Minimum toe clearance: probing the neural control of locomotion

Tim Killeen, Christopher S Easthope, László Demkó, Linard Filli, Lilla Lőrincz, Michael Linnebank, Armin Curt, Björn Zörner, Marc Bolliger, Tim Killeen, Christopher S Easthope, László Demkó, Linard Filli, Lilla Lőrincz, Michael Linnebank, Armin Curt, Björn Zörner, Marc Bolliger

Abstract

Minimum toe clearance (MTC) occurs during a highly dynamic phase of the gait cycle and is associated with the highest risk of unintentional contact with obstacles or the ground. Age, cognitive function, attention and visual feedback affect foot clearance but how these factors interact to influence MTC control is not fully understood. We measured MTC in 121 healthy individuals aged 20-80 under four treadmill walking conditions; normal walking, lower visual field restriction and two Stroop colour/word naming tasks of two difficulty levels. Competition for cognitive and attentional resources from the Stroop task resulted in significantly lower mean MTC in older adults, with the difficult Stroop task associated with a higher frequency of extremely low MTC values and subsequently an increased modelled probability of tripping in this group. While older adults responded to visual restriction by markedly skewing MTC distributions towards higher values, this condition was also associated with frequent, extremely low MTC values. We reveal task-specific, age-dependent patterns of MTC control in healthy adults. Age-related differences are most pronounced during heavy, distracting cognitive load. Analysis of critically-low MTC values during dual-task walking may have utility in the evaluation of locomotor control and fall risk in older adults and patients with motor control deficits.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1
Experimental setup. Healthy adults aged 20–80 underwent 3D gait analysis while walking on an instrumented treadmill without handrail support. They undertook four locomotor tasks. Normal walking without a secondary task (a) was performed with the eyes fixed on a cross at eye height. Participants then walked while engaged in two Stroop colour-naming task (see methods) of differing difficulty. Image (b) shows the simpler task in which word and colour stimuli are congruent. In the more difficult, incongruent task (c) word and colour are discordant. Participants also carried out a visual restriction task in which they walked wearing eye goggles, the lower half of which were covered in black fabric to obscure the lower visual field. The upper edge of the fabric was affixed at the level of the subject’s interpupillary line. This figure was adapted from Fig. 1 in the publication Killeen et al. Increasing cognitive load attenuates right arm swing in healthy human walking. R. Soc. open sci. 2017 4 160993; DOI: 10.1098/rsos.160993. Published 25 January 2017 under the Creative Commons Attribution Licence 4.0.
Figure 2
Figure 2
Minimum toe clearance parameters under different locomotor conditions. (a) The effect of age group on MTC in each of the four walking conditions. Differences in mean MTC between age groups (younger adults; 20–39, middle-aged adults; 40–59, older adults; 60–80) tested using ANOVA and post-hoc t-tests where appropriate with significance set at p ≤ 0.05, corrected for multiple comparisons (Bonferroni). NW; normal walking, CS; congruent Stroop task, IS; incongruent Stroop task, VR; visual restriction. (b) Within-age group condition effects on mean MTC, compared using a linear mixed model (see methods) and post-hoc t-tests where appropriate with significance set at p ≤ 0.05, corrected for multiple comparisons (Bonferroni). (c) Differences in mean MTC variability (coefficient of variation; CoV) between age groups, compared using ANOVA as in (a). (d) Condition effect on MTC timing variability (CoV), compared using a linear mixed model as in b). Error bars indicate SEM.
Figure 3
Figure 3
Scatter plot of age and mean minimum toe clearance under four walking conditions. During the congruent and incongruent Stroop tasks, age was a significant, but weak, negative predictor of MTC, with R2 values of 0.043 (F = 4.9; p = 0.030) in the congruent and 0.050 (F = 6.0; p = 0.016) in the incongruent task. During normal walking and visual restriction, no such relationship was observed.
Figure 4
Figure 4
Relative MTC frequency distributions for healthy adults aged 60–80 years. Each individual contributed MTC values for 25 consecutive strides. Values indicated are mean frequencies per 1 mm bin with error bars indicating standard error of the mean. The histogram for normal walking is indicated in (a) and is presented as a semi-transparent overlay (grey) to allow comparison with the histograms of the three locomotor conditions (black; (bd)). Similar graphics for the younger and middle-aged cohorts may be found in the Supplementary Material.
Figure 5
Figure 5
Minimum toe clearance cumulative relative frequency graphs for each age group. Each individual contributed 25 consecutive MTC values to the group histogram. Dotted lines indicate MTC thresholds of 5 mm and 10 mm, while shaded area indicates MTC values over 10 mm. MTC; minimum toe clearance.
Figure 6
Figure 6
Tripping probability modelling for healthy adults aged 20–80 years during normal walking and under increased cognitive load. Modelling was based on the group frequency distributions and followed the approach taken by Best and Begg. Briefly, per-stride probabilities of striking a hypothetical, unseen obstacle of a given height at MTC are modelled based on MTC frequency distributions, including skewness and kurtosis. Similar graphics for all conditions and age groups may be found in the Supplementary Material.

References

    1. Ayoung-Chee P, et al. Long-term outcomes of ground-level falls in the elderly. J. Trauma Acute Care Surg. 2014;76:498–503. doi: 10.1097/TA.0000000000000102.
    1. World Health Organization. In WHO Global Report on Falls Prevention in Older Age. 1–9 (WHO Press 2007).
    1. Blake AJ, Morgan K, Bendall MJ. Falls by elderly people at home: prevalence and associated factors. Age Ageing. 1988;17:365–372. doi: 10.1093/ageing/17.6.365.
    1. Rosen T, Mack KA, Noonan RK. Slipping and tripping: fall injuries in adults associated with rugs and carpets. J. Inj. Violence Res. 2013;5:61–69. doi: 10.5249/jivr.v5i1.177.
    1. Nagano H, Begg RK, Sparrow WA, Taylor S. Ageing and limb dominance effects on foot-ground clearance during treadmill and overground walking. Clin. Biomech. 2011;26:962–968. doi: 10.1016/j.clinbiomech.2011.05.013.
    1. Winter, D. A. The Biomechanics and Motor Control of Human Locomotion: Normal, Elderly and Pathological. (University of Waterloo Press 1991).
    1. Winter, D. A. Foot trajectory in human gait: a precise and multifactorial motor control task. Phys. Ther. 72, 45–53–6 (1992).
    1. Best R, Begg R. A method for calculating the probability of tripping while walking. J. Biomech. 2008;41:1147–1151. doi: 10.1016/j.jbiomech.2007.11.023.
    1. Barrett RS, Mills PM, Begg RK. A systematic review of the effect of ageing and falls history on minimum foot clearance characteristics during level walking. Gait Posture. 2010;32:429–435. doi: 10.1016/j.gaitpost.2010.07.010.
    1. Mirelman A, et al. Executive function and falls in older adults: New findings from a five-year prospective study link fall risk to cognition. PLoS One. 2012;7:1–8. doi: 10.1371/journal.pone.0040297.
    1. Muir-Hunter SW, Wittwer JE. Dual-task testing to predict falls in community-dwelling older adults: a systematic review. Physiotherapy. 2015;102:29–40. doi: 10.1016/j.physio.2015.04.011.
    1. Laessoe U, Hoeck HC, Simonsen O, Voigt M. Residual attentional capacity amongst young and elderly during dual and triple task walking. Hum. Mov. Sci. 2008;27:496–512. doi: 10.1016/j.humov.2007.12.001.
    1. Yogev-Seligmann G, Hausdorff JM, Giladi N. The role of executive function and attention in gait. Mov. Disord. 2008;23:329–342. doi: 10.1002/mds.21720.
    1. Springer S, et al. Dual-tasking effects on gait variability: The role of aging, falls, and executive function. Mov. Disord. 2006;21:950–957. doi: 10.1002/mds.20848.
    1. Gomes, G. de C. et al. Gait performance of the elderly under dual-task conditions: Review of instruments employed and kinematic parameters. Rev. Bras. Geriatr. e Gerontol. 165–182 (2016).
    1. Montero-Odasso M, Verghese J, Beauchet O, Hausdorff JM. Gait and cognition: A complementary approach to understanding brain function and the risk of falling. J. Am. Geriatr. Soc. 2012;60:2127–2136. doi: 10.1111/j.1532-5415.2012.04180.x.
    1. Pelosin E, et al. Attentional Control of Gait and Falls: Is Cholinergic Dysfunction a Common Substrate in the Elderly and Parkinson’s Disease? Front. Aging Neurosci. 2016;8:104. doi: 10.3389/fnagi.2016.00104.
    1. Woollacott M, Shumway-Cook A. Attention and the control of posture and gait: a review of an emerging area of research. Gait Posture. 2002;16:1–14. doi: 10.1016/S0966-6362(01)00156-4.
    1. Lundin-Olsson L, Nyberg L, Gustafson Y. ‘Stops walking when talking’ as a predictor of falls in elderly people. Lancet. 1997;349:617. doi: 10.1016/S0140-6736(97)24009-2.
    1. Herman T, Mirelman A, Giladi N, Schweiger A, Hausdorff JM. Executive control deficits as a prodrome to falls in healthy older adults: A prospective study linking thinking, walking, and falling. Journals Gerontol. - Ser. A Biol. Sci. Med. Sci. 2010;65A:1086–1092. doi: 10.1093/gerona/glq077.
    1. Hamacher D, Hamacher D, Schega L. Towards the importance of minimum toe clearance in level ground walking in a healthy elderly population. Gait Posture. 2014;40:727–729. doi: 10.1016/j.gaitpost.2014.07.016.
    1. Mills PM, Barrett RS, Morrison S. Toe clearance variability during walking in young and elderly men. Gait Posture. 2008;28:101–107. doi: 10.1016/j.gaitpost.2007.10.006.
    1. Santhiranayagam BK, Lai DTH, Sparrow WA, Begg RK. Minimum toe clearance events in divided attention treadmill walking in older and young adults: a cross-sectional study. J. Neuroeng. Rehabil. 2015;12:58. doi: 10.1186/s12984-015-0052-2.
    1. Sparrow WA, Begg RK, Parker S. Variability in the foot-ground clearance and step timing of young and older men during single-task and dual-task treadmill walking. Gait Posture. 2008;28:563–7. doi: 10.1016/j.gaitpost.2008.03.013.
    1. Alcock L, Galna B, Lord S, Rochester L. Characterisation of foot clearance during gait in people with early Parkinson’s disease: Deficits associated with a dual task. J. Biomech. 2016;49:2763–2769. doi: 10.1016/j.jbiomech.2016.06.007.
    1. Al-Yahya E, et al. Cognitive motor interference while walking: A systematic review and meta-analysis. Neurosci. Biobehav. Rev. 2011;35:715–728. doi: 10.1016/j.neubiorev.2010.08.008.
    1. Kesler A, et al. Shedding light on walking in the dark: the effects of reduced lighting on the gait of older adults with a higher-level gait disorder and controls. J. Neuroeng. Rehabil. 2005;2:27. doi: 10.1186/1743-0003-2-27.
    1. Hamacher D, Hamacher D, Krowicki M, Schega L. Gait Variability in Chronic Back Pain Sufferers With Experimentally Diminished Visual Feedback: A Pilot Study. J. Mot. Behav. 2015;48:205–8. doi: 10.1080/00222895.2015.1073136.
    1. Graci V, Elliott DB, Buckley JG. Peripheral visual cues affect minimum-foot-clearance during overground locomotion. Gait Posture. 2009;30:370–374. doi: 10.1016/j.gaitpost.2009.06.011.
    1. Heasley K, Buckley JG, Scally A, Twigg P, Elliott DB. Stepping up to a new level: Effects of blurring vision in the elderly. Investig. Ophthalmol. Vis. Sci. 2004;45:2122–2128. doi: 10.1167/iovs.03-1199.
    1. Begg R, Best R, Dell’Oro L, Taylor S. Minimum foot clearance during walking: Strategies for the minimisation of trip-related falls. Gait Posture. 2007;25:191–198. doi: 10.1016/j.gaitpost.2006.03.008.
    1. Svoboda B, Kranzl A. A study of the reproducibility of the marker application of the Cleveland Clinic Marker Set including the Plug-In Gait Upper Body Model in clinical gait analysis. Gait Posture. 2012;36:S62–S63. doi: 10.1016/j.gaitpost.2011.10.286.
    1. Vicon. Plug-in-Gait modelling instructions. Plug-in-Gait Manual (2002).
    1. Killeen, T. et al. Modulating Arm Swing Symmetry with Cognitive Load: A Window on Rhythmic Spinal Locomotor Networks in Humans? J. NeurotraumaEpub ahead of print, 1–6 (2016).
    1. Stroop J. Studies of interference in serial verbal reactions. J. Exp. Psychol. 1935;121:15–23. doi: 10.1037/0096-3445.121.1.15.
    1. Sejdić E, Fu Y, Pak A, Fairley JA, Chau T. The Effects of Rhythmic Sensory Cues on the Temporal Dynamics of Human Gait. PLoS One. 2012;7:e43104. doi: 10.1371/journal.pone.0043104.
    1. Verghese J, Holtzer R, Lipton RB, Wang C. Quantitative gait markers and incident fall risk in older adults. J. Gerontol. A Biol. Sci. Med. Sci. 2009;64:896–901. doi: 10.1093/gerona/glp033.
    1. Maki BE. Gait changes in older adults: predictors of falls or indicators of fear. J. Am. Geriatr. Soc. 1997;45:313–320. doi: 10.1111/j.1532-5415.1997.tb00946.x.
    1. De Asha AR, Buckley JG. The effects of walking speed on minimum toe clearance and on the temporal relationship between minimum clearance and peak swing-foot velocity in unilateral trans-tibial amputees. Prosthet. Orthot. Int. 2015;39:120–125. doi: 10.1177/0309364613515493.
    1. Capaday C, Lavoie BA, Barbeau H, Schneider C, Bonnard M. Studies on the corticospinal control of human walking. I. Responses to focal transcranial magnetic stimulation of the motor cortex. J. Neurophysiol. 1999;81:129–39.
    1. Brouwer B, Ashby P. Corticospinal projections to lower limb motoneurons in man. Exp. Brain Res. 1992;89:649–654. doi: 10.1007/BF00229889.
    1. Yang JF, Gorassini M. Spinal and brain control of human walking: implications for retraining of walking. Neuroscientist. 2006;12:379–389. doi: 10.1177/1073858406292151.
    1. Tucker MR, et al. Control strategies for active lower extremity prosthetics and orthotics: a review. NeuroEngineering Rehabil. 2015;12:1. doi: 10.1186/1743-0003-12-1.
    1. Clark DJ. Automaticity of walking: functional significance, mechanisms, measurement and rehabilitation strategies. Front. Hum. Neurosci. 2015;9:246.
    1. Schulz BW, Lloyd JD, Lee WE. The effects of everyday concurrent tasks on overground minimum toe clearance and gait parameters. Gait Posture. 2010;32:18–22. doi: 10.1016/j.gaitpost.2010.02.013.
    1. Heasley K, Buckley JG, Scally A, Twigg P, Elliott DB. Falls in older people: Effects of age and blurring vision on the dynamics of stepping. Investig. Ophthalmol. Vis. Sci. 2005;46:3584–3588. doi: 10.1167/iovs.05-0059.
    1. Killeen T, et al. Increasing cognitive load attenuates right arm swing in healthy human walking. R. Soc. Open Sci. 2017;4:160993. doi: 10.1098/rsos.160993.
    1. Manchester D, Woollacott M, Zederbauer-Hylton N, Marin O. Visual, Vestibular and Somatosensory Contributions to Balance Control in the Older Adult. J. Gerontol. 1989;44:M118–M127. doi: 10.1093/geronj/44.5.M118.
    1. Seidler RD, et al. Motor control and Aging: Links to age-related brain structural, functional and biomechanical effects. Neurosci. Biobehav. Rev. 2011;34:721–733. doi: 10.1016/j.neubiorev.2009.10.005.
    1. Dietz V. Human neuronal control of automatic functional movements: interaction between central programs and afferent input. Physiol. Rev. 1992;72:33–69.
    1. Hausdorff JM, Yogev G, Springer S, Simon ES, Giladi N. Walking is more like catching than tapping: gait in the elderly as a complex cognitive task. Exp. Brain Res. 2005;164:541–8. doi: 10.1007/s00221-005-2280-3.
    1. Hallemans A, Ortibus E, Meire F, Aerts P. Low vision affects dynamic stability of gait. Gait Posture. 2010;32:547–551. doi: 10.1016/j.gaitpost.2010.07.018.
    1. Gabell A, Nayak USL. The Effect of Age on Variability in Gait. J. Gerontol. 1984;39:662–666. doi: 10.1093/geronj/39.6.662.
    1. Morris ME, Iansek R, Matyas Ta, Summers JJ. Ability to modulate walking cadence remains intact in Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry. 1994;57:1532–1534. doi: 10.1136/jnnp.57.12.1532.
    1. Van Dyck E, et al. Spontaneous Entrainment of Running Cadence to Music Tempo. Sport. Med. Open. 2015;2:15. doi: 10.1186/s40798-015-0025-9.
    1. Kaipust JP, McGrath D, Mukherjee M, Stergiou N. Gait variability is altered in older adults when listening to auditory stimuli with differing temporal structures. Ann. Biomed. Eng. 2013;41:1595–603. doi: 10.1007/s10439-012-0654-9.
    1. Filli L, et al. Monitoring long-term efficacy of fampridine in gait-impaired patients with multiple sclerosis. Neurology. 2017;88:832–41. doi: 10.1212/WNL.0000000000003656.
    1. Schulz BW. Minimum toe clearance adaptations to floor surface irregularity and gait speed. J. Biomech. 2011;44:1277–1284. doi: 10.1016/j.jbiomech.2011.02.010.
    1. Dadashi F, et al. Gait and foot clearance parameters obtained using shoe-worn inertial sensors in a large-population sample of older adults. Sensors. 2013;14:443–457. doi: 10.3390/s140100443.
    1. Hollman JH, et al. A comparison of variability in spatiotemporal gait parameters between treadmill and overground walking conditions. Gait Posture. 2016;43:204–209. doi: 10.1016/j.gaitpost.2015.09.024.
    1. McGrath D, Greene BR, Walsh C, Caulfield B. Estimation of minimum ground clearance (MGC) using body-worn inertial sensors. J. Biomech. 2011;44:1083–1088. doi: 10.1016/j.jbiomech.2011.01.034.

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