have with gait, all gait tasks showed a higher decrease for angular velocity in pitch and roll plane when biofeedback was given compared to none. During the walking 8 m eyes open task a significantly higher decrease in sway angular velocity occurred in the pitch plane when VT biofeedback was provided. Janssen et al. Janssen et al. (2009) also reported a decrease in sway velocities and task specific reductions in sway angles in their study on healthy young subjects. However, in our study, no significant decreases in sway angle were found in comparison to no VT feedback (training alone). Overall, the greatest differences with pre-test were found during the second assessment trial with biofeedback. A carry-over effect of biofeedback to the third assessment for which no feedback was provided was only found for pitch plane trunk angular velocity in the tandem stance eyes closed task. This significant decrease was also found in the first post-training assessment sequence. However, training alone (no feedback) also showed a decrease in trunk angular velocity. Therefore, the difference between biofeedback and none was not significant. The question arises if performance with VT feedback is worse in patients with higher EDSS scores given that their balance control deficits are correlated with their EDSS scores (Corporaal et al., 2013). In this study we used individually set thresholds and therefore cannot answer this question. In other studies where population set thresholds have been used, improvements are greater for those with initially poorer balance control because these subjects reached feedback thresholds more often (Davis et al., 2010).
Training alone (Table 2B) resulted in few significant differences between the pre-training and post-training assessments. For walking eight tandem steps eyes open and walking over barriers, gait speed increased when no feedback was provided as shown in Fig. 2. This decrease in trial duration can be possibly explained by a learning effect (Horlings et al., 2009b). 4.3. Future studies Our results showed that vibrotactile biofeedback of trunk sway leads to an immediate effect on trunk sway in MS patients without prior experience with such biofeedback. Although a significant effect was found, the sample size was small. Therefore, it would be interesting to repeat the study with a greater sample size and a greater period of training. We would expect, however, that the direction of the effects, greater for VT feedback than for training without VT feedback would be the same as noted in studies on controls and other patient groups (Davis et al., 2010; NanhoeMahabier et al., 2012). Some patients indicated that initially they had difficulties reacting to the VT biofeedback. As the vibrotactile biofeedback was received on their head they encountered difficulties in reacting to the biofeedback by changing the angle of their trunk. The initial reaction was to move the head and only after training did they move with their trunk. Providing patients with biofeedback around their trunk might be a solution for this problem. However, as discussed by Verhoeff et al. (2009) the 20–30 ms transmission delay for balance information between trunk versus head VT feedback and to the CNS may have an impact on balance control. Despite these initial learning steps, MS patients were able to reduce sway during gait more than during stance (Table 2A). This is crucial because gait is relatively more affected than stance in MS patients (Kalron and Achiron, 2013; Mazumder et al., 2015; Perneger, 1998). Our study helps understanding reactions of MS-patients to VT biofeedback. However, further research is needed to investigate how VT biofeedback could be used to prevent falling and how much biofeedback training can induce a meaningful carry-over effect on balance control. A carry-over effect would reduce the need to provide VT balance biofeedback continuously.
5. Conclusion This study showed that vibrotactile biofeedback leads to an improvement in balance control of MS patients over that provided by training alone (no feedback). The effects differed between gait and stance tasks as in healthy subjects. Vibrotactile feedback was only effective while wearing the device; a significant carry-over effect was not observed with biofeedback. To see whether more extensive biofeedback training can lead to a more permanent effect and which frequency and duration of training is most effective, further research with larger group of cohorts is needed.
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Conflict of interest The author JHJ Allum declares a conflict of interest as he worked as a consultant for the company producing the SwayStar equipment used in this study.
Funding This research was supported by grants from the Freiwillige Akademische Gesellschaft of Basel and the Swiss MS Society to Dr. O Yaldizli and Dr. JHJ Allum. RP Van der Logt was also supported by a grant from the Radboud University Medical Centre, Nijmegen and the Nijmegen University Fund.
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Findling, O., et al., 2011. Trunk sway in mildly disabled multiple sclerosis patients with and without balance impairment. Exp. Brain Res. 213 (4), 363–370. Frohman, E.M., Racke, M.K., Raine, C.S., 2006. Multiple sclerosis–the plaque and its pathogenesis. N. Engl. J. Med. 354 (9), 942–955. Hegeman, J., et al., 2005. The balance control of bilateral peripheral vestibular loss subjects and its improvement with auditory prosthetic feedback. J. Vestib. Res. 15 (2), 109–117. Horlings, C.G., et al., 2008. Identifying deficits in balance control following vestibular or proprioceptive loss using posturographic analysis of stance tasks. Clin. Neurophysiol. 119 (10), 2338–2346. Horlings, C.G., et al., 2009a. Vestibular and proprioceptive influences on trunk movements during quiet standing. Neuroscience 161 (3), 904–914. Horlings, C.G., et al., 2009b. Trunk sway analysis to quantify the warm-up phenomenon in myotonia congenita patients. J. Neurol. Neurosurg. Psychiatry 80 (2), 207–212. Huffman, J.L., et al., 2010a. Directional effects of biofeedback on trunk sway during stance tasks in healthy young adults. Gait Posture 32 (1), 62–66. Huffman, J.L., et al., 2010b. Directional effects of biofeedback on trunk sway during stance tasks in healthy young adults. Gait Posture 32 (1), 62–66. Janssen, L.J., et al., 2009. Directional effects of biofeedback on trunk sway during gait tasks in healthy young subjects. Gait Posture 29 (4), 575–581. Kalron, A., Achiron, A., 2013. Postural control, falls and fear of falling in people with multiple sclerosis without mobility aids. J. Neurol. Sci. 335 (1–2), 186–190. Leone, C., et al., 2015. Prevalence of walking-related motor fatigue in persons with multiple sclerosis: decline in walking distance induced by the 6-minute walk test. Neurorehabil. Neural Repair (Epub ahead of print). Lublin, F.D., Reingold, S.C., 1996. Defining the clinical course of multiple sclerosis: results of an international survey. National Multiple Sclerosis Society (USA) Advisory committee on clinical trials of new agents in multiple sclerosis. Neurology 46 (4), 907–911. Mazumder, R., et al., 2015. Fear of falling is associated with recurrent falls in people with multiple sclerosis: a longitudinal cohort study. Int. J. MS Care 17 (4), 164–170. McDonald, W.I., et al., 2001. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann. Neurol. 50 (1), 121–127. Missaoui, B., Thoumie, P., 2009. How far do patients with sensory ataxia benefit from so-called “proprioceptive rehabilitation”? Neurophysiol. Clin. 39 (4–5), 229–233. Nanhoe-Mahabier, W., et al., 2012. The effects of vibrotactile biofeedback training on trunk sway in Parkinson’s disease patients. Park. Relat. Disord. 18 (9), 1017–1021. Perneger, T.V., 1998. What's wrong with Bonferroni adjustments. BMJ 316 (7139), 1236–1238. Verhoeff, L.L., et al., 2009. Effects of biofeedback on trunk sway during dual tasking in the healthy young and elderly. Gait Posture 30 (1), 76–81.
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Multiple Sclerosis and Related Disorders journal homepage: www.elsevier.com/locate/msard
The effect of vibrotactile biofeedback of trunk sway on balance control in multiple sclerosis R.P. van der Logt a,1, O. Findling b,c,1, H. Rust b, O. Yaldizli b, J.H.J. Allum a,n a
Division of Audiology and Neurootology, Department of ORL, University Hospital Basel, CH-4031 Basel, Switzerland Department of Neurology, University Hospital Basel, Switzerland c Department of Neurology, Cantonal Hospital Aarau, Switzerland b
art ic l e i nf o
a b s t r a c t
Article history: Received 11 November 2015 Received in revised form 9 April 2016 Accepted 1 May 2016
Background: Patients with multiple sclerosis (MS) suffer from diminished balance control due to slowed sensory conduction and possibly delayed central processing. Vibrotactile biofeedback of trunk sway has been shown to improve balance control in patients with peripheral and central vestibular disorders. Here, the effects of vibrotactile feedback training on trunk sway and a possible carry-over effect was measured in MS patients during stance and gait. Methods: Ten MS patients (mean age 46.8 77.7 years, 40% male) participated in a crossover study in which 7 different stance and gait tasks were trained with and without angle feedback for stance and angular velocity feedback for gait. An assessment sequence of 12 tasks was performed once before and twice after the training sequence. Trunk sway was measured with body-worn gyroscopes. Head mounted vibrotactile biofeedback of trunk sway was provided during one crossover training arm and the following second assessment sequence. Results: Biofeedback generally leads to a decrease in sway but an increase in sway angular velocities during some stance tasks compared to training without biofeedback. Biofeedback while walking eyes open resulted in a decreased sway angular velocity. The greatest changes were found in the pitch direction of trunk sway. Effects diminished after biofeedback was removed. Conclusions: This study showed that vibrotactile biofeedback of trunk sway beneficially effects stance and provides significant improvement in gait compared to training without biofeedback in MS patients. & 2016 Elsevier B.V. All rights reserved.
Keywords: Multiple sclerosis Balance control Trunk sway Vibrotactile biofeedback Stance Gait
1. Introduction Multiple sclerosis (MS) is a chronic autoimmune inflammatory disease of the central nervous system (CNS) which can affect sensory and motor systems. Balance impairment is one of the key symptoms of MS, which leads to unstable walking patterns and increases the risk of falling (Cameron and Lord, 2010; Kalron and Achiron, 2013; Mazumder et al., 2015). Furthermore, fear of falling can lead to a curtailment of activity, physiological deconditioning, and institutionalization (Kalron and Achiron, 2013; Mazumder et al., 2015). One form of balance impairment is caused by diminished proprioceptive sensory information from the lower legs which triggers and modulates balance corrections in reaction to unexpected perturbations while walking or standing (Bloem et al., 2000). Proprioceptive deficits in MS are the result of slowed n
Corresponding author. E-mail address: [email protected] (J.H.J. Allum). 1 Equal first authors.
http://dx.doi.org/10.1016/j.msard.2016.05.003 2211-0348/& 2016 Elsevier B.V. All rights reserved.
somatosensory conduction and impaired central integration due to demyelination and axonal loss (Cameron and Lord, 2010; Cameron et al., 2008; Frohman et al., 2006). Diminished proprioceptive information leads to increased compensating movement in pelvis and shoulders to maintain balance during stance, as observed in lower-leg proprioceptive loss patients by the greater sway at the pelvis and shoulders while standing quiet with eyes closed on a firm support surface (Horlings et al., 2008, 2009a). Thus a similar balance deficit can be expected in MS patients. Clinically, MS is classified in different subtypes (Lublin and Reingold, 1996). Most of the patients ( 85%) have relapsing-remitting MS (RRMS) characterised by the relapses at disease onset. Relapses are subacute new symptoms or exacerbation of old symptoms which recover mostly partially within weeks. In contrast to this, in people with primary progressive MS (PPMS) the disease starts without relapses but with a continuous progression of disability. Relapses are possible later on but in general less frequently than in RRMS. Within 15 years most of the RRMS patients develop secondary progression with less relapse frequency and predominantly continuous progression of disability which is called secondary progressive MS. Deficits in balance affect about
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75% of all patients with MS and can occur in all clinical subtypes (Missaoui and Thoumie, 2009; McDonald et al., 2001). Thus all MS patient groups could presumably benefit from techniques which improve balance control. The effect of balance biofeedback on body sway has been explored in different modalities, including feedback of trunk linear acceleration, trunk angular position or velocity (Davis et al., 2010; Dozza et al., 2005; Hegeman et al., 2005; Verhoeff et al., 2009). Such biofeedback has been proven to have an effect on improving balance for healthy people (Verhoeff et al., 2009; Huffman et al., 2010a; Janssen et al., 2009), patients with either peripheral or central vestibular balance deficits (Basta et al., 2008; Dozza et al., 2007; Nanhoe-Mahabier et al., 2012). For stance and gait tasks differences in trunk sway angles and velocities improvements are observed (Kalron and Achiron, 2013; Verhoeff et al., 2009). For patients with balance deficits, the differential effect of position versus velocity vibrotactile biofeedback on stance and gait, respectively, is largely unknown. However, for normal subjects, position feedback is more effective for stance and velocity feedback more effective for gait (Janssen et al., 2009; Huffman et al., 2010b). MS patients tend to have relatively worse gait balance control compared to that of stance (Fanchamps et al., 2012). Therefore, the aim of this study was to investigate the effects of vibrotactile (VT) biofeedback training on MS patients during stance and gait tasks while receiving position and velocity feedback, respectively. We expected a greater improvement in gait based on the greater improvement observed with velocity biofeedback in young controls (Janssen et al., 2009). Additionally, this study investigated whether using a VT biofeedback system yielded a more beneficial carryover effect for MS patients once the VT biofeedback was removed. All results were compared with the effect of the same training but without VT feedback.
2. Methods 2.1. Subjects Ten MS patients (6 RRMS, 2 PPMS and 2 secondary progressive MS) were included in the study (mean age 46.8 77.7 years, 40% male, mean EDSS score at first test 3.9 71.7, median EDSS score 4.0. Range 2.5–6.0). Patients were excluded from the study if they were unable to walk without walking aids, had orthopaedic problems or other diseases/disabilities than MS that could affect their balance. All participants provided written informed consent to participate before the experiment started. The study was approved (026–2014 EKNZ) by the Ethical Committee NW Switzerland (responsible for the University Hospital Basel) and carried out according to the Declaration of Helsinki. 2.2. Experimental setup All 10 MS patients were enrolled in a crossover study design with a minimum two-week interval between the measurement days of each crossover arm. Two additional patients dropped out after their first visit due to scheduling conflicts. Patients were randomly assigned to a starting crossover arm with or without VT biofeedback. Patients performed assessment and training sequences consisting of stance and gait tasks while trunk sway was measured with a SwayStar™ device (Balance International Innovations GmbH, Switzerland). This device measures the angular velocities of the trunk in the pitch (anterior - posterior) and roll (medial lateral) planes using two gyroscopes mounted near the body's centre of mass (Allum and Carpenter, 2005), in the centre of the lower back at vertebral level L3-L5. An elasticated belt was used to
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Table 1 List of assessment and training tasks in the order tasks were performed within these sequences. Assessment tasks Standing 1 leg eyes open (20 s) Standing 2 legs eyes closed (20 s) Standing 2 legs eyes open on foam (20 s) Standing 1 leg eyes open on foam (20 s) Standing 2 legs eyes closed on foam (20 s) Tandem stance eyes open (20 s) Walking 8 tandem steps eyes open Tandem stance eyes closed (20 s) Walking 8 tandem steps eyes closed Walking over barriers Walking 8 m eyes open Walking 3 m eyes closed Training tasks Standing 2 legs eyes closed (20 s) 3x Standing 1 leg eyes open on foam (20 s) 3x Standing 2 legs eyes closed on foam (20 s) 3x Tandem stance eyes closed (20 s) 3x Walking 8 tandem steps eyes open 3x Walking 3 m eyes closed 3x Walking 8 m eyes open 3x
Order of sequences: First assessment ↓ Training sequence ↓ Second assessment ↓ Third assessment
The assessment sequence was repeated twice after the training sequence. For the measurement arm with VT biofeedback patients also received VT biofeedback during the second assessment. The results of the 2nd and 3rd assessment with and without VT biofeedback were compared with the results of the 1st assessment.
strap the attached Swaystar™ system around the patients’ waist. The SwayStar™ device has been validated in a number of studies in MS patients (Fanchamps et al., 2012; Findling et al., 2011; Corporaal et al., 2013). For the measurements, patients removed their shoes to avoid measurement variations due to shoe types. Patients performed the assessment sequence three times and the training sequence of trial protocols once per crossover arm on the same day with sufficient breaks between sequences to avoid fatigue. Trials were always performed at the same time of day (generally mornings) for each patient to avoid diurnal differences in fatigue levels affecting the results. The training sequence was performed after the first assessment sequence. The order of tasks within the assessment and training sequences is listed in Table 1. A BalanceFreedom™ add-on to SwayStar™ was used to provide patients direction-specific VT feedback during the training sequence and during the second assessment sequence if patients were in the investigational arm with VT feedback. This head mounted device is connected to the SwayStar™ and uses eight vibrotactile actuators spaced at 45 degree to indicate the direction of sway once a threshold of sway angle or velocity was exceeded. Task-specific biofeedback thresholds for angle (used during stance tasks) and angular velocity (used during gait protocols) were set at 90% of the 90% range results acquired during the first pre-training assessment sequence from each patient. Patients were requested to reduce sway as much as possible during the training and subsequent assessment sequences. When receiving VT biofeedback of trunk sway, they were requested to avoid activating the VT transducers and if these were activated to move away from the direction indicated by the feedback. A 5–10 min break took place between all assessment and training sequences. Assessment sequences consisted of 12 tasks and the training sequence included 7 of these tasks, 4 stance and 3 gait tasks (see Table 1). Tasks were stopped when a patient lost balance or completed the task. Stance tasks were performed maximally for 20 seconds. For 2-legged stance tasks (except tandem stance), participants stood on a foam or firm surfaces with their feet shoulder width apart and their arms hanging next to their body. They were asked to stand as quiet as possible and asked not to talk during the trials. For eyes open stance tasks,
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Table 2A Effect of vibrotactile biofeedback training. Task
ΔRA in deg (SEM)
S1EO S2EC S2EOF S1EOF S2ECF TSEO W8TSEO TSEC W8TSEC WOB W8MEO W3MEC
2.92 0.07 0.20 2.99 0.26 2.01 3.11 0.78 2.94 2.29 0.31 0.92
(3.36)* (0.14) (0.24) (1.66)* (0.19) (0.97)* p¼ 0.04 (1.33)* (1.48) (2.18) (1.43)* (0.28) (0.48)
ΔRV in deg/s (SEM) 1.13 0.66 1.01 10.65 0.15 3.06 4.22 6.32 4.05 2.20 3.78 2.52
ΔPA in deg (SEM)
(7.80)* (0.21)* p ¼0.017 (0.62) (6.84)* (0.55)* (3.73)* (2.61)* (3.67) (3.11) (4.31) (2.94) (1.84) *
1.15 0.12 0.56 0.95 0.45 0.87 2.29 3.55 2.35 1.28 0.26 1.24
(3.15)* (0.17) (0.58) (1.72) (0.36)* (1.19) * (1.36)* (2.91)* (1.04) p ¼ 0.050 (1.32)* (0.51) (1.28)
ΔPV in deg/s (SEM) 13.43 1.36 2.01 0.57 0.27 0.66 3.21 9.59 2.32 5.48 13.87 5.24
(9.28)* (0.26)* p¼ 0.005 (0.64)*p ¼ 0.005 (2.87)* (0.69)* (2.66)* (2.50)* (4.23)* p ¼0.04 (2.56) (4.25) (6.03) p ¼0.022 (3.61)*
Results are given in increase (positive) or decrease (negative) in trunk sway variable for the second (first post-training) assessment with VT biofeedback compared to the first (pre-training) assessment without biofeedback. Grey shaded values indicate a significant change between pre and post-training measurements for which p values are provided. Bold values indicate a significant difference between training conditions (none versus with VT biofeedback). Task abbreviations are listed in the methods section. R stands for roll A for angle, V for angular velocity, P for pitch, Δ for increase or decrease. * ¼ First assessment (pre-training) showed a significant difference between patients and 20 healthy age- and gender-matched controls – data from (Huffman et al., 2010b; Findling et al., 2011). Healthy control measures were not available for the W8TSEC task.
patients were instructed to fixate on a point at eye height 5 m away. All tasks were demonstrated to the patients. During all tasks a spotter stood next to the patient to support them in case balance was lost. 2.3. Assessment sequence Five stance tasks were performed first: standing on one leg with eyes open (S1EO); standing on two legs with eyes closed (S2EC); standing on two legs with eyes open on foam (S2EOF); standing on one leg with eyes open on foam (S1EOF); standing on two legs eyes closed on foam (S2ECF). Next, tandem stance (TSEO) and walking eight tandem steps (W8TSEO) were performed with eyes open and afterwards these two tasks were performed with eyes closed (TSEC, W8TSEC). Then patients were asked to walk over a set of low (24 cm) barriers spaced one meter apart (WOB). Finally, patients walked eight meters with eyes open (W8MEO) and three meters with eyes closed (W3MEC). The first assessment sequence was used to set VT thresholds individually. The second assessment which took place after training was used to assess the combined effect of VT feedback during training and during the assessment and the third assessment which was without VT feedback was used to assess the carry-over effect VT feedback during training and the prior assessment. 2.4. Training sequence For the training sequence, tasks were executed three consecutive times. This sequence consisted of: standing two legs eyes closed (S2EC); standing one leg eyes open on foam (S1EOF); standing two legs eyes closed on foam (S2EOF); tandem stance eyes closed (TSEC); walking eight tandem steps eyes open (W8TSEO); walking three meters eyes closed (W3MEC); walking eight meters eyes open (W8MEO). The tasks comprising assessment and training sequences are listed in Table 1. 2.5. Data analysis SwayStar™ measurements for the 90% range of pitch (P) and roll (R) sway angle (A) and the 90% range of pitch and roll sway angular velocity (V) for each task were examined as outcome measures. The duration until task completion or loss of balance for every task was the fifth outcome measure. A Wilcoxon signed-rank test was performed using SPSS (IBM SPSS statistics 20, Chicago, IL, USA) to compare the results of the pre-training assessment with
the second assessment sequence (with and without biofeedback) and the third assessment sequence (no biofeedback). A Wilcoxon signed-rank test was used because of the sample size. The third trial of each task during the training sequence was used to assess the direct training effect. To test whether vibrotactile feedback led to an increase or decrease in sway angle and sway angular velocity for all tasks within the assessment sequences, differences were computed for trunk sway between pre-training and the first posttraining assessments with biofeedback. These differences were formed for the arm with and without VT feedback. To determine if there was a difference in carry-over effects depending on the training condition (none or VT feedback) the second post-assessment sequence (3rd assessment) measures were compared with those of the first pre-training assessment. These differences were compared with a Wilcoxon signed-rank test to determine if a significant effect of vibrotactile biofeedback versus none occurred for each task. Given the problems associated with formally correcting for multiple comparisons (Perneger, 1998) we present results flagged using the conventional (p r0.05).
3. Results 3.1. Effects of vibrotactile biofeedback on stance tasks Although there was generally a reduction in trunk sway with VT feedback (Table 2A), not all of the changes were significant or significantly different from providing training without VT feedback. For the easier stance trials an increase in sway velocity was noted with VT feedback. For example, a significant increase in RV was observed during VT training sessions (p ¼0.013) and posttraining in second assessment trials with VT feedback on (p ¼0.017) for the S2EC task (Table 2A). Likewise, for the S2EOF task with VT feedback there was an increase in PV in the second assessment trial (p ¼0.005) compared to the first assessment. This increase significantly differed from the no-feedback S2EOF measurement (p ¼0.012). Biofeedback during tandem stance tasks led to variable results. TSEO showed a decrease in RA (p ¼ 0.037) during the second assessment compared to the pre-training assessment trial. The tandem stance task with closed eyes also led to a decrease in PV during the second assessment (p ¼ 0.036) and a carry-over effect occurred (p ¼0.028) during the third assessment trials. However, similar results were found during the training alone (no VT feedback) measurements.
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Fig. 1. Differences in RA, PA, RV and PV for training alone (no VT feedback) and VT feedback conditions for the W8MEO task. Δα: difference between pre-training assessment and training sequence. Δβ: difference between pre-training assessment and second assessment (post-training). Δγ: difference between pre-training assessment and third assessment trial (post training carry-over effect). *indicates significant difference between training conditions.
3.2. Effects of vibrotactile biofeedback on gait tasks During the W8MEO second assessment trial a significant decrease in PV was found (p ¼0.022), whereas the training alone (without VT feedback) measurement resulted in a small, insignificant increase. This resulted in a significant difference between feedback and training alone (p ¼ 0.036). These findings are shown in Fig. 1. 3.3. Training alone (without VT feedback) There was a general increase in trunk sway when training without VT feedback was provided (Table 2B). For example, training alone resulted in an increase in PV (p ¼0.017) during the S1EO second assessment. S2EC RV measures showed a decrease during post-training assessments, but this decrease was only significant during the training (p ¼0.017). Gait tasks did not show any significant differences in balance measures after training alone (no VT feedback). However, the duration of W8TSEO and WOB tasks decreased significantly during post-training assessment trials. These differences in duration are shown in Fig. 2.
4. Discussion 4.1. Effects of vibrotactile biofeedback training This study showed there is a significant difference in balance control when MS patients trained and were assessed with vibrotactile biofeedback compared to training and assessment
Table 2B Training alone effects. Task
ΔRA in deg (SEM)
ΔRV in deg/s (SEM)
ΔPA in deg (SEM)
ΔPV in deg/s (SEM)
S1EO S2EC S2EOF S1EOF S2ECF TSEO W8TSEO TSEC W8TSEC WOB W8MEO W3MEC
4.85 0.22 0.18 3.65 0.29 2.20 1.33 2.97 2.52 1.78 0.31 0.07
8.72 0.40 0.41 6.19 0.33 1.58 2.07 3.58 2.79 3.88 0.67 2.47
6.42 0.06 0.10 0.78 0.39 0.57 2.28 2.21 0.77 2.29 0.62 0.45
9.90 0.08 0.32 7.28 0.75 0.16 2.46 9.91 1.51 2.37 5.25 5.35
(4.08) (0.16) (0.13) (1.79) (0.54) (2.52) (1.62) (2.39) (1.26) (1.49) (0.68) (0.50)
(6.28) (0.41) (0.55) (7.48) (0.78) (4.00) (2.47) (3.54) (3.30) (3.32) (1.89) (2.68)
(4.23) (0.25) (0.30) (2.24) (0.60) (0.50) (2.52) (1.78) (2.27) (2.05) (0.41) (0.69)
(5.43) p ¼0.017 (0.27) (0.36) (7.54) (1.27) (2.27) (2.81) (7.22) (3.01) (5.22) (2.64) (3.52)
Results are given in increase or decrease in trunk sway variable for the second (first post-training) assessment compared to the first (pre-training assessment) Both without VT biofeedback. Grey shaded values indicate a significant change between pre and post-training measurements. Bold values indicate a significant difference between training conditions (none versus with VT biofeedback). These are the same measures indicated in Table 2A. Abbreviations are described in the legend for Table 2A.
without feedback. Although decreases in sway occurred in several tasks with feedback, many were not significant when compared to training and assessment without VT feedback. Our current result reinforce the point that devices that provide balance feedback during training and assessment sessions need to be tested by comparing with the effect of training and assessment without feedback and not by just examining the difference between a first
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14,0
Duraon in seconds
12,0
*
10,0
*
8,0
* *
6,0
W8TSEO
WOB
4,0
It is well-known that fatigue is a confounding factor for trials with MS patients. For example, fatigue increases for 6 min walking trials with EDSS scores (Leone et al., 2015). We attempted to avoid fatigue by providing patients with adequate rest periods of 5– 10 min between each assessment which lasted 10 min and after training. Nevertheless, lack of a strong carryover effect in this study may have been due to the confounding effect of fatigue. Differences between balance measures for the VT and no feedback protocol arms of this study would not be influenced by fatigue as these involved the same tasks and durations.
2,0
4.2. Training alone (without VT biofeedback)
0,0 First assessment Training
Secon d
Third assessment
Fig. 2. Mean durations (and SEM) of W8STEO and WOB for training alone without VT biofeedback. *Marks a significant difference (p o 0.05) with respect to the first assessment.
assessment without feedback to a second with feedback. As with normal subjects (Davis et al., 2010; Huffman et al., 2010b), providing balance feedback during training for stance tasks leads to an increase in sway velocity. For example, two-legged stance tasks with eyes closed on firm surface showed an increase in trunk angular velocity in the roll and pitch plane when biofeedback was given. The same reaction occurred during the standing on foam with eyes open task, where angular velocity was significantly enhanced in the pitch but not in the roll plane. In both tasks, enhancements differed from the results of the without feedback measurements. The increase in trunk angular velocity is possibly related to faster, shorter reactions of biofeedback compared to the reaction on losing balance for no feedback. In our previous studies on normal subjects (Davis et al., 2010; Huffman et al., 2010b), enhancement in angular velocities were accompanied by a decrease in trunk sway angle. Possibly the absence of a change in sway angle can be explained by the fact that MS-patients judged the correction amplitude incorrectly even with feedback due to a mismatch with available proprioceptive information. Interestingly, given the difficulties MS patients have with gait, all gait tasks showed a higher decrease for angular velocity in pitch and roll plane when biofeedback was given compared to none. During the walking 8 m eyes open task a significantly higher decrease in sway angular velocity occurred in the pitch plane when VT biofeedback was provided. Janssen et al. Janssen et al. (2009) also reported a decrease in sway velocities and task specific reductions in sway angles in their study on healthy young subjects. However, in our study, no significant decreases in sway angle were found in comparison to no VT feedback (training alone). Overall, the greatest differences with pre-test were found during the second assessment trial with biofeedback. A carry-over effect of biofeedback to the third assessment for which no feedback was provided was only found for pitch plane trunk angular velocity in the tandem stance eyes closed task. This significant decrease was also found in the first post-training assessment sequence. However, training alone (no feedback) also showed a decrease in trunk angular velocity. Therefore, the difference between biofeedback and none was not significant. The question arises if performance with VT feedback is worse in patients with higher EDSS scores given that their balance control deficits are correlated with their EDSS scores (Corporaal et al., 2013). In this study we used individually set thresholds and therefore cannot answer this question. In other studies where population set thresholds have been used, improvements are greater for those with initially poorer balance control because these subjects reached feedback thresholds more often (Davis et al., 2010).
Training alone (Table 2B) resulted in few significant differences between the pre-training and post-training assessments. For walking eight tandem steps eyes open and walking over barriers, gait speed increased when no feedback was provided as shown in Fig. 2. This decrease in trial duration can be possibly explained by a learning effect (Horlings et al., 2009b). 4.3. Future studies Our results showed that vibrotactile biofeedback of trunk sway leads to an immediate effect on trunk sway in MS patients without prior experience with such biofeedback. Although a significant effect was found, the sample size was small. Therefore, it would be interesting to repeat the study with a greater sample size and a greater period of training. We would expect, however, that the direction of the effects, greater for VT feedback than for training without VT feedback would be the same as noted in studies on controls and other patient groups (Davis et al., 2010; NanhoeMahabier et al., 2012). Some patients indicated that initially they had difficulties reacting to the VT biofeedback. As the vibrotactile biofeedback was received on their head they encountered difficulties in reacting to the biofeedback by changing the angle of their trunk. The initial reaction was to move the head and only after training did they move with their trunk. Providing patients with biofeedback around their trunk might be a solution for this problem. However, as discussed by Verhoeff et al. (2009) the 20–30 ms transmission delay for balance information between trunk versus head VT feedback and to the CNS may have an impact on balance control. Despite these initial learning steps, MS patients were able to reduce sway during gait more than during stance (Table 2A). This is crucial because gait is relatively more affected than stance in MS patients (Kalron and Achiron, 2013; Mazumder et al., 2015; Perneger, 1998). Our study helps understanding reactions of MS-patients to VT biofeedback. However, further research is needed to investigate how VT biofeedback could be used to prevent falling and how much biofeedback training can induce a meaningful carry-over effect on balance control. A carry-over effect would reduce the need to provide VT balance biofeedback continuously.
5. Conclusion This study showed that vibrotactile biofeedback leads to an improvement in balance control of MS patients over that provided by training alone (no feedback). The effects differed between gait and stance tasks as in healthy subjects. Vibrotactile feedback was only effective while wearing the device; a significant carry-over effect was not observed with biofeedback. To see whether more extensive biofeedback training can lead to a more permanent effect and which frequency and duration of training is most effective, further research with larger group of cohorts is needed.
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Conflict of interest The author JHJ Allum declares a conflict of interest as he worked as a consultant for the company producing the SwayStar equipment used in this study.
Funding This research was supported by grants from the Freiwillige Akademische Gesellschaft of Basel and the Swiss MS Society to Dr. O Yaldizli and Dr. JHJ Allum. RP Van der Logt was also supported by a grant from the Radboud University Medical Centre, Nijmegen and the Nijmegen University Fund.
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