High-level sports performance requires excellent balance ability (15). Balance performance relies on the ability to integrate visual, somatosensory, and vestibular information (37) and to adapt the contribution of each sensory system according to the environment (1). Expert athletes in gymnastics (6), soccer (28), judo (30), and ironman triathlon (25) have been shown to rely less on vision for postural control when their balance performance without visual information was compared with controls (6,25,28,30). It has been suggested that decreased visual dependence for postural control allows expert athletes to dedicate their visual attention to their athletic activity or game (28). Therefore, sensory integration aspects of different balance exercises should be considered by strength and conditioning specialists. Specifically, it is important to identify whether balance exercises such as unstable surfaces training facilitate somatosensory activation or visual dependence.
In 1965, Freeman et al. suggested that foot and ankle instability associated with recurrent ankle sprains results from deficits in somatosensory input (cutaneous joint position sense and movement) because of damage to the capsule and ligaments' mechanoreceptors. To recover this “motor incoordination,” they recommended “coordination exercises” in the form of standing on wobble boards (10). This notion was later termed “sensorimotor training,” or “proprioceptive training,” and has become a popular intervention to prevent and treat ankle sprains (36). Proprioceptive training today could include single-leg standing with eyes closed, and balancing on other unstable and compliant surfaces such as the both-sides-up (BOSU) balance trainer ball (23). The design of the BOSU provides a solid plastic base integrated with an inflatable rubber bladder that resembles a halved Swiss ball (45). The theoretical model of functional instability has later been expanded by Hertel to include conscious perception of somatosensory information, reflex responses, and motor control deficits, all of which may be present with ankle instability (14). When a person experiences an ankle sprain, a key concern in training is to prevent the development of instability and repeated ankle sprains (27). For that reason, proprioceptive training targeting restoration of proprioceptive function is common practice (36). Over time, however, the ability to improve proprioception by exercise has been questioned (2). Today, over 40 years since the original introduction of the Freeman theory, there is little question that training on unstable and compliant surfaces such as BOSU balls can improve standing balance performance (24,34) and sports-related activities performance (45). What remains unclear is how much of the observed improvement in motor performance is due to neural adaptions in somatosensory integration (2) or the other reasons such as improved strength, endurance (2), or compensation by reliance on visual cues (2). Note that improvements in standing balance with eyes closed post-training were seen when a BOSU training program also included exercise with eyes closed (24) but not when all exercises were conducted with eyes open (35).
Interestingly, neurological rehabilitation has a different clinical theory regarding the use of compliant surfaces in balance assessment and interventions. In 1990, Nashner and Peters developed the Sensory Organization Test wherein a sway-referenced platform was used to alter sensory information (26). This perspective was expanded to include compliant surfaces such as foam which are consistently used in neurorehabilitation research as a method of disrupting the somatosensory contribution to balance (29). Because the reliability of information received from cutaneous receptors and proprioceptors is affected when standing on compliant surfaces, somatosensory processing for balance is reduced (21), presumably increasing reliance on visual and vestibular inputs (41). This has been applied in the clinic through tests such as the Clinical Test of Sensory Interaction and Balance (37) wherein a participant's response while standing on foam is assumed to represent mostly visual and vestibular integration (or vestibular cues only, with closed eyes). Evidence supporting the neurorehabilitation perspective was provided by showing increased sway when participants were standing with their eyes closed on foam as compared with eyes open (40). In addition, some studies indicated that people with visual impairments produced more body sway on a foam surface compared with people with normal vision (40), especially when a secondary task was introduced (21). Others, however, demonstrated that postural sway is also increased in single limb stance in a dark environment (12), suggesting that visual dependence could be a function of how challenging a task is regardless of the surface properties.
Proprioceptive training, including compliant surfaces' exercises, is a popular intervention among strength and conditioning specialists, and its effect on balance performance and injury prevention has been tested in dozens of studies (27,36). However, studies attempting to explain the underlying mechanism of improvements in balance after such training are still lacking. The purpose of this study was to test the hypothesis that visual dependence is increased during a single exercise session on challenging compliant surfaces in young adults with and without history of repeated ankle sprains. If supported, this will suggest that challenging compliant surfaces might be used to specifically facilitate utilization of visual cues in people with balance problems associated with sensory deficits but may not be optimal for athletes or patients trying to decrease their visual dependence and improve their ability to focus on somatosensory cues, the environment, and the activity.
Experimental Approach to the Problem
The neurorehabilitation clinical theory suggests that visual dependence increases when a person is standing on compliant surfaces. To test that, we applied sophisticated motor control techniques used to study “sensory weighting and reweighting” (17,31) (amounts of response to a sensory stimulus). Jeka et al. demonstrated that when small oscillating sensory stimuli (e.g., visual field movement) were provided at slow frequencies and low amplitudes to people while standing, they tended to match the frequency and amplitude of their body sway to the stimuli (1,18). Peterka showed that healthy adults tended to match their body sway to a rotating visual surround when the frequencies of the stimulus were between 0.1 and 0.8 Hz and decreased that match (reweighting) at lower or higher frequencies (31). We analyzed the frequencies and amplitudes of a participant's body sway in response to visual stimuli of 3 frequencies while maintaining standing balance on one of 3 surfaces: firm plate, memory foam, and BOSU ball. This allows for quantification of visual dependence during exercises that are commonly prescribed by strength and conditioning specialists (17).
The sample included 30 healthy young adults (HEALTHY) and 10 participants with history of recurrent ankle sprains (SPRAIN), who are presumed to have compromised lower leg proprioception (14). Recruited participants were of any race or ethnic background, men and women, aged 18–40 years, with normal or corrected to normal vision. Eligible HEALTHY participants had not had any lower limb or back injury within the 12 months before the study and were excluded if any evidence of somatosensory or vestibular loss, or if limited dorsiflexion (<10°) was found during a clinical screening. Participants in the SPRAIN group had to have 3 or more sprains in the past 5 years, a previous diagnosis of a moderate inversion ankle sprain, and at least 1 episode of the ankle “giving way” in the past 12 months (8). This study was approved by the Institutional Review Board of the University of Washington, Seattle, and a signed informed consent was obtained from all participants.
To determine eligibility, participants with SPRAIN were interviewed over the phone before testing. They were asked about their history of ankle sprains and completed the ankle instability instrument (AII) (7) and the foot and ankle ability measure (FAAM) (5). The AII was found to be highly reliable among college students (7). Carcia et al. reported construct validity of the daily and sports subsections of the FAAM by showing that scores of both subscales were greater in healthy athletes than in those with chronic ankle instability and in athletes who indicated that their ankles were “normal” compared with those who reported their ankle to be nearly normal or abnormal (5).
Clinical and demographic characteristics by group appear in Table 1. The mean age for the HEALTHY group was 28.5 years (SD = 5.4) with 60% women. Participants in the SPRAIN group were on average younger (mean = 22.2, SD = 4.6 years) with 60% women. All but 3 participants were participating in different sports activities on a regular basis, often more than one. The most common activities reported were running/jogging (21 participants), resistance training (20 participants), and biking (14 participants). Other activities reported more than once included elliptical (5 participants), swimming, yoga, dance and treadmill (3 participants), basketball (2 participants). Two participants were previous gymnasts. The SPRAIN group was on average more active as evident by minutes of weekly exercise and had lower scores on the balance error scoring system (BESS). Eight participants had 5 or 6 “yes” responses on the AII. The entire group scored 80% or higher on the daily section of the FAAM. A wider range was observed on the sports section of the FAAM (28–100%).
Participants visited our laboratory twice, once for a short clinical screening (up to 30 minutes) and again for testing (about 2 hours). On the first session, the participants completed a demographics questionnaire and were interviewed regarding physical activity habits. We then measured their height and weight and performed a clinical screening. The screening included smooth pursuit, saccades, and the dynamic visual acuity test; (22) Semmes monofilament testing (33) and bilateral lower leg recognition of vibration by a tuning fork (cutaneous and vibration sensation); and ankle range of motion. Those tests were used to confirm the inclusion criteria of normal sensory function and ankle dorsiflexion in our sample. Participants also performed the BESS (single-leg conditions only), a tool commonly used by researchers and clinicians to evaluate balance in young adults. People with functional ankle instability have been shown to perform worse on the single-leg conditions of the BESS compared with controls (9).
During the testing session, participants were asked to stand on each of the 3 surfaces: floor, foam, and BOSU. On all surfaces, participants stood barefoot and were asked to do whatever felt natural to them to maintain their balance. For the floor condition, participants stood on a firm wooden plate placed on a force platform. For the foam condition, participants stood on high-density (6 lb·ft−3) memory foam (10 × 36 × 36 cm) placed over the wooden plate. We replaced the foam after every 4 participants to assure that its viscoelastic properties were maintained. On floor and foam, participants stood with their feet together. For the third condition, participants stood with feet hips-width apart on a BOSU balance trainer (Fitness Quest, Canton, OH, USA) with the compliant side up. The BOSU was placed on a wooden plate, which matched the flat side of the BOSU (61 cm2) to the smaller force platform (59 × 39 cm rectangle). To assure consistent foot placement between trials on the floor and foam, a researcher marked the heel position of the participants. On the BOSU, the participant's hip width was measured with calipers. The researcher then marked the location of the medial right and left big toes with adhesive tape on top of the compliant side of the BOSU.
Participants wore a safety harness, and a licensed physical therapist (PT) or a PT student guarded and instructed them throughout the testing session. Two 4-point canes, placed at either side of the BOSU or foam, supported participants getting on and off the surface or if they lost their balance. Participants were asked to observe dots projected on a screen located 1 m in front of them (17). The visual stimulation used a Toshiba TDP-EW25U projector, a Draper Cinefold Portable Cineflex Rear Projection Screen, and custom software to generate oscillating visual stimuli. Planar projections of circular dots were distributed in a fixed pattern (initially randomized over the area), except for a clear central area of occlusion of 32 cm in diameter. The clear central area was made to suppress the visibility of “sampling artifacts” or aliasing effects, which are most likely to occur in the foveal region (42). The projected image had a width of 163 cm and height of 120 cm; the diameter of the dots was 10 mm, and the horizontal movement amplitude was 4.5 mm (total range of 9 mm). The dots were moving in one of the 3 frequencies: 0.40, 0.48, and 0.56 Hz. Those frequencies of visual stimulus motion were shown to be within a comfortable range for healthy adults (31).
Each frequency was repeated 3 times on each of the surfaces. These visual trials were part of a larger study that included application of Achilles' tendon vibration, the results of which will be reported elsewhere. Each condition lasted 60 seconds and was administered in 2 blocks on each surface with rest breaks of 5–10 minutes. The order of the blocks and that of the conditions within each block was randomized but was kept constant between surfaces. The room was darkened, and participants wore goggles that prevented them from seeing beyond the edges of the visual screen. They also wore headphones that played a white noise audio loop (Plantronics P590 Bluetooth headset, Jabra A320 Bluetooth transceiver, and Apple iPod shuffle containing the audio file) to prevent distractions from sounds in the environment. The experimental setup when a participant was standing on the BOSU can be seen in Figure 1.
Data Reduction and Measurements
Force plate data were sampled at 100 Hz (20) by a Kistler 9281A11 multicomponent force platform. It has been shown that the majority of lateral postural sway energy lies between 0.3 and 1.05 Hz (38). Therefore, a 0.05–1.0 Hz, fourth order zero-lag Butterworth band-pass filter was applied (43). The data were smoothed through a Welch smoothing window to avoid spectral leakage, along with a tolerance interval to detect response peaks within 0.02 Hz of the stimulus. A spectral analysis of the time domain data was then conducted using custom written LabView software (Figure 2). Because the visual stimulus was in the frontal plane, only mediolateral data were analyzed. The first 5 seconds were excluded from analysis to eliminate transient responses. Detailed definitions of our descriptive measures, outcome measures, and specific research hypotheses are described in Table 2.
The strength and timing of a sensory response are often quantified by gains and phases relative to the stimulus (18). Our primary outcome measure, the visual gain, is a unitless estimate of the magnitude of the postural response divided by the magnitude of the stimulus, in our case 4.5 mm, at the stimulus frequency (3). The phase describes the temporal relationship between postural sway and stimulus, and in our study was measured in degrees (3). When a person perfectly matches their timing of sway to the stimulus, phase values are expected to be tightly clustered around 0. Because gains are higher with larger magnitude of body sway, and people tend to sway more on compliant compared with firm surfaces (39), we also measured participants' primary frequency (PF) (38). Primary frequency detects the frequency of the peak that has the greatest body sway amplitude and is independent of amount of sway (38). It indicates how closely individuals match their sway to the stimulus provided. An example of PFs from spectral analysis of 1 participant on a single trial can be seen in Figure 2. Gains, phases, and PFs were calculated from the mean of 3 trials in each condition.
Descriptive analyses (i.e., numeric summaries and visual displays) were used to characterize demographics, clinical measures, and the phases of the 2 samples. To eliminate bias because of fatigue or learning, the order of the conditions was randomized. The optimal analysis for such structure of data is a randomized block model within a specific frequency, where each individual is considered a block and surfaces are considered the randomized treatments. A repeated-measures model is not appropriate for our data because it does not account for the randomization of the data, and therefore information could be lost (4). Therefore, to test for mean differences in gains and PFs according to surface, we conducted a separate analysis of variance (ANOVA) for each frequency (4). When surface was statistically significant at 0.05, we performed Tukey's post hoc analysis to identify for which surfaces the mean values differed. To explore whether the behavior was similar in the SPRAIN group, we ran the same analysis for HEALTHY and SPRAIN groups. Analyses were conducted with IBM SPSS versions 21 for Mac and 22 for Windows.
Gains and Phases
For both groups, gains were similar on floor and foam and higher on the BOSU. Table 3 shows the ANOVA results for gains across surfaces and frequencies. The mean gain differed significantly between the 3 surfaces on all frequencies for both groups (p < 0.001 for all). Post hoc analysis showed the gains on the BOSU were different from floor and foam gains (p < 0.001 for all). Gains on the foam tended to be higher than on the floor (Table 3) with 1 significant difference in HEALTHY group (frequency 0.48 Hz, p = 0.04). All individual gains across surfaces and frequencies can be seen in Figure 3 (top part). Note that 2 participants with SPRAIN had higher gains on all conditions. Figure 3 (bottom part) shows individual phases in degrees. The phases appear to be clustered around 0 when participants were standing on the BOSU indicating that the participants attended to the stimulus provided. The phase ranges for floor and foam were extremely large with minimal temporal matching on those surfaces.
Table 4 shows the results for PFs across surfaces and frequencies. In the HEALTHY group, for each frequency, the mean PF differed among the 3 surfaces (p < 0.001 for the 3 models), and post hoc analysis in each model showed that the BOSU PF was different from the floor and foam PF (p < 0.01 for all), with no significant differences between floor and foam (p > 0.06 for all). The same results were seen for the SPRAIN group. Box plots displaying PF across surfaces and frequencies for both groups appear in Figure 4. Note that on the BOSU, the medians are concentrated around the visual stimulus frequency. For a more detailed analysis, we calculated the proportion of individuals whose PF was within 0.02 Hz of the input frequency (e.g., between 0.38 and 0.42 Hz when the input was 0.40 Hz), which are shown in brackets in Table 4. The BOSU surface consistently had more individuals “matching” the input frequency than the other surfaces, with percentages of 73% for low and medium visual stimulus frequencies and 57% for the high visual stimulus frequency in the HEALTHY group, and 70, 60, and 80% matching in the SPRAIN group for low, medium, and high frequencies, respectively. The foam and floor surfaces had very low percentages of individuals matching, with floor having the lowest matching.
In this study, we applied a novel approach (31) to quantify visual dependence and compared the participants' responses to visual cues between a firm surface and 2 compliant surfaces (BOSU ball and foam). We found that both groups, HEALTHY and SPRAIN, had a strong response to the visual stimulus when standing on a BOSU ball. Participants' sway at all visual stimulus frequencies on a BOSU ball exhibited high gains with clustered phases, and the peak amplitude sway frequency closely matched the stimulus frequency. Conversely, response to the visual stimulus when the participants were standing on the foam or floor was minimal. We conclude that a single session of stance on a challenging compliant surface such as a BOSU ball may force young adults to rely on visual cues for balance. At the same time, memory foam did not evoke visual dependence in young adults, possibly because balancing on foam was not challenging for them.
People with recurrent ankle sprains or other musculoskeletal or neurologic injuries that lead to sensorimotor deficits require specific balance training addressing neuromuscular control and proprioception (13). Although training on compliant surfaces such as BOSU balls is routinely used to improve balance and prevent ankle sprains (36), the physiologic mechanism of this training strategy has not been clearly identified (2,14). Our findings show that a single session of stance under highly challenging surface conditions led to a large increase in response to visual cues. Our results are in agreement with Hazime et al. who demonstrated visual dependence in 11 healthy young adults challenged by a single-leg stance position in a dark room (12). Although the mechanism of long-term improvements in balance after training on BOSU balls remains to be determined, it is possible that stance on BOSU balls should be incorporated into balance training when the session's goal is to facilitate utilization of visual cues (specific visual training for balance). At the same time, specific proprioceptive training and training of athletes who try to decrease their visual dependence might benefit from less challenging surface conditions and more challenging visual conditions (e.g., dark or visually distracting environment and eyes closed). For example, dancers demonstrated improved dynamic balance performance (measured as time to complete and reach distance on the star excursion balance test) after a progressive intervention with eyes closed, compared with controls who practiced with eyes open (16). Future studies should identify the effect of such interventions on proprioceptive function.
Memory foam is commonly used in neurological rehabilitation for assessing sensory integration (37). The use of a memory foam surface disperses foot pressure, and by that it is thought to change the afferent information from cutaneous and mechanoreceptors (proprioception) in the lower limb, forcing individuals to primarily rely on visual and vestibular cues to generate a balance response (44). Indeed, it has consistently been shown that closing the eyes when standing on foam leads to an increase in body sway amplitude (40) or increased anterior-posterior torque variance (29). Given that, we hypothesized that visual dependence, as measured by gains and PF, will be higher on the BOSU as compared with the foam and higher on the foam as compared with on the floor. Although the first hypothesis was supported, the second was rejected; visual dependence in healthy young adults was similar on the floor and the foam. Although gains were somewhat higher on the foam than on the floor in both groups, the responses were not statistically different. We therefore propose that increased dependency on vision for postural control is a factor of the interaction between the surface and the person (i.e., how challenging a balance task is to an individual) rather than on the support surface qualities alone. In other words, not all compliant surfaces will produce visual dependence for every person. A few technical differences between our work and that of others should be noted. First, we studied visual dependence by providing the participants with mediolateral visual stimuli that were intended to mimic translational visual movement encountered in daily living (17). Others looked at balance response on foam when visual input was eliminated by closing the eyes (29,37). Second, to prevent participants from “bottoming out” on the foam given the length of the task (60 seconds), we used high-density memory foam, whereas others used low (29) to moderate (37) density. In the future, the other types of foam should be tested and applied to patients with more severe balance problems to establish whether visual dependence gradually increases with increased level of support surface challenge.
Our sample of participants with SPRAIN was intended to represent a population with deficits in somatosensory processing (13) for whom balance interventions using unstable and compliant surfaces are commonly applied (32). All 10 participants met the basic criteria of functional ankle instability (8), and 9 of them had at least 4 “yes” responses on the AII (7). However, the sample was somewhat heterogeneous with 6 participants scoring >90% score on the daily subsection of the FAAM score and 3 scoring >80% on the sports subsection (5). Overall, our exploratory findings in this small sample were similar to those of our larger sample of HEALTHY. The responses of people with SPRAIN were greatly magnified when standing on the BOSU compared with the floor or foam. Descriptive statistics also showed that people with SPRAIN generally had a greater response to vision compared with HEALTHY across surfaces at most visual stimulus frequencies (Tables 3 and 4, and Figures 3 and 4). This may have occurred because 2 participants with SPRAIN showed a strong response to the visual stimulus regardless of the surface on which they were standing (Figure 3). Of the 2, one participant had very low BESS scores when standing on 1 leg on the foam with eyes closed (failure on the right and −8 on the left) and a particularly low FAAM sports score (43%). The other individual had a score of −3 for the same BESS conditions (better than the mean of the group) and a FAAM sports score of 75%. This participant, however, was the only one in the SPRAIN group who was not physically active.
Some limitations of this study should be noted and addressed in future research. First, our clinical sample (SPRAIN) was small and heterogeneous. Although 2 participants had large responses to the visual stimulus across surfaces, most established visual dependence that was similar to healthy young adults. This may be because most of the participants were physically active, and some were fairly confident in their balance abilities. In the future, we plan to study a larger sample of participants with a more stringent definition of functional ankle instability. The finding of similar visual dependence between floor and foam also needs to be tested in a clinical sample with more severe balance problems (e.g., patients with unilateral vestibular loss). It is possible that for them, standing on foam will provide enough challenge to facilitate visual dependence. Second, our findings in the HEALTHY group are limited to young and physically active adults. Third, our participants' foot position was different between the surfaces. On the floor and foam, participants were standing with feet together to increase the level of challenge. On the BOSU, however, standing with feet together was not feasible because participants found it too hard to balance for 60 seconds. It is possible that a wide stance made it mechanically easier for the participants to follow the dots with an abduction/adduction hip strategy, and this might partially explain the large differences in matching we observed. However, previous work by Goodworth et al. showed that frontal plane movement of visual stimulus had minor influence on balance when participants adopted a wide stance as compared with a narrow stance (11), supporting our hypothesis of visual dependence as a function of level of challenge. We did not analyze the frequency distribution on each surface without visual distractors. It is therefore theoretically possible that people display higher frequencies when balancing on the BOSU. However, we did analyze 3 different frequencies (low, medium, and high) and observed increased matching on the BOSU at all three. Participants were tested on different hours during the day (morning, early afternoon, and late afternoon). Previous research identified a relationship between balance performance and time of testing in older adults (19). Although we did not control for the time of testing, our findings were consistent among most participants. Finally, our findings are applicable to a single session of stance on a BOSU. Because we did not measure training effects, we cannot infer what happens to visual dependence for postural control after a training program on a BOSU ball.
We found that the high level of challenge during a single session of static stance on compliant surfaces facilitates use of visual cues more than moderate or low levels of challenge. When prescribing balance training to young adults, strength and conditioning specialists should consider how increasing the level of challenge affects sensory integration and whether this aligns with the specific goals of the training session. For instance, if you are training novice athletes perhaps you want to train them to be less dependent on their vision for balance to be able to allocate visual attention to their environment. Also, the literature suggests that people with functional ankle instability should be trained to regain their somatosensory function rather than increasing their reliance on vision. In these examples, increased visual dependence could be counter-productive.
The authors thank Deborah Kartin, PT, PhD, for consultation and assistance with data collection. The authors thank Alex Bennett, DPT, and Somer Kreisman, SPT, for assistance with data collection. This work was funded by the Walter C. and Anita C. Stolov research award, University of Washington, Department of Rehabilitation Medicine. Study sponsors had no involvement in the research project or article production.
1. Allison LK, Kiemel T, Jeka JJ. Multisensory reweighting of vision and touch is intact in healthy and fall-prone older adults. Exp Brain Res 175: 342–352, 2006.
2. Ashton-Miller JA, Wojtys EM, Huston LJ, Fry-Welch D. Can proprioception really be improved by exercises? Knee Surg Sports Traumatol Arthrosc 9: 128–136, 2001.
3. Bair WN, Kiemel T, Jeka JJ, Clark JE. Development of multisensory reweighting for posture control in children. Exp Brain Res 183: 435–446, 2007.
4. Belle GV, Kerr KF. Design and Analysis of Experiments in the Health Sciences: John Wiley & Sons, 2012.
5. Carcia CR, Martin RL, Drouin JM. Validity of the foot and ankle ability measure in athletes with chronic ankle instability. J Athl Train 43: 179–183, 2008.
6. Croix G, Chollet D, Thouvarecq R. Effect of expertise level on the perceptual characteristics of gymnasts. J Strength Cond Res 24: 1458–1463, 2010.
7. Docherty CL, Gansneder BM, Arnold BL, Hurwitz SR. Development and reliability of the ankle instability instrument. J Athl Train 41: 154–158, 2006.
8. Docherty CL, Moore JH, Arnold BL. Effects of strength training on strength development and joint position sense in functionally unstable ankles. J Athl Train 33: 310–314, 1998.
9. Docherty CL, Valovich McLeod TC, Shultz SJ. Postural control deficits in participants with functional ankle instability as measured by the balance error scoring system. Clin J Sport Med 16: 203–208, 2006.
10. Freeman MA, Dean MR, Hanham IW. The etiology and prevention of functional instability of the foot. J Bone Joint Surg Br 47: 678–685, 1965.
11. Goodworth AD, Mellodge P, Peterka RJ. Stance width changes how sensory feedback is used for multi-segmental balance control. J Neurophysiol, 2014.
12. Hazime FA, Allard P, Ide MR, Siqueira CM, Amorim CF, Tanaka C. Postural control under visual and proprioceptive perturbations during double and single limb stances: Insights for balance training. J Bodyw Mov Ther 16: 224–229, 2012.
13. Hertel J. Functional anatomy, pathomechanics, and pathophysiology of lateral ankle instability. J Athl Train 37: 364–375, 2002.
14. Hertel J. Sensorimotor deficits with ankle sprains and chronic ankle instability. Clin Sports Med 27: 353–370, vii, 2008.
15. Hrysomallis C. Balance ability and athletic performance. Sports Med 41: 221–232, 2011.
16. Hutt K, Redding E. The effect of an eyes-closed dance-specific training program on dynamic balance in elite pre-professional ballet dancers: A randomized controlled pilot study. J Dance Med Sci 18: 3–11, 2014.
17. Jeka J, Allison L, Saffer M, Zhang Y, Carver S, Kiemel T. Sensory reweighting with translational visual stimuli in young and elderly adults: The role of state-dependent noise. Exp Brain Res 174: 517–527, 2006.
18. Jeka J, Oie KS, Kiemel T. Multisensory information for human postural control: Integrating touch and vision. Exp Brain Res 134: 107–125, 2000.
19. Jorgensen MG, Rathleff MS, Laessoe U, Caserotti P, Nielsen OBF, Aagaard P. Time-of-day influences postural balance in older adults. Gait Posture 35: 653–657, 2012.
20. Kirchner M, Schubert P, Getrost T, Haas CT. Effect of altered surfaces on postural sway characteristics in elderly subjects. Hum Mov Sci, 2013.
21. Kotecha A, Chopra R, Fahy RTA, Rubin GS. Dual tasking and balance in those with central and peripheral vision loss. Invest Ophthalmol Vis Sci 54: 5408–5415, 2013.
22. Lambert S, Sigrist A, Delaspre O, Pelizzone M, Guyot JP. Measurement of dynamic visual acuity in patients with vestibular areflexia. Acta Otolaryngol 130: 820–823, 2010.
23. Laudner KG, Koschnitzky MM. Ankle muscle activation when using the Both Sides Utilized (BOSU) balance trainer. J Strength Cond Res 24: 218–222, 2010.
24. Martínez-Amat A, Hita-Contreras F, Lomas-Vega R, Caballero-Martínez I, Alvarez PJ, Martínez-López E. Effects of 12-week proprioception training program on postural stability, gait, and balance in older adults: A controlled clinical trial. J Strength Cond Res 27: 2180–2188, 2013.
25. Nagy E, Toth K, Janositz G, Kovacs G, Feher-Kiss A, Angyan L, et al.. Postural control in athletes participating in an ironman triathlon. Eur J Appl Physiol 92: 407–413, 2004.
26. Nashner LM, Peters JF. Dynamic posturography in the diagnosis and management of dizziness and balance disorders. Neurol Clin 8: 331–349, 1990.
27. O'Driscoll J, Delahunt E. Neuromuscular training to enhance sensorimotor and functional deficits in subjects with chronic ankle instability: A systematic review and best evidence synthesis. Sports Med Arthrosc Rehabil Ther Technol 19, 2011.
28. Paillard T, Noé F. Effect of expertise and visual contribution on postural control in soccer. Scand J Med Sci Sports 16: 345–348, 2006.
29. Patel M, Fransson PA, Johansson R, Magnusson M. Foam posturography: Standing on foam is not equivalent to standing with decreased rapidly adapting mechanoreceptive sensation. Exp Brain Res 208: 519–527, 2011.
30. Perrin P, Deviterne D, Hugel F, Perrot C. Judo, better than dance, develops sensorimotor adaptabilities involved in balance control. Gait Posture 15: 187–194, 2002.
31. Peterka RJ. Sensorimotor integration in human postural control. J Neurophysiol 88: 1097–1118, 2002.
32. Postle K, Pak D, Smith TO. Effectiveness of proprioceptive exercises for ankle ligament injury in adults: A systematic literature and meta-analysis. Man Ther 17: 285–291, 2012.
33. Rith-Najarian SJ, Stolusky T, Gohdes DM. Identifying diabetic patients at high risk for lower-extremity amputation in a primary health care setting. A prospective evaluation of simple screening criteria. Diabetes Care 15: 1386–1389, 1992.
34. Romero-Franco N, Martínez-Amat A, Hita-Contreras F, Martínez-López EJ. Short-term effects of a proprioceptive training session with unstable platforms on the monopodal stabilometry of athletes. J Phys Ther Sci 26: 45–51, 2014.
35. Romero-Franco N, Martínez-López E, Lomas-Vega R, Hita-Contreras F, Martínez-Amat A. Effects of proprioceptive training program on core stability and center of gravity control in sprinters. J Strength Cond Res 26: 2071–2077, 2012.
36. Schiftan GS, Ross LA, Hahne AJ. The effectiveness of proprioceptive training in preventing ankle sprains in sporting populations: A systematic review and meta-analysis. J Sci Med Sport, 2014.
37. Shumway-Cook A, Horak FB. Assessing the influence of sensory interaction of balance. Suggestion from the field. Phys Ther 66: 1548–1550, 1986.
38. Soames RW, Atha J. The spectral characteristics of postural sway behaviour. Eur J Appl Physiol 49: 169–177, 1982.
39. Stanek JM, Meyer J, Lynall R. Single-limb-balance difficulty on 4 commonly used rehabilitation devices. J Sport Rehabil 22: 288–295, 2013.
40. Tomomitsu MSV, Alonso AC, Morimoto E, Bobbio TG, Greve JMD. Static and dynamic postural control in low-vision and normal-vision adults. Clinics (Sao Paulo) 68: 517–521, 2013.
41. Tse YYF, Petrofsky JS, Berk L, Daher N, Lohman E, Laymon MS, et al.. Postural sway and rhythmic electroencephalography analysis of cortical activation during eight balance training tasks. Med Sci Monit 19: 175–186, 2013.
42. Williams DR. Aliasing in human foveal vision. Vision Res 25: 195–205, 1985.
43. Winter DA. Biomechanics and Motor Control of Human Movement (4th ed.). Hoboken, NJ: Wiley, 2009.
44. Wu G, Chiang JH. The significance of somatosensory stimulations to the human foot in the control of postural reflexes. Exp Brain Res 114: 163–169, 1997.
45. Yaggie JA, Campbell BM. Effects of balance training on selected skills. J Strength Cond Res 20: 422–428, 2006.