By Steven Phu

Slips and trips are the most common causes of falls in ambulant older people, with the rapid activation and coordination of muscles being essential to recover balance following such postural disturbances. For falls prevention, balance (e.g. standing on one leg, tandem walking) and strengthening exercises are highly effective but often lack task specificity. In comparison, reactive balance training directly practices fall circumstances by inducing repeated perturbations such as slips and trips. Although there is accumulating evidence that these more task-specific interventions also prevent falls in older people, the underlying mechanisms remain unclear. For example, we do not know whether postural responses after an unpredictable perturbation are delayed with ageing and if these postural responses can be improved by exercise and/or reactive balance training interventions. Therefore, we performed a systematic review to determine the impact of ageing and interventions (both exercise and reactive balance training) on postural responses following unpredictable perturbations.

After searching the literature for studies assessing delay in muscle activation (onset latency) following an unpredictable perturbation, we compared postural responses of young versus older adults, regular exercisers versus non exercisers and the effects of interventions with (randomised control trials) and without (uncontrolled clinical trials) a control group (Figure 1). Through meta-analysis, we found evidence for significant delays in postural responses in older versus young adults. We also found evidence for faster postural response in regular exercisers (i.e. those who reported continued participation in exercise for at least a year). Finally, in data from controlled trials, we found postural responses were improved after medium (2 to 6 weeks) and long term (≥6 weeks) interventions regardless of the training mode (exercise or reactive balance training). In contrast, short-term interventions over one or two days did not improve postural responses.

In summary, our systematic review and meta-analysis provided evidence for age-related decline and exercise-induced improvement in postural responses following unpredictable perturbations. There was insufficient evidence to determine the ideal modality of intervention (exercise or reactive balance training) to improve postural responses, however, the data suggested interventions lasting at least 2 weeks were required to achieve improvements.

Figure 1. Summary of meta-analysis findings examining onset latency (milliseconds) in response to postural perturbations

Publication

Phu S, Sturnieks DL, Lord SR, Okubo Y. Impact of ageing, fall history and exercise on postural reflexes following unpredictable perturbations: A systematic review and meta-analyses. Mech Ageing Dev. 2022;203:111634. doi: 10.1016/j.mad.2022.111634

https://doi.org/10.1016/j.mad.2022.111634

About the Author

By Yuge Zhang.

Epidemiological research shows that approximately 30% of community-living people aged 65 years and over fall at least once a year. Among them, women appear more likely to fall, with studies reporting that approximately 65% of women fall in their usual place of residence compared to only 44% of men. Portable and cheap inertial sensors has been proved to be a feasible way to quantify collect gait data in people’s own environment on either the trunk or foot. Our aim was to further understand gait differences between young and older women in gait acceleration intensity, variability and stability of the feet and trunk using inertial sensors.

We recruited 20 older women (mean age 68 years) and 18 young women (mean age 22) to walk straight for 100 meters at their preferred speed, while wearing inertial sensors on their heels and lower back (See Figure 1). Since previous research has shown that clinical gait tests of 4 or 10 meters do not represent daily-life gait very well, we asked people to walk 100 meters to reflect well the natural gait without participants being exhausted. We used sagittal plane angular velocity of foot sensor to classify gait events, time of heel strike and toe off (See Figure 2). We found that foot maximum vertical acceleration and amplitude, trunk-foot vertical acceleration attenuation, as well as their variability were significantly smaller in older compared to young women. In contrast, trunk mediolateral acceleration amplitude, maximum vertical acceleration, and amplitude, as well as their variability were significantly larger in older compared to young women. Moreover, older women showed lower stability (i.e., higher LDE values) in mediolateral acceleration as well as lower mediolateral and vertical angular velocities of the trunk.

Even though we measured healthy older women, they had softer floor impacts with higher vertical trunk acceleration, lower attenuation between trunk-foot vertical acceleration, and higher variability of the trunk acceleration, and hence, were more likely to fall. These findings suggest that instrumented gait measurements may help for the early detection of changes or impairments in gait performance.

Figure 1. Test environment

Figure 2. Sagittal plane angular velocity of foot sensor (The blue and red points represented the gait events Theel_strike and Tfoot-flat, respectively)

Publication

Yuge Zhang, Xinglong Zhou, Mirjam Pijnappels, Sjoerd M. Bruijn. Differences in gait stability and acceleration characteristics between healthy young and older females. Frontiers in rehabilitation sciences, 2021. DOI: 10.3389/fresc.2021.763309.

About the Author

By Lotte Grevendonk and Christopher McCrum

There are many benefits of habitual physical activity, exercise and sports participation for older people. However, the extent to which these influence one of the most common causes of injuries in older age, namely falls, is unclear. In this study, we assessed the influence of age on various metabolic and mobility-related outcomes, accounting for physical activity levels. We also evaluated the additional effects of more extensive exercise or sports participation in old age. In this blog post, we focus on our motion-capture derived gait outcomes.

We investigated walking characteristics of 12 younger adults (~24y) versus 13 healthy older adults (~71y) with approximately the same habitual physical activity levels (~10,000 steps per day, 2.6% and 2.2% of waking time in high intensity physical activity). We also compared the same healthy older adults with 15 exercise-trained older adults (~68y, ~14,000 steps per day, 5.3% of waking time in high intensity physical activity, mostly endurance or mixed endurance and resistance-based exercise training).

We first compared spatiotemporal step parameters and their variability between the groups when participants walked on a treadmill at a range of speeds. In these conditions, most gait variables were not affected by age (young vs. old) and none were affected by exercise training (older healthy vs. older trained). These findings indicated that perhaps decline in steady-state walking is slowed with suitable physical activity levels, but not further enhanced by exercise training.

Using repeated treadmill belt acceleration perturbations, we compared groups on stability (first perturbation) and adaptability (repeated perturbations). Despite similar physical activity levels, older adults responded less effectively to the first perturbation compared to their younger peers (Figure 1, top left panel; larger deviation from, and more steps to return to, baseline Anteroposterior Margin of Stability). However, adaptability was not significantly different between age groups (Figure 1, top right panel). We found no clear differences between the healthy and trained older adults in these outcomes (Figure 1, bottom panels).

In conclusion, older people can broadly preserve their spatiotemporal step parameters during unperturbed walking with sufficient physical activity but the ability to cope with large balance disturbances remains less effective initially (adaptability was not affected by age). High levels of exercise training beyond that recommended by the World Health Organisation in old age do not seem to provide further benefit for either aspect of walking stability, but this should be further investigated in larger future studies.

Figure 1. Mean and SD of the anteroposterior margins of stability for the younger versus older participants (Y and O) and for the older versus trained older participants (TO) during the first and ninth perturbations (Pert1R and Pert9L) including unperturbed walking prior to each perturbation (Base), the final step prior to each perturbation (Pre) and the first eight recovery steps following the perturbations (Post1 – 8). A significant group effect from a two-way repeated measures ANOVA was found only for the Y vs. O comparison at Pert1R. *: Significant difference to Base within the group (p < 0.05; adjusted using Dunnett’s multiple comparisons test). #: significant difference between groups (p < 0.05; adjusted using Šídák’s multiple comparisons test).

Publication

Grevendonk L, Connell NJ, McCrum C, Fealy CE, Bilet L, Bruls YMH, Mevenkamp J, Schrauwen-Hinderling VB, Jörgensen JA, Moonen-Kornips E, Schaart G, Havekes B, de Vogel-van den Bosch J, Bragt MCE, Meijer K, Schrauwen P, and Hoeks J. Impact of aging and exercise on skeletal muscle mitochondrial capacity, energy metabolism, and physical function. Nature Communications 12: 4773, 2021. doi: 10.1038/s41467-021-24956-2

About the Author

By Dr Erika Pliner

Ladder use is a hazardous activity and the leading cause of fatal falls from a height. Older adults are at highest risk of experiencing a ladder fall during household activities, such as clearing a roof gutter. Climbing (foot and body position, handhold force) and environmental (climb direction, ladder angle) factors are known to affect ladder fall risk, but little is known about individual characteristics that may predispose someone to a ladder fall. Therefore, we conducted a study to determine individual factors that contribute to effective ladder use.

We recruited 100 older adults and asked them to clear a gutter using a straight ladder in the laboratory (Figure 1). The gutter was 2.1 m above the ground, 5.8 m in length, and filled with tennis balls. The straight ladder was partially fixed to the experimental setup that supported the gutter, simulating a straight ladder leaning against a wall. The ladder was easily moved laterally along the wall to the desired location. To completely clear the length of the gutter, participants had to move and climb the ladder multiple times. We recorded time to complete this task as the outcome measure.

For each participant, we assessed individual metrics of strength, upper limb control, balance, cognition, and propensity for risk-taking. To determine which individual factors are related to effective ladder use, we performed regression analysis with the individual metrics on task completion time. Our results showed that the time taken to clear the gutter was predicted by multiple individual factors. Specifically, participants with greater quadriceps strength, better upper limb coordination, more controlled leaning balance, and a greater propensity for taking risks completed the gutter clearing task faster, suggesting these participants to be more effective ladder users.

Knowledge of individual factors that are associated with effective ladder use can be used to direct ladder fall interventions. Ladder users who take longer to complete ladder tasks (increasing their ladder use exposure and fall risk) may be identified and warned of their fall risk through screening tools and targeted for strength and balance training interventions to reduce their fall risk. Further, this knowledge can guide ladder design and safety instruction. Specifically, ladders could be designed to reduce the need for superior balance control and quadriceps strength with a greater base-of-support at lower rungs commonly used for working heights. Safety instructions may be updated to inform users to utilize additional tools to avoid strenuous postures that require greater upper limb coordination. Future work is needed to assess the trade-off between efficient ladder use (faster task completion times) and risky ladder use (completing the task near or outside stability limits).

Figure 1. Experimental set-up

Pliner, E.M., Sturnieks, D.L., Lord, S.R. (2020). Individual factors that influence task performance on a straight ladder in older people. Experimental Gerontology, 142: 111127. https://doi.org/10.1016/j.exger.2020.111127

About the Author

By Mr Peter Hong, Ms Helen Chong, Dr Vicki Komisar and Dr Steve Robinovitch

The COVID-19 pandemic has created challenges to the ISPGR research community, especially in the collection of new data with human participants. The pandemic has also highlighted the value of shared databases for reuse by other research groups. The Technology for Injury Prevention in Seniors (TIPS) team at Simon Fraser University hopes to foster innovation in the prevention of falls and fall-related injuries in older adults, by sharing a dataset of video footage of real-life falls experienced by older people.

Falls are the number one cause of injuries, and a major barrier to mobility for older people, especially in long-term care. Many ISPGR members pursue research on the cause and prevention of falls in older adults. Yet rarely are we able to draw on objective evidence on how falls occur. Video footage of falls in older adults provides a wealth of information on the circumstances of falls to drive innovation (Robinovitch et al, Lancet, 2013).

The TIPS program at Simon Fraser University (SFU), in partnership with the Fraser Health Authority and two long-term care homes in the Greater Vancouver Area, has recently posted to the Databrary Network an expanded dataset of videos of 239 real-life falls experienced by older adults in long-term care homes. The videos can be accessed at: https://nyu.databrary.org/volume/739.

Databrary is an online data repository, hosted by New York University, that allows for sharing of video data for reuse in research and teaching by investigators associated with an institution having an Institutional Review Board (IRB) for human participant research. To date, Databrary has users from 616 institutions in over 25 countries, and TIPS’s falls videos collection is currently being used by researchers in Canada, Europe and the US. Visit the Databrary website ( https://nyu.databrary.org/user/register?page=create) for extensive instructions on gaining access.

The 239 falls posted to Databrary were selected from a larger pool to represent the range of falls we have observed in long-term care, with respect to: fall direction, activity at time of falling, biomechanical cause of the fall, sex of the individual falling, height of the fall, use of mobility aids, frequency of head impact, and frequency of pelvis impact. The 239 falls were experienced by 100 individuals of mean age 83.3 years (SD = 7.4), all of whom were residents of the two long-term care homes. 52 women accounted for 152 falls, and 48 men accounted for 87 falls. All falls occurred in common areas (hallways, dining rooms, lounges). For 111 of the 239 falls, at least two camera views captured the fall, which could allow for subsequent 3D kinematic analyses.

In addition to the video footage, the Databrary dataset includes Excel spreadsheets that allow you to search the dataset based on: the number of camera views, the frame rate and resolution of the video, characteristics of the resident falling (age, sex, height, weight), injuries associated with the fall, use of  mobility aids, biomechanical cause of the fall, and the activity at the time of the fall. For those residents who provided consent, we include data on medications and disease diagnoses.

TIPS hopes to foster innovation in geriatric falls research and education by sharing the falls video database with researchers, healthcare professionals, and educators. The dataset may be particularly relevant for researchers pursuing sensor-based fall detection, and the design of exoskeletons, assistive devices, environmental modifications, and wearable protective gear. The dataset should also help to inform more externally valid approaches to assess postural stability and risk for falls in older adults.

Figure 1. Example of fall sequence captured by video footage in a long-term care home.

References and example publications related to the real-life falls database:

Komisar, V, Shishov, N, Yang, Y, Robinovitch, SN. (2020) Effect of Holding Objects on the Occurrence of Head Impact in Falls by Older Adults: Evidence From Real-Life Falls in Long-Term Care, The Journals of Gerontology: Series A, glaa168, https://doi.org/10.1093/gerona/glaa168

van Schooten KS, Yang Y, Robinovitch SN (2018). The association between fall frequency, injury risk and characteristics of falls in older residents of long-term care: do recurrent fallers fall more safely? The Journals of Gerontology: Series A, Volume 73, Issue 6, June 2018, Pages 786–791, https://doi.org/10.1093/gerona/glx196

Robinovitch SN, Feldman F, Yang Y, Schonnop R, Leung PM, Sarraf T, Sims-Gould J, and Loughin M. (2013) Video capture of the circumstances of falls in elderly people residing in long-term care: an observational study. The Lancet. 381(9873): 47-54. https://doi.org/10.1016/S0140-6736(12)61263-X

About the Author

By Maud van den Bogaart

Falls are a major cause of injury and death in older people (1). Based on his appearance, and according to common belief, Santa Claus has been estimated to be around 1750 years of age. Extrapolating the known relationship between age and fall risk, Santa Claus should have an extremely high risk of falling, which is aggravated by his night shift work under winter conditions. Additionally, carrying a load, such as a sack with presents, changes the gait pattern in a way that increases fall risk (2). A fall may preclude Santa from performing his annual chore and puts the happiness of millions of children at risk.

A sensitive parameter to detect fall risk is a person’s gait variability, defined as the stride-to-stride variations of gait kinematics. Indeed, older people at risk of falls are known to walk with increased gait variability compared to their counterparts with a lower fall risk (3). Unfortunately, to date, Santa’s natural habitat lacks a gait analysis setup to quantify his gait variability and assess his fall risk. Moreover, his busy schedule precludes a visit to a gait lab. Therefore, estimates of Santa’s fall risk are based on extrapolation and hence likely unreliable. New techniques based on deep learning, with a high degree of automatization, can assess gait variability in a natural environment from simple video-recordings (4). Using such novel methodology would allow to assess Santa in his natural habitat whilst not hampering his Christmas chores. This markerless method (DeepLabCut) has significant advantages over laboratory-based optoelectronic gait analysis, in that it is free, open-source, applicable in the participant’s natural environment, and requires only a video camera. Therefore, it is likely to be particularly useful for routine gait analysis in clinical settings.

Using DeepLabCut, we investigated Santa’s gait and gait variability, to assess his fall risk using a, presumably authentic, video we found on YouTube (Figure 1). In spite of his likely extremely old age, Santa’s gait variability puts him in a considerably younger age group, with values comparable to those of people between the age of 65 and 70 years old (2, 5). Hence, Santa’s gait variability and therefore fall risk could not be linearly extrapolated with age. Additionally, Santa adopted a different posture and increased gait variability when carrying presents, which was also similar to that of older people aged 65 –to 70 years (Figure 1). Carrying presents indeed increased Santa’s gait variability, which suggests a higher fall risk while making people merry during Christmas time (2).

In conclusion, we highly  recommended Santa to train his strength, balance and gait stability before the Christmas season and, if possible, to spread the delivery of presents over a longer period to reduce his risk of falling. The use of deep learning to analyze gait in natural environments and clinical settings is very promising and I expect that it will revolutionize the field of rehabilitation medicine.

Figure 1. Workflow of the gait analysis of video-recordings of Santa Claus walking with and without a Christmas sack with presents in sagittal and frontal plane using deep learning (Deeplabcut; pretrained human gait model). Video-recordings of Santa Claus during one of his practice runs with and without a Christmas sack with presents were collected (https://youtu.be/U9eUqR7uXEE, https://youtu.be/Pbfp04UCMCs, https://youtu.be/phpm0AF3AO4, https://youtu.be/dvn5qujgrjE). The DeepLabCut human-pretrained model was used to retrieve the 2D locations of anatomical landmarks (e.g. ankle, knee, hip and shoulder) during walking (https://github.com/DeepLabCut/DeepLabCut/blob/master/examples/COLAB_DLC_ModelZoo.ipynb). Stride length, time and width were defined by the 2D locations of the ankle joint centers. Seven strides were analyzed per video. Differences in stride length, width and time variability between conditions were tested for significance using the Levene’s Test of Homogeneity of Variance (α=0.05).

References

1. Haagsma JA, Graetz N, Bolliger I, Naghavi M, Higashi H, Mullany EC, et al. The global burden of injury: incidence, mortality, disability-adjusted life years and time trends from the Global Burden of Disease study 2013. Inj Prev. 2016;22(1):3-18.
2. Walsh GS, Low DC, Arkesteijn M. Effect of stable and unstable load carriage on walking gait variability, dynamic stability and muscle activity of older adults. J Biomech. 2018;73:18-23.
3. Callisaya ML, Blizzard L, Schmidt MD, McGinley JL, Srikanth VK. Ageing and gait variability–a population-based study of older people. Age Ageing. 2010;39(2):191-7.
4. Nath T, Mathis A, Chen AC, Patel A, Bethge M, Mathis MW. Using DeepLabCut for 3D markerless pose estimation across species and behaviors. Nat Protoc. 2019;14(7):2152-76.
5. Hollman JH, McDade EM, Petersen RC. Normative spatiotemporal gait parameters in older adults. Gait Posture. 2011;34(1):111-8.

About the Author

By Dr Sudeshna Chatterjee

In the past several years, studies have shown that the prefrontal cortex — which has a crucial role in the control of executive functions including attention, working memory, and motor planning — is also involved in the neural control of walking. Mobile brain imaging approaches, such as functional near-infrared spectroscopy, allow us to measure prefrontal cortical activation during the performance of various walking tasks. While this is extremely valuable, an important yet unresolved challenge in the measurement and interpretation of brain activity during walking is the influence of inter-individual differences on brain activation. In our study, we address important knowledge gaps by investigating the extent to which prefrontal cortical activation during an obstacle negotiation task relative to typical steady state walking is explained by inter-individual differences in age, executive function, and sex in older adults. Furthermore, we present a novel perspective on the interpretation of prefrontal activation during walking based on a conceptual model of brain aging, the Compensation-Related Utilization of Neural Circuits Hypothesis (CRUNCH). Developed by Reuter-Lorenz and Cappell (2008), CRUNCH is a broader conceptual framework that consolidates several brain aging models including neural inefficiency, neural compensation, and capacity limitation.

We found that age, executive function, and their interaction are significant predictors of prefrontal activation during obstacle negotiation in older adults. Consistent with CRUNCH, among older adults of a younger age (< 75 years), lower executive function was associated with neural inefficiency where greater recruitment of prefrontal activation was observed during obstacle negotiation compared to their peers with higher executive function (Panel A). In contrast, older adults of an advanced age (≥ 75 years) exhibited a ceiling effect of brain recruitment resources during obstacle negotiation regardless of executive function level (Panel B). Panels C and D show the conceptual interpretation of our data based on the CRUNCH framework. Finally, we found evidence of compensatory overactivation, where greater prefrontal activation was associated with a smaller drop in obstacle negotiation speed compared to typical steady state walking.

Our findings demonstrate that the interaction between task demands and individual characteristics may influence the functional range of brain activity available during complex walking and this should be considered by studies designed to intervene on brain activation efficiency to enhance walking ability in older adults. We suggest that future studies should measure activity from additional brain regions; design walking tasks with multiple gradations of difficulty; and include genetics and lifestyle as these variables may protect against or worsen mobility decline in older adults.

Figure 1: Panels A and B show the prefrontal activity data during typical steady state walking (Typical) and obstacle negotiation (Obstacles) in the early and late aging groups. Panels C and D show the conceptual interpretation of our data based on the Compensation-Related Utilization of Neural Circuits Hypothesis (CRUNCH) framework. EF denotes executive function. ΔO2Hb denotes the change in prefrontal activity during the walking period compared to the reference period for each task. ΔPFR denotes the change in prefrontal recruitment during Obstacles compared to Typical. Group differences in ΔPFR are reported as Cohen’s d.

This research was supported by a NIH/NIA R21 grant awarded to Dr. David J. Clark, Associate Professor at the University of Florida (The UPfront Walking Study).

Publication

Chatterjee SA, Seidler RD, Skinner JW, Lysne PE, Sumonthee C, Wu SS, Cohen RA, Rose DK, Woods AJ, Clark DJ. Obstacle negotiation in older adults: prefrontal activation interpreted through conceptual models of brain aging. Innov Aging. 2020;4(4):1-12. doi: 10.1093/geroni/igaa034.

About the Author

By Dr Paulo Cezar Rocha dos Santos

Perturbations to a healthy person’s walking can emerge from external (e.g., slip, trip) and/or internal constraints. Without a fast and effective response, perturbations lead to a loss of balance and falls. Internal perturbations might originate from a state of fatigue, limiting the capacity to allocate internal resources during a motor task. Because of age-related reductions in neuromuscular function, older adults might have increased difficulty adapting the neuromuscular control of walking when fatigued. Neuromuscular control can be assessed by intermuscular beta-band (15-35Hz) coherence, which is an indirect indication of a common neural drive to two muscles.

In a study published in Scientific Reports, we examined the effects of age on intermuscular beta-band coherence during treadmill walking before and after an experimentally induced fatiguing task. Twelve older and 12 younger adults walked on a treadmill for 3min, at 1.2 m/s, before and after performing a repetitive sit-to-stand test (fatiguing task). We calculated gait metrics (length, width, swing and stance time, cadence) and intermuscular coherence in late swing and early stance phases in knee and ankle synergistic and antagonistic muscle pairs from 100 strides of data.

We observed only minimal effects of age and fatigue on gait metrics. However, before a repetitive sit-to-stand test, we observed that, compared with younger, older adults had lower (48-62%) coherence in synergistic muscle pairs (Figure 1a). After a repetitive sit-to-stand test, gastrocnemius lateralis-soleus coherence in swing decreased by ~ 23% and increased by ~ 23% in younger and older, respectively (Figure 1b). We also observed that tibialis anterior-peroneus longus increased by 16%, and rectus-biceps femoris coherence in late swing decreased by ~ 20%, independent of age (although this difference seems to be driven by older adults, Figure 1b).

We interpreted the weak intermuscular coherence in old age as the central nervous system’s inefficiency in reducing motor control’s complexity by sending common drives to synergistic muscles. Fatigue may elicit an age-specific compensation in neuromuscular control whereby despite lower-limb fatigue, older adults increased intermuscular coherence between ankle synergistic muscle pairs enabling them to keep walking.

To sum up, this study improves our understanding of how healthy aging brings about adaptations during gait and how such adaptations could change into compensations to maintain walking performance.

Figure 1. Intermuscular beta-band coherence before and after experimentally induced fatigue (repetitive sit-to-stand protocol) in younger (gray bars) and older (green bars) adults; a) mean and standard error of beta-band coherence before a repetitive sit-to-stand test; b) relative change in percentage induced by a repetitive sit-to-stand test in late swing (orange) and early stance (blue) phases. GL: gastrocnemius lateralis, SL: Soleus, TA: tibialis anterior, PL: peroneus longus; RF: rectus femoris, VL: vastus lateralis, BF: biceps femoris. Figure adapted from Santos et al., 2020.

Publication

dos Santos, P.C.R., Lamoth, C.J.C., Barbieri, F.A. et al. Age-specific modulation of intermuscular beta coherence during gait before and after experimentally induced fatigue. Sci Rep 10, 15854 (2020). https://doi.org/10.1038/s41598-020-72839-1

About the Author

By Dr Keisuke Hirata

During walking, the front foot often slips when it comes in contact with a slippery surface (due to oil, water, ice, etc.). If the leading foot slips forward during walking, the body tends to rotate backward and a corrective response such as a backward step is adopted. The slip velocity relative to the walking velocity could be a determinant of falls. However, experimental studies using artificial slipping environments are still needed to clarify the exact relationship between slip velocity and walking velocity. This is because even though walking velocity can be unified among participants, slip velocity cannot, as it depends on the individual body weight. To overcome this problem, we used a double-belt treadmill built into the floor. The treadmill was programed to independently control the slip velocity and timing of each belt.

The participants walked onto the belt of the treadmill from overground walking (Figure 1A). The treadmill was programed to induce a slip (with a maximum slip velocity of 1.6 m/s) for a single foot (Figure 1B). The motion capture system recorded ten young male adults walking onto the belt under fast (≈ 1.6m/s) and slow (≈ 0.9m/s) walking velocity conditions. We classified the corrective responses based on heel marker distances as follows: (1) stop walking (taking-step strategy) and (2) keep walking (overcome the slip and continue the trial). The results showed that, in slow conditions, most participants took wide steps or stepped backward and then stopped walking (Figure 1C). Moreover, increased step length and hip flexion angle of the slipping leg was associated with effortless corrective response only in the slow walking condition.

In older people with balance-related problems who walk slowly, the unexpected slip perturbation velocity may be greater than the walking velocity. Considering the relationship between walking velocity and slip velocity, rehabilitation for falls prevention should focus on increasing the hip joint range of motion and on training at-risk people to take longer steps to ensure a stable base of support.

Figure 1 A: The experimental environment. B: Schematic of the situation wherein a slip occurs. C: The result of relationships between the corrective response (foot markers distance) and walking velocity.

Publication

Hirata K, Kokubun T, Miyazawa T, Hanawa H, Kubota K, Sonoo M, Fujino T, Kanemura N. 2020 Relationship Between the Walking Velocity Relative to the Slip Velocity and the Corrective Response. Journal of Medical and Biological Engineering. doi: https://doi.org/10.1007/s40846-020-00527-6

About the Author