Motor Control, 2016, 20, 21 -32 http://dx.doi.org/10.1123/mc.2014-0046 © 2016 Human Kinetics, Inc.
ORIGINAL RESEARCH
Sensory Interactions for Head and Trunk Control in Space in Young and Older Adults During Normal and Narrow-Base Walking Fang Zhang and Nandini Deshpande Queen’s University Fifteen young (20–30 years old) and 15 older (>65 years old) healthy participants were recruited to investigate age-related differences in head and trunk control under suboptimal vestibular conditions (galvanic vestibular stimulation, or GVS) and vision conditions during normal and narrow-based walking. Head-roll velocity decreased in the blurred-vision condition and marginally increased with GVS in older but not in young participants. Head pitch increased, whereas head-roll velocity decreased in narrow-base walking. Trunk pitch, trunk-pitch velocity, and gait speed increased with GVS, whereas trunk-pitch velocity and gait speed decreased in narrow-base walking. Marginally increased head-roll velocity in the older participants possibly suggests decreased integrative ability of the central nervous system in elderly people. The changes in head control during narrowbase walking may be an attempt to simplify the interpretation of the vestibular signal and increase otolith sensitivity. The complexity of controlling the trunk in the mediolateral direction was suggested by different strategies used for trunk control in different conditions. Keywords: aging, vestibular, vision, head control, trunk control
The precise control of the angular velocity of head and the trunk segments during dynamic tasks is critical for normal postural control (Lin et al., 2014; Shaw et al., 2012). Faster movements of the head make the vestibulo-ocular reflex less robust for foveating visual images (Pulaski, Zee, & Robinson, 1981), resulting in a less stable platform for the vision. In addition, faster head movements may increase ambiguities in the otolithic signal and difficulty in interpretation of vestibular information (Pozzo, Berthoz, & Lefort, 1990). Finally, stability of the head in space is also critical because the head position is used by the central nervous system (CNS) for mapping overall postural control (Massion, 1998). The faster movement of the trunk, which bears the largest body mass, may bring about greater momentum and The authors are with the School of Rehabilitation Therapy, Queen’s University, Kingston, Ontario, Canada. Address author correspondence to Nandini Deshpande at [email protected]. 21
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increase the challenge on postural control mechanisms (Granata & England, 2006). In addition, faster movements may limit the allowable time for neuromuscular corrections in case of instability experienced during walking or even falling (Granata & England, 2006). Overall, high velocity of both head and trunk movements may jeopardize precision in postural control and, therefore, stability during dynamic tasks. Consequently, it is not surprising that higher velocity movements of the head or trunk are associated with higher likelihood of falling (Bourke & Lyons, 2008). Therefore, it is crucial to understand the mechanisms underlying the control of head and trunk velocity and the possible age-related differences in these mechanisms. The vestibular system detects head acceleration and allows the deciphering of information on head velocity and position in space, and it controls head and trunk movement through the vestibulo-cervical reflex and vestibulo-spinal reflex, respectively (Bent, Inglis, & McFadyen, 2004; Honegger, Hubertus, & Allum, 2013). The vision provides the CNS with a vertical reference with respect to surrounding environment and has been shown to influence head-roll velocity (Cromwell, Newton, & Forrest, 2002) and trunk angular displacement during walking (Deshpande & Patla, 2007). Previous studies (Deshpande & Patla, 2007; Darlington et al., 2000) have focused primarily on the role of the vestibular system and its interaction with vision in the control of head and/or trunk position in space. However, how the sensory systems collectively contribute to the control of head and trunk velocity and whether aging process changes these interactions have not been examined. The first objective of this study was to understand whether older persons can reduce the weighting of discordant vestibular input and use available visual information to compensate for vestibular disturbance in the control of head and trunk angular velocity during a dynamic task such as walking. Postural control in the mediolateral (M-L) direction, in particular, is closely associated with fall-related fracture in older adults (Hilliard et al., 2008). With increasing age, postural control in the M-L direction may deteriorate faster and earlier compared with that in the anteroposterior (A-P) direction (Melzer, Benjuya, & Kaplanski, 2004; Choy, Brauer, & Nitz, 2003). To assess the ability to control M-L postural stability, researchers can increase the challenge by asking the individuals to walk on a narrow path that poses M-L constraints to foot placement, commonly referred to as narrowbase walking (Schrager et al., 2008). Compared with young persons, older adults demonstrate an overall higher peak velocity and displacement of the body center of mass in the M-L direction during narrow-base walking (Schrager et al., 2008). However, head or trunk control in space under these constraints has not been extensively examined. Moreover, it is known that both vision and vestibular input play an important role in postural control in the M-L direction (Bent, McFadyen, & Inglis, 2002), and the weighting of the vestibular system is up-regulated when the challenge to postural control is increased (Bent et al., 2002). As a result, the second objective of this study was to compare vestibular-visual input interactions between young and older healthy participants for head and trunk control in narrow-base walking condition. We hypothesized that compared with young persons, older participants would exhibit deteriorated ability to reduce the weighting of the discordant vestibular input and use the available visual information for the control of both the head and trunk in space. The narrow-base walking condition would further exaggerate such differences, as older participants’ CNS may have significant conflict in down-regulating vestibular gain when the challenge to postural control is increased. MC Vol. 20, No. 1, 2016
Head and Trunk Control During Walking 23
Method
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Participants Fifteen healthy young adults (seven women; age range = 20–30 years) and 15 healthy older adults (eight women; age range = 65–85 years) were recruited. The information of the average age, height, and weight in both the young and older group is shown in Table 1. Participants with any of the following conditions were excluded: (a) history of neuromuscular disorder, diabetes, dizziness or more than one fall in the past year, (b) unable to walk without walking aids, and (c) lower limb pain during walking (e.g., because of recent injury, peripheral vascular disease). All participants signed an informed consent approved by the Health Sciences and Affiliated Teaching Hospitals Research Ethics Board.
Procedures Walking Conditions. The participants were asked to walk straight ahead for 6 m
at their preferred pace in two conditions: unrestricted normal walking and narrowbase walking (i.e., walking between the lines of tape placed 25 cm apart). The participants wore their usual running/walking shoes and their normal corrective glasses/lenses if they wore them routinely.
Sensory Manipulations. The vestibular and visual inputs were manipulated either
individually or concurrently on randomly selected trials. Vestibular information was manipulated using bipolar galvanic vestibular stimulation (GVS; S48, Grass Medical Instruments, Quincy, MA), which creates an imbalance in vestibular information by increasing the firing rate of the vestibular nerve on the cathodal side and decreasing the firing rate of that nerve on the anodal side (Wardman, Day, & Fitzpatrick, 2003). The anode in this study was randomly placed either on the right or on the left side because no side-specific difference of trunk-roll angle or head-roll angle between the effect magnitudes has been reported previously (Deshpande & Patla, 2007). To determine threshold stimulation intensity, we asked each participant to stand with feet together, and the GVS intensity was slowly increased to the level at which the participants’ postural sway in the anodal direction was visibly perceived by the experimenter (Bent et al., 2004; Deshpande & Patla, 2007). GVS was applied at 2 times the individual’s threshold GVS intensity and was maintained throughout the walking trial (Bent et al., 2004; Deshpande & Patla, 2007). Table 1 Average Age, Height and Weight of the Young and Older Participants Parameter
Young group
Older group
Age, years
25.40 (0.92)
72.60 (1.36)
Height, cm
167.27 (2.03
165.27 (3.15)
Weight, kg
62.75 (2.94)
67.37 (3.38)
Note. Values in parentheses are standard errors. MC Vol. 20, No. 1, 2016
24 Zhang and Deshpande
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Visual input was manipulated using custom-made blurring goggles (Optometry Laboratory, University of Waterloo, Waterloo, ON, Canada) that significantly reduced visual contrast sensitivity, simulating dense cataracts (Deshpande & Patla, 2007). Walking trials were blocked according to the walking conditions, and within these blocks, trials in sensory conditions were randomized. In each combination of walking conditions and sensory manipulations, two identical trials were performed, for a total of 16 trials—two walking conditions (narrow-base walking and normal walking) × two vision conditions (blurring goggles and normal vision) × two GVS conditions (GVS and no GVS) × two trials.
Setup and Protocol The experiment was performed in the Motor Performance Laboratory at the Queen’s University. Infrared-emitting diodes (IREDs) were attached to 10 anatomical landmarks for each participant: at the cranial vertex; above the left and right ears; on the left and right acromion processes; on the 7th cervical, 12th thoracic, and 2nd sacral vertebrae; and on the left and right lateral malleoli. The IREDs were tracked by two OPTOTRAK camera banks (Northern Digital, Waterloo, ON, Canada), and data were captured at a sampling rate of 100 Hz. For the trials in which GVS was used, the participants were asked to start their walking 2 s after the experimenter initiated GVS to eliminate initial instability induced by GVS (Deshpande & Patla, 2007).
Outcome Measures OPTOTRAK data were filtered using low-pass filter (Butterworth filter) at 5 Hz, and the filtered data were used to calculate all the variables included in this study. Because no difference was observed in results of paired t tests between the two identical trials in all the sensory and walking conditions, all the variables were averaged over the two trials (data not shown). Segmental Responses. The average head-pitch angle and pitch angular velocity
and the average head-roll angle and roll angular velocity were included to represent head control in space. The position and velocity were computed from the instantaneous spatial coordinate data of the IREDs at the cranial vertex and the seventh cervical vertebra. The averages were calculated as the root-meansquare values from across the trial. Likewise, the average trunk-pitch angle and angular velocity and the average trunk roll and angular velocity represented trunk control in space. These four variables were calculated as the root-mean-squares of values from across the trial using the spatial coordinates of the IREDs on the seventh cervical and second sacral vertebrae.
Global Locomotor Responses. The average gait speed was calculated from the displacement of the second sacral vertebra IRED. To exclude acceleration and deceleration phase during the walking process, we calculated the average gait speed for the middle 2 m (between 2 and 4 m) of the walking path. Average step length and step width were calculated from all the steps successfully captured by the OPTOTRAK. The data from the IREDs on the left and right lateral malleoli were used for calculation of the two variables. MC Vol. 20, No. 1, 2016
Head and Trunk Control During Walking 25
Statistical Analysis
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Nonnormally distributed data were square-root transformed. A separate four-way repeated measures analysis of variance (ANOVA; Age Group × Walking Condition × GVS × Vision) was used for each outcome measure to examine the effect of sensory manipulation and walking condition, and to compare the possible difference between young and older participants. IBM SPSS Statistics (Version 21.0 for Windows) was used for data analysis. Statistical significance was set at p = .05. Further analysis was performed if a significant interaction effect was found. For example, if there was an interaction between age group and GVS, further analysis (ANOVA) was performed in the young and older group separately to understand the impact of GVS in each age group.
Results Segmental Responses The data of one young participant were corrupted because of technical difficulty and were excluded. All the outcome measures except gait speed and average steplength and step-width data were square root transformed. Average head roll was not influenced by any condition. Average head-roll angular velocity decreased in both the narrow-base walking condition, F(1, 27) = 8.55, p = .007, observed power = 0.81 (6.5%) (Figure 1) and the blurred vision condition, F(1, 27) = 7.98, p = .009, observed power = 0.78 (4.0%). There was also marginal interaction between age group and GVS, F(1, 27) = 3.96, p = .06. Further analysis showed that in young participants, head-roll velocity was not affected by GVS, F(1, 14) = 1.09, p = .32, observed power = 0.16; in older persons, however, head-roll velocity was marginally increased by GVS, F(1, 14) = 3.89, p = .07, observed power = 0.45 (3.1%) (Figure 1).
Figure 1 — The graph displays average head-roll velocity (degree/s) ± SE in young (a) and older (b) participants. ** denotes a significant (p < .05) decrease in average head-roll velocity in the narrow-base walking condition in both young and older participants and * indicates a marginally (p < .1) increased average head-roll velocity with GVS in older participants. MC Vol. 20, No. 1, 2016
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Average head pitch was significantly increased in the narrow-base walking condition compared with normal-based walking in both age groups, F(1, 27) = 21.72, p < .001, observed power = 0.99 (22.0%) (Figure 2). Average head-pitch velocity was not affected by GVS, F(1, 27) = 1.36, p = .26, observed power = 0.20, narrow-base walking, F(1, 27) = 0.48, p = .49, observed power = 0.10, or blurred vision, F(1, 27) = 0.42, p = .52, observed power = 0.10. Trunk-roll angle was not affected by GVS, F(1, 27) = 2.51, p = .12, observed power = 0.14, narrow-base walking, F(1, 27) = 0.83, p = .37, observed power = 0.14, or blurred vision, F(1, 27) = 0.34, p = .57, observed power = 0.09 (Figure 3). Trunk-roll velocity was also not affected by GVS, F(1, 27) = 0.71, p = .41, observed power = 0.13, narrow-base walking, F(1, 27) = 0.41, p = .53, observed power = 0.10, or blurred vision, F(1, 27) = 0.08, p = .79, observed power = 0.06 (Figure 4). Average trunk pitch was increased by GVS, F(1, 27) = 6.29, p = .02, observed power = 0.69 (4.8%). Average trunk-pitch velocity decreased in the narrow-base walking condition, F(1, 27) = 13.38, p = .001, observed power = 0.92 (3.3%), but
Figure 2 — The graph displays average head-pitch angle (degree) ± SE in young (a) and older (b) participants. ** denotes a significant (p < .05) increase in the narrow-base walking condition in both young and older participants.
Figure 3 — The graph displays average trunk-roll angle (degree) ± SE in young (a) and older (b) participants. No significant result was found.
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Head and Trunk Control During Walking 27
Figure 4 — The graph displays average trunk-roll velocity (degree/s) ± SE in young (a) and older (b) participants. No significant result was found.
was increased by GVS, F(1, 27) = 12.99, p = .001, observed power = 0.94 (4.6%) (Figure 5).
Global Locomotor Responses Gait speed significantly decreased in the narrow-base walking condition, F(1, 27) = 8.00, p = .009, observed power = 0.79; older persons: 6.6%; young persons: 2.7%. Gait speed was significantly increased by GVS, F(1, 27) = 16.66, p < .001, observed power = 0.98, in both young (4.7%) and older participants (4.8%). However, there was no significant difference between young and older persons, F(1, 27) = 1.27, p = .27, observed power = 0.19. Average step length increased with GVS, F(1, 25) = 29.35, p < .001, and observed power = 0.98 (2.3%), but decreased in the narrow-base walking condition, F(1, 25) = 20.38, p < .001, observed power = 0.98 (5.1%). Average step width increased with GVS, F(1, 25) = 13.22, p = .001, observed power = 0.94 (4.4%), but decreased in narrow-base walking condition, F(1, 25) = 18.71, p < .001, observed power = 0.98 (12.9%). (The value for degrees of freedom was 25 rather than 27 because of missing data from the IREDs on the left and right lateral malleoli in two participants.)
Discussion This study investigated age-related differences in the control of the head and trunk in space during normal and narrow-base walking. Overall, minimal age-related differences were observed, as demonstrated by marginal differences in head control. This was reflected in marginal increase in head-roll velocity in older adults but not in young individuals when vestibular information was discordant. The M-L stability of the trunk was maintained in young as well as older participants despite task and sensory constraints. Healthy older adults exhibited marginally reduced ability to decrease the weighting of the discordant vestibular input and use vision to control head stability MC Vol. 20, No. 1, 2016
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28 Zhang and Deshpande
Figure 5 — The graph displays average trunk-pitch velocity (degree/s) ± SE in young (a) and older (b) participants. ** denotes a significant (p < .05) decrease in the narrow-base walking condition and increase in GVS condition (p < .05) in both young and older participants.
in space when the vestibular input was manipulated using GVS. Such marginal age-related difference in the CNS integrative ability might be due to age-related changes in the CNS, especially the age-related atrophy of the posterior multimodal sensory area in the association cortex (Salat et al., 2004), and to age-related neuronal loss in the sensory nuclei in the brainstem (Tang, Lopez, & Baloh, 2002), both of which are responsible for integrating different sensory modalities and directing motor behavior (Tang et al., 2002; Saper, Iversen, & Frackowiak, 2000). Available evidence suggests that the increased weighting of vestibular afferents may be regarded as a compensation for age-related deterioration in the peripheral vestibular organs (Lopez, Honrubia, & Baloh, 1997) as well as the aging of the vestibular nuclei in the brain stem (Tang et al., 2002). Alternatively, it is also possible that the increased vestibular weighting could result from the aging of other sensory systems, such as somatosensory input (Horak & Hlavacka, 2001). However, there is no robust evidence identifying underlying neural substrates associated with age-related changes in sensory reweighting processes. Head-roll velocity in both age groups decreased in both the blurred-vision condition and the narrow-base walking condition. In addition, the head pitch increased in narrow-base walking condition. The decreased head-roll velocity in the blurred-vision condition may demonstrate an adaptive strategy to reduce image motion under this suboptimal vision condition. It is possible that when vision was blurred, the vestibular compensation of the torsional eye movements through the vestibulo-ocular reflex was not sufficient to maintain image clarity, so that decreased head-roll velocity was needed to adapt to the suboptimal vision conditions (Herdman, 1998). The decreased head-roll velocity and increased head-pitch angle were observed in the narrow-base walking. Both of the responses may be associated with the necessity of reliance on vestibular system for postural control in the difficult task. As mentioned above, decreasing head movement velocity may simplify the interpretation of vestibular information (Pozzo et al., 1990). On the other hand, a simple explanation for increased head-pitch angle in the narrow-base MC Vol. 20, No. 1, 2016
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Head and Trunk Control During Walking 29
walking condition could be the need to visually ensure that the foot positioning was within the 25-cm path delineated by the tapes. However, it is also possible that the increase in the head pitch was the strategy used to increase the sensitivity of the otoliths perhaps for better detecting linear movement of the head or providing a more accurate vertical reference when M-L challenge is imposed. When head pitch increases, the utricle is closer to the horizontal plane so that the change in the shear force acting on the otoconial membrane is maximal, increasing its sensitivity (Pozzo et al., 1990). Further, increased head-pitch angle and decreased head-roll velocity in narrow-base walking may not stem from decreased gait speed in the same condition, as adjusting for gait speed did not change the significant impact of the narrow-base walking condition. Nor was gait speed a significant covariate for head pitch angle (p = .60) or head-roll velocity (p = .26). The average trunk-pitch displacement and trunk-pitch velocity increased in the GVS condition, and trunk-pitch velocity decreased in the narrow-base walking condition. However, these changes in trunk control may be the result of the similar changes in gait speed in the respective conditions. The impact of GVS on the head and trunk is mainly in the M-L direction but not the A-P direction (Wardman et al., 2003). Therefore, increased average trunk-pitch angle and trunk-pitch velocity with GVS may not reflect a direct impact of GVS on trunk control. In particular, increased trunk-pitch angle could be a strategy to bring body’s center of mass slightly forward to facilitate the forward momentum to counteract GVS-induced M-L perturbation (Orendurff et al., 2004). To support this inference, we analyzed the impact of GVS and narrow-base walking on trunk-pitch angle and trunk-pitch velocity, adjusting for gait speed. Despite the result that gait speed was a significant covariate for trunk pitch velocity (p = .003), the significant impact of GVS and the narrow-base walking condition did not change. In this study, trunk-roll angle and velocity did not increase in the GVS condition or in the narrow-base walking condition. It was observed that GVS-induced increased gait speed was accompanied by an increase in step width. It is possible that a higher momentum in the A-P direction together with wider base of support allowed the maintenance of trunk stability in the M-L direction, and thus no GVSinduced impact on trunk roll velocity or angle was found. Conversely, although step width significantly decreased in the narrow-base walking condition because of task constraints, changes in trunk-roll angle or velocity were not observed. The decrease in gait speed in the narrow-base walking condition possibly allowed for longer double support phase to increase the stability in response to the challenge in the M-L direction. Thus, overall, no significant effect of the narrow-base walking condition on trunk M-L stability was found. The results suggest that trunk control in the M-L direction is more complex than A-P control. Even with intact lower limb somatosensory input, vision had a significant impact on head control, and GVS marginally increased head-roll velocity in older people, whereas GVS increased neither trunk-roll velocity nor angular displacement in M-L direction. The subtle differences between head and trunk control found in this study support differential segmental control (Kavanagh, Morrison, & Barrett, 2005). It is suggested that head control may be dependent more on reflexes directly related to the visual and/or vestibular system, such as the optokinetic cervical reflex and/or the vestibulocervical reflex (Dan et al., 2000), showing the importance of the “top-down” model (Massion, 1998). Trunk control may rely more on intact MC Vol. 20, No. 1, 2016
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lower limb sensation (Deshpande & Zhang, 2014), suggesting the importance of the “bottom-up” model (Massion, 1998). No significant difference was found in gait speed between young and older participants. It is probably because a majority of the older participants (12 of 15) included in this study were young old (i.e., 75 years old or younger), and all the older participants were very healthy and active. All of them could walk independently and none of them had any of the conditions mentioned in the exclusion criteria (e.g., neuromuscular disorder). Further, 11 of 15 older participants regularly performed physical exercises for at least 5 hr per week, and the activities ranged from jogging to cycling. The findings in this study were to some extent different than predicted by the hypothesis. Compared with young persons, older participants exhibited only marginally deteriorated ability to reduce the weighting of the discordant vestibular input for controlling head stability but not trunk stability. There was no significant difference between young and older participants in terms of the ability to keep head and trunk stability during narrow-base walking even with sensory manipulations. It is possible that applying GVS intensity at 2 times the threshold may not be enough to evoke differential responses when people were walking at a self-selected speed with intact lower limb somatosensory input and some visual information available. Second, the constraint of 25 cm for foot placement in the narrow-base walking condition may not be a big M-L challenge for healthy older participants. Normalization of the path width to body morphology (e.g., normalization to 50% of the distance between the participant’s anterior superior iliac spines) could be an alternative. However, women are typically shorter and have wider hips than men (Conley et al., 2007). Therefore, normalized path width may have different challenges to men and women. Further, normalization of the path width to body height may suffer from the similar limitation. It is possible that normalization to normal step width could overcome such shortcoming. However, in terms of future clinical use, a standard protocol is easier to apply. This issue requires further research to determine the best protocol. In future studies, the path width could be further reduced or an external M-L perturbation can be used, which may show more subtle age-related changes.
Conclusion The results have shown that reliance on vestibular information to control head velocity in the M-L direction is marginally higher in older people than in young people. Results have also shown vision’s control over head stability regardless of age. In addition, the complexity of trunk control in the M-L direction in different conditions was observed. The findings may enhance our understanding of the importance of the vestibular input and sensory interaction in controlling head and trunk stability during walking, which may lay a foundation for the development of strategies to improve postural control and reduce falls. Acknowledgments This work was supported by Senate Advisory Research Committee, Queen’s University research funding to Dr. Nandini Deshpande. We thank Dr. Alison Novak, Mika Yoshikawa and Patricia Hewston for assistance with data collection. MC Vol. 20, No. 1, 2016
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Melzer, I., Benjuya, N., & Kaplanski, J. (2004). Postural stability in the elderly: a comparison between fallers and non-fallers. Age and Ageing, 33, 602–607. PubMed doi:10.1093/ ageing/afh218 Choy, N.L., Brauer, S., & Nitz, J. (2003). Changes in postural stability in women aged 20 to 80 years. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 58, M525–M530. PubMed doi:10.1093/gerona/58.6.M525 Orendurff, M.S., Segal, A.D., Klute, G.K., Berge, J.S., Rohr, E.S., & Kadel, N.J. (2004). The effect of walking speed on center of mass displacement. Journal of Rehabilitation Research and Development, 41, 829–834. PubMed doi:10.1682/JRRD.2003.10.0150 Pozzo, T., Berthoz, A., & Lefort, L. (1990). Head stabilization during various locomotor tasks in humans. Experimental Brain Research, 82, 97–106. PubMed doi:10.1007/ BF00230842 Pulaski, P.D., Zee, D.S., & Robinson, D.A. (1981). The behavior of the vestibulo-ocular reflex at high velocities of head rotation. Brain Research, 222, 159–165. PubMed doi:10.1016/0006-8993(81)90952-5 Salat, D.H., Buckner, R.L., Snyder, A.Z., Greve, D.N., Desikan, R.S.R., Busa, E., . . . Fischl, B. (2004). Thinning of the cerebral cortex in aging. Cerebral Cortex, 14, 721–730. PubMed doi:10.1093/cercor/bhh032 Saper, C.B., Iversen, S., & Frackowiak, R. (2000). Integration of sensory and motor function: The association areas of the cerebral cortex and the cognitive capabilities of the brain. In E.R. Kandel, J.H. Schwartz, & T.M. Jessell (Eds.), Principles of neural science (4th ed., pp. 349–380). New York, NY: McGraw-Hill. Schrager, M.A., Kelly, V.E., Price, R., Ferrucci, L., & Shumway-Cook, A. (2008). The effects of age on medio-lateral stability during normal and narrow base walking. Gait & Posture, 28, 466–471. PubMed doi:10.1016/j.gaitpost.2008.02.009 Shaw, J.A., Stefanyk, L.E., Frank, J.S., Jog, M.S., & Adkin, A.L. (2012). Effects of age and pathology on stance modifications in response to increased postural threat. Gait & Posture, 35, 658–661. PubMed doi:10.1016/j.gaitpost.2011.12.020 Tang, Y., Lopez, I., & Baloh, R.W. (2002). Age-related change of the neuronal number in the human medial vestibular nucleus: A stereological investigation. Journal of Vestibular Research, 1, 357–363. PubMed Wardman, D.L., Day, B.L., & Fitzpatrick, R.C. (2003). Position and velocity responses to galvanic vestibular stimulation in human subjects during standing. The Journal of Physiology, 547, 293–299. PubMed doi:10.1113/jphysiol.2002.030767
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ORIGINAL RESEARCH
Sensory Interactions for Head and Trunk Control in Space in Young and Older Adults During Normal and Narrow-Base Walking Fang Zhang and Nandini Deshpande Queen’s University Fifteen young (20–30 years old) and 15 older (>65 years old) healthy participants were recruited to investigate age-related differences in head and trunk control under suboptimal vestibular conditions (galvanic vestibular stimulation, or GVS) and vision conditions during normal and narrow-based walking. Head-roll velocity decreased in the blurred-vision condition and marginally increased with GVS in older but not in young participants. Head pitch increased, whereas head-roll velocity decreased in narrow-base walking. Trunk pitch, trunk-pitch velocity, and gait speed increased with GVS, whereas trunk-pitch velocity and gait speed decreased in narrow-base walking. Marginally increased head-roll velocity in the older participants possibly suggests decreased integrative ability of the central nervous system in elderly people. The changes in head control during narrowbase walking may be an attempt to simplify the interpretation of the vestibular signal and increase otolith sensitivity. The complexity of controlling the trunk in the mediolateral direction was suggested by different strategies used for trunk control in different conditions. Keywords: aging, vestibular, vision, head control, trunk control
The precise control of the angular velocity of head and the trunk segments during dynamic tasks is critical for normal postural control (Lin et al., 2014; Shaw et al., 2012). Faster movements of the head make the vestibulo-ocular reflex less robust for foveating visual images (Pulaski, Zee, & Robinson, 1981), resulting in a less stable platform for the vision. In addition, faster head movements may increase ambiguities in the otolithic signal and difficulty in interpretation of vestibular information (Pozzo, Berthoz, & Lefort, 1990). Finally, stability of the head in space is also critical because the head position is used by the central nervous system (CNS) for mapping overall postural control (Massion, 1998). The faster movement of the trunk, which bears the largest body mass, may bring about greater momentum and The authors are with the School of Rehabilitation Therapy, Queen’s University, Kingston, Ontario, Canada. Address author correspondence to Nandini Deshpande at [email protected]. 21
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increase the challenge on postural control mechanisms (Granata & England, 2006). In addition, faster movements may limit the allowable time for neuromuscular corrections in case of instability experienced during walking or even falling (Granata & England, 2006). Overall, high velocity of both head and trunk movements may jeopardize precision in postural control and, therefore, stability during dynamic tasks. Consequently, it is not surprising that higher velocity movements of the head or trunk are associated with higher likelihood of falling (Bourke & Lyons, 2008). Therefore, it is crucial to understand the mechanisms underlying the control of head and trunk velocity and the possible age-related differences in these mechanisms. The vestibular system detects head acceleration and allows the deciphering of information on head velocity and position in space, and it controls head and trunk movement through the vestibulo-cervical reflex and vestibulo-spinal reflex, respectively (Bent, Inglis, & McFadyen, 2004; Honegger, Hubertus, & Allum, 2013). The vision provides the CNS with a vertical reference with respect to surrounding environment and has been shown to influence head-roll velocity (Cromwell, Newton, & Forrest, 2002) and trunk angular displacement during walking (Deshpande & Patla, 2007). Previous studies (Deshpande & Patla, 2007; Darlington et al., 2000) have focused primarily on the role of the vestibular system and its interaction with vision in the control of head and/or trunk position in space. However, how the sensory systems collectively contribute to the control of head and trunk velocity and whether aging process changes these interactions have not been examined. The first objective of this study was to understand whether older persons can reduce the weighting of discordant vestibular input and use available visual information to compensate for vestibular disturbance in the control of head and trunk angular velocity during a dynamic task such as walking. Postural control in the mediolateral (M-L) direction, in particular, is closely associated with fall-related fracture in older adults (Hilliard et al., 2008). With increasing age, postural control in the M-L direction may deteriorate faster and earlier compared with that in the anteroposterior (A-P) direction (Melzer, Benjuya, & Kaplanski, 2004; Choy, Brauer, & Nitz, 2003). To assess the ability to control M-L postural stability, researchers can increase the challenge by asking the individuals to walk on a narrow path that poses M-L constraints to foot placement, commonly referred to as narrowbase walking (Schrager et al., 2008). Compared with young persons, older adults demonstrate an overall higher peak velocity and displacement of the body center of mass in the M-L direction during narrow-base walking (Schrager et al., 2008). However, head or trunk control in space under these constraints has not been extensively examined. Moreover, it is known that both vision and vestibular input play an important role in postural control in the M-L direction (Bent, McFadyen, & Inglis, 2002), and the weighting of the vestibular system is up-regulated when the challenge to postural control is increased (Bent et al., 2002). As a result, the second objective of this study was to compare vestibular-visual input interactions between young and older healthy participants for head and trunk control in narrow-base walking condition. We hypothesized that compared with young persons, older participants would exhibit deteriorated ability to reduce the weighting of the discordant vestibular input and use the available visual information for the control of both the head and trunk in space. The narrow-base walking condition would further exaggerate such differences, as older participants’ CNS may have significant conflict in down-regulating vestibular gain when the challenge to postural control is increased. MC Vol. 20, No. 1, 2016
Head and Trunk Control During Walking 23
Method
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Participants Fifteen healthy young adults (seven women; age range = 20–30 years) and 15 healthy older adults (eight women; age range = 65–85 years) were recruited. The information of the average age, height, and weight in both the young and older group is shown in Table 1. Participants with any of the following conditions were excluded: (a) history of neuromuscular disorder, diabetes, dizziness or more than one fall in the past year, (b) unable to walk without walking aids, and (c) lower limb pain during walking (e.g., because of recent injury, peripheral vascular disease). All participants signed an informed consent approved by the Health Sciences and Affiliated Teaching Hospitals Research Ethics Board.
Procedures Walking Conditions. The participants were asked to walk straight ahead for 6 m
at their preferred pace in two conditions: unrestricted normal walking and narrowbase walking (i.e., walking between the lines of tape placed 25 cm apart). The participants wore their usual running/walking shoes and their normal corrective glasses/lenses if they wore them routinely.
Sensory Manipulations. The vestibular and visual inputs were manipulated either
individually or concurrently on randomly selected trials. Vestibular information was manipulated using bipolar galvanic vestibular stimulation (GVS; S48, Grass Medical Instruments, Quincy, MA), which creates an imbalance in vestibular information by increasing the firing rate of the vestibular nerve on the cathodal side and decreasing the firing rate of that nerve on the anodal side (Wardman, Day, & Fitzpatrick, 2003). The anode in this study was randomly placed either on the right or on the left side because no side-specific difference of trunk-roll angle or head-roll angle between the effect magnitudes has been reported previously (Deshpande & Patla, 2007). To determine threshold stimulation intensity, we asked each participant to stand with feet together, and the GVS intensity was slowly increased to the level at which the participants’ postural sway in the anodal direction was visibly perceived by the experimenter (Bent et al., 2004; Deshpande & Patla, 2007). GVS was applied at 2 times the individual’s threshold GVS intensity and was maintained throughout the walking trial (Bent et al., 2004; Deshpande & Patla, 2007). Table 1 Average Age, Height and Weight of the Young and Older Participants Parameter
Young group
Older group
Age, years
25.40 (0.92)
72.60 (1.36)
Height, cm
167.27 (2.03
165.27 (3.15)
Weight, kg
62.75 (2.94)
67.37 (3.38)
Note. Values in parentheses are standard errors. MC Vol. 20, No. 1, 2016
24 Zhang and Deshpande
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Visual input was manipulated using custom-made blurring goggles (Optometry Laboratory, University of Waterloo, Waterloo, ON, Canada) that significantly reduced visual contrast sensitivity, simulating dense cataracts (Deshpande & Patla, 2007). Walking trials were blocked according to the walking conditions, and within these blocks, trials in sensory conditions were randomized. In each combination of walking conditions and sensory manipulations, two identical trials were performed, for a total of 16 trials—two walking conditions (narrow-base walking and normal walking) × two vision conditions (blurring goggles and normal vision) × two GVS conditions (GVS and no GVS) × two trials.
Setup and Protocol The experiment was performed in the Motor Performance Laboratory at the Queen’s University. Infrared-emitting diodes (IREDs) were attached to 10 anatomical landmarks for each participant: at the cranial vertex; above the left and right ears; on the left and right acromion processes; on the 7th cervical, 12th thoracic, and 2nd sacral vertebrae; and on the left and right lateral malleoli. The IREDs were tracked by two OPTOTRAK camera banks (Northern Digital, Waterloo, ON, Canada), and data were captured at a sampling rate of 100 Hz. For the trials in which GVS was used, the participants were asked to start their walking 2 s after the experimenter initiated GVS to eliminate initial instability induced by GVS (Deshpande & Patla, 2007).
Outcome Measures OPTOTRAK data were filtered using low-pass filter (Butterworth filter) at 5 Hz, and the filtered data were used to calculate all the variables included in this study. Because no difference was observed in results of paired t tests between the two identical trials in all the sensory and walking conditions, all the variables were averaged over the two trials (data not shown). Segmental Responses. The average head-pitch angle and pitch angular velocity
and the average head-roll angle and roll angular velocity were included to represent head control in space. The position and velocity were computed from the instantaneous spatial coordinate data of the IREDs at the cranial vertex and the seventh cervical vertebra. The averages were calculated as the root-meansquare values from across the trial. Likewise, the average trunk-pitch angle and angular velocity and the average trunk roll and angular velocity represented trunk control in space. These four variables were calculated as the root-mean-squares of values from across the trial using the spatial coordinates of the IREDs on the seventh cervical and second sacral vertebrae.
Global Locomotor Responses. The average gait speed was calculated from the displacement of the second sacral vertebra IRED. To exclude acceleration and deceleration phase during the walking process, we calculated the average gait speed for the middle 2 m (between 2 and 4 m) of the walking path. Average step length and step width were calculated from all the steps successfully captured by the OPTOTRAK. The data from the IREDs on the left and right lateral malleoli were used for calculation of the two variables. MC Vol. 20, No. 1, 2016
Head and Trunk Control During Walking 25
Statistical Analysis
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Nonnormally distributed data were square-root transformed. A separate four-way repeated measures analysis of variance (ANOVA; Age Group × Walking Condition × GVS × Vision) was used for each outcome measure to examine the effect of sensory manipulation and walking condition, and to compare the possible difference between young and older participants. IBM SPSS Statistics (Version 21.0 for Windows) was used for data analysis. Statistical significance was set at p = .05. Further analysis was performed if a significant interaction effect was found. For example, if there was an interaction between age group and GVS, further analysis (ANOVA) was performed in the young and older group separately to understand the impact of GVS in each age group.
Results Segmental Responses The data of one young participant were corrupted because of technical difficulty and were excluded. All the outcome measures except gait speed and average steplength and step-width data were square root transformed. Average head roll was not influenced by any condition. Average head-roll angular velocity decreased in both the narrow-base walking condition, F(1, 27) = 8.55, p = .007, observed power = 0.81 (6.5%) (Figure 1) and the blurred vision condition, F(1, 27) = 7.98, p = .009, observed power = 0.78 (4.0%). There was also marginal interaction between age group and GVS, F(1, 27) = 3.96, p = .06. Further analysis showed that in young participants, head-roll velocity was not affected by GVS, F(1, 14) = 1.09, p = .32, observed power = 0.16; in older persons, however, head-roll velocity was marginally increased by GVS, F(1, 14) = 3.89, p = .07, observed power = 0.45 (3.1%) (Figure 1).
Figure 1 — The graph displays average head-roll velocity (degree/s) ± SE in young (a) and older (b) participants. ** denotes a significant (p < .05) decrease in average head-roll velocity in the narrow-base walking condition in both young and older participants and * indicates a marginally (p < .1) increased average head-roll velocity with GVS in older participants. MC Vol. 20, No. 1, 2016
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Average head pitch was significantly increased in the narrow-base walking condition compared with normal-based walking in both age groups, F(1, 27) = 21.72, p < .001, observed power = 0.99 (22.0%) (Figure 2). Average head-pitch velocity was not affected by GVS, F(1, 27) = 1.36, p = .26, observed power = 0.20, narrow-base walking, F(1, 27) = 0.48, p = .49, observed power = 0.10, or blurred vision, F(1, 27) = 0.42, p = .52, observed power = 0.10. Trunk-roll angle was not affected by GVS, F(1, 27) = 2.51, p = .12, observed power = 0.14, narrow-base walking, F(1, 27) = 0.83, p = .37, observed power = 0.14, or blurred vision, F(1, 27) = 0.34, p = .57, observed power = 0.09 (Figure 3). Trunk-roll velocity was also not affected by GVS, F(1, 27) = 0.71, p = .41, observed power = 0.13, narrow-base walking, F(1, 27) = 0.41, p = .53, observed power = 0.10, or blurred vision, F(1, 27) = 0.08, p = .79, observed power = 0.06 (Figure 4). Average trunk pitch was increased by GVS, F(1, 27) = 6.29, p = .02, observed power = 0.69 (4.8%). Average trunk-pitch velocity decreased in the narrow-base walking condition, F(1, 27) = 13.38, p = .001, observed power = 0.92 (3.3%), but
Figure 2 — The graph displays average head-pitch angle (degree) ± SE in young (a) and older (b) participants. ** denotes a significant (p < .05) increase in the narrow-base walking condition in both young and older participants.
Figure 3 — The graph displays average trunk-roll angle (degree) ± SE in young (a) and older (b) participants. No significant result was found.
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Head and Trunk Control During Walking 27
Figure 4 — The graph displays average trunk-roll velocity (degree/s) ± SE in young (a) and older (b) participants. No significant result was found.
was increased by GVS, F(1, 27) = 12.99, p = .001, observed power = 0.94 (4.6%) (Figure 5).
Global Locomotor Responses Gait speed significantly decreased in the narrow-base walking condition, F(1, 27) = 8.00, p = .009, observed power = 0.79; older persons: 6.6%; young persons: 2.7%. Gait speed was significantly increased by GVS, F(1, 27) = 16.66, p < .001, observed power = 0.98, in both young (4.7%) and older participants (4.8%). However, there was no significant difference between young and older persons, F(1, 27) = 1.27, p = .27, observed power = 0.19. Average step length increased with GVS, F(1, 25) = 29.35, p < .001, and observed power = 0.98 (2.3%), but decreased in the narrow-base walking condition, F(1, 25) = 20.38, p < .001, observed power = 0.98 (5.1%). Average step width increased with GVS, F(1, 25) = 13.22, p = .001, observed power = 0.94 (4.4%), but decreased in narrow-base walking condition, F(1, 25) = 18.71, p < .001, observed power = 0.98 (12.9%). (The value for degrees of freedom was 25 rather than 27 because of missing data from the IREDs on the left and right lateral malleoli in two participants.)
Discussion This study investigated age-related differences in the control of the head and trunk in space during normal and narrow-base walking. Overall, minimal age-related differences were observed, as demonstrated by marginal differences in head control. This was reflected in marginal increase in head-roll velocity in older adults but not in young individuals when vestibular information was discordant. The M-L stability of the trunk was maintained in young as well as older participants despite task and sensory constraints. Healthy older adults exhibited marginally reduced ability to decrease the weighting of the discordant vestibular input and use vision to control head stability MC Vol. 20, No. 1, 2016
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28 Zhang and Deshpande
Figure 5 — The graph displays average trunk-pitch velocity (degree/s) ± SE in young (a) and older (b) participants. ** denotes a significant (p < .05) decrease in the narrow-base walking condition and increase in GVS condition (p < .05) in both young and older participants.
in space when the vestibular input was manipulated using GVS. Such marginal age-related difference in the CNS integrative ability might be due to age-related changes in the CNS, especially the age-related atrophy of the posterior multimodal sensory area in the association cortex (Salat et al., 2004), and to age-related neuronal loss in the sensory nuclei in the brainstem (Tang, Lopez, & Baloh, 2002), both of which are responsible for integrating different sensory modalities and directing motor behavior (Tang et al., 2002; Saper, Iversen, & Frackowiak, 2000). Available evidence suggests that the increased weighting of vestibular afferents may be regarded as a compensation for age-related deterioration in the peripheral vestibular organs (Lopez, Honrubia, & Baloh, 1997) as well as the aging of the vestibular nuclei in the brain stem (Tang et al., 2002). Alternatively, it is also possible that the increased vestibular weighting could result from the aging of other sensory systems, such as somatosensory input (Horak & Hlavacka, 2001). However, there is no robust evidence identifying underlying neural substrates associated with age-related changes in sensory reweighting processes. Head-roll velocity in both age groups decreased in both the blurred-vision condition and the narrow-base walking condition. In addition, the head pitch increased in narrow-base walking condition. The decreased head-roll velocity in the blurred-vision condition may demonstrate an adaptive strategy to reduce image motion under this suboptimal vision condition. It is possible that when vision was blurred, the vestibular compensation of the torsional eye movements through the vestibulo-ocular reflex was not sufficient to maintain image clarity, so that decreased head-roll velocity was needed to adapt to the suboptimal vision conditions (Herdman, 1998). The decreased head-roll velocity and increased head-pitch angle were observed in the narrow-base walking. Both of the responses may be associated with the necessity of reliance on vestibular system for postural control in the difficult task. As mentioned above, decreasing head movement velocity may simplify the interpretation of vestibular information (Pozzo et al., 1990). On the other hand, a simple explanation for increased head-pitch angle in the narrow-base MC Vol. 20, No. 1, 2016
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Head and Trunk Control During Walking 29
walking condition could be the need to visually ensure that the foot positioning was within the 25-cm path delineated by the tapes. However, it is also possible that the increase in the head pitch was the strategy used to increase the sensitivity of the otoliths perhaps for better detecting linear movement of the head or providing a more accurate vertical reference when M-L challenge is imposed. When head pitch increases, the utricle is closer to the horizontal plane so that the change in the shear force acting on the otoconial membrane is maximal, increasing its sensitivity (Pozzo et al., 1990). Further, increased head-pitch angle and decreased head-roll velocity in narrow-base walking may not stem from decreased gait speed in the same condition, as adjusting for gait speed did not change the significant impact of the narrow-base walking condition. Nor was gait speed a significant covariate for head pitch angle (p = .60) or head-roll velocity (p = .26). The average trunk-pitch displacement and trunk-pitch velocity increased in the GVS condition, and trunk-pitch velocity decreased in the narrow-base walking condition. However, these changes in trunk control may be the result of the similar changes in gait speed in the respective conditions. The impact of GVS on the head and trunk is mainly in the M-L direction but not the A-P direction (Wardman et al., 2003). Therefore, increased average trunk-pitch angle and trunk-pitch velocity with GVS may not reflect a direct impact of GVS on trunk control. In particular, increased trunk-pitch angle could be a strategy to bring body’s center of mass slightly forward to facilitate the forward momentum to counteract GVS-induced M-L perturbation (Orendurff et al., 2004). To support this inference, we analyzed the impact of GVS and narrow-base walking on trunk-pitch angle and trunk-pitch velocity, adjusting for gait speed. Despite the result that gait speed was a significant covariate for trunk pitch velocity (p = .003), the significant impact of GVS and the narrow-base walking condition did not change. In this study, trunk-roll angle and velocity did not increase in the GVS condition or in the narrow-base walking condition. It was observed that GVS-induced increased gait speed was accompanied by an increase in step width. It is possible that a higher momentum in the A-P direction together with wider base of support allowed the maintenance of trunk stability in the M-L direction, and thus no GVSinduced impact on trunk roll velocity or angle was found. Conversely, although step width significantly decreased in the narrow-base walking condition because of task constraints, changes in trunk-roll angle or velocity were not observed. The decrease in gait speed in the narrow-base walking condition possibly allowed for longer double support phase to increase the stability in response to the challenge in the M-L direction. Thus, overall, no significant effect of the narrow-base walking condition on trunk M-L stability was found. The results suggest that trunk control in the M-L direction is more complex than A-P control. Even with intact lower limb somatosensory input, vision had a significant impact on head control, and GVS marginally increased head-roll velocity in older people, whereas GVS increased neither trunk-roll velocity nor angular displacement in M-L direction. The subtle differences between head and trunk control found in this study support differential segmental control (Kavanagh, Morrison, & Barrett, 2005). It is suggested that head control may be dependent more on reflexes directly related to the visual and/or vestibular system, such as the optokinetic cervical reflex and/or the vestibulocervical reflex (Dan et al., 2000), showing the importance of the “top-down” model (Massion, 1998). Trunk control may rely more on intact MC Vol. 20, No. 1, 2016
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lower limb sensation (Deshpande & Zhang, 2014), suggesting the importance of the “bottom-up” model (Massion, 1998). No significant difference was found in gait speed between young and older participants. It is probably because a majority of the older participants (12 of 15) included in this study were young old (i.e., 75 years old or younger), and all the older participants were very healthy and active. All of them could walk independently and none of them had any of the conditions mentioned in the exclusion criteria (e.g., neuromuscular disorder). Further, 11 of 15 older participants regularly performed physical exercises for at least 5 hr per week, and the activities ranged from jogging to cycling. The findings in this study were to some extent different than predicted by the hypothesis. Compared with young persons, older participants exhibited only marginally deteriorated ability to reduce the weighting of the discordant vestibular input for controlling head stability but not trunk stability. There was no significant difference between young and older participants in terms of the ability to keep head and trunk stability during narrow-base walking even with sensory manipulations. It is possible that applying GVS intensity at 2 times the threshold may not be enough to evoke differential responses when people were walking at a self-selected speed with intact lower limb somatosensory input and some visual information available. Second, the constraint of 25 cm for foot placement in the narrow-base walking condition may not be a big M-L challenge for healthy older participants. Normalization of the path width to body morphology (e.g., normalization to 50% of the distance between the participant’s anterior superior iliac spines) could be an alternative. However, women are typically shorter and have wider hips than men (Conley et al., 2007). Therefore, normalized path width may have different challenges to men and women. Further, normalization of the path width to body height may suffer from the similar limitation. It is possible that normalization to normal step width could overcome such shortcoming. However, in terms of future clinical use, a standard protocol is easier to apply. This issue requires further research to determine the best protocol. In future studies, the path width could be further reduced or an external M-L perturbation can be used, which may show more subtle age-related changes.
Conclusion The results have shown that reliance on vestibular information to control head velocity in the M-L direction is marginally higher in older people than in young people. Results have also shown vision’s control over head stability regardless of age. In addition, the complexity of trunk control in the M-L direction in different conditions was observed. The findings may enhance our understanding of the importance of the vestibular input and sensory interaction in controlling head and trunk stability during walking, which may lay a foundation for the development of strategies to improve postural control and reduce falls. Acknowledgments This work was supported by Senate Advisory Research Committee, Queen’s University research funding to Dr. Nandini Deshpande. We thank Dr. Alison Novak, Mika Yoshikawa and Patricia Hewston for assistance with data collection. MC Vol. 20, No. 1, 2016
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