By Mr Alexandre Tapin and Dr Cyril Duclos

Virtual reality (VR) applications are developed for many purposes: entertainment (video games), culture (visiting a virtual museum) or rehabilitation. However walking is difficult to simulate with current VR systems. It requires a large space and/or the ability to produce actual gait movements. So can we make someone feel that they are walking while they are actually standing? The perception that we are walking is in part mediated by proprioception which may be mimicked by muscle vibration. Vibrating muscles at 70-100Hz can generate proprioceptive information of lengthening of the vibrated muscle, which is perceived as joint motion. For example, vibration of the quadriceps is associated with perception of knee flexion. A study successfully simulated perception of writing letters using six vibrators activated in a specific pattern at the upper-limb. Another study induced small lower-limb gait motions in quiet-standing participants using vibrations patterned according to the sequence of gait movements. However, we do not know whether participants ‘perceived’ gait motion during these vibrations. The main goal of this study was to quantify gait motion perception during multiple vibrations and how this perception was modulated by various factors.

We installed twelve vibrators on the flexor and extensor muscles at the hips, knees, and ankles bilaterally of 20 young healthy participants. Vibrations were applied at 80Hz with a pattern simulating gait (60 steps/minute) for one minute while participants stood (Figure, left). Eleven conditions were tested (one trial per condition) to test the effect of vision, vibration frequency, and the number and type of joints stimulated on gait movement perception.

At the end of each trial, the level of perception of gait motion was quantified using a visual analog scale (0 (feels stationary) to 10 (feels like walking)). Every participant, but one, had good perception of gait motion (>5/10) for one or more conditions. Visual conditions did not seem to affect perception systematically, but absence of knees stimulation and low vibration frequency decreased the level of perception of gait motion (Figure, right) .

Figure. left: montage of the position of the vibrators; right: boxplot of the gait motion perception scores regarding conditions. Whiskers indicates min and max, upper and bottom side of the box indicates respectively third and first quartiles, the line and the cross within the box respectively indicates the median and the mean.

Gait-like proprioceptive stimulation can induce gait motion perception in individuals who are standing, even when visual information is available. Combined with an avatar in VR, it could improve the immersion in the VR experience through coherent visual and proprioceptive feedbacks and be used to better understand multisensory integration processes. It could also be used to complete the loop in brain machine interfaces where the intent of action is determined using neuroimaging and the proprioceptive and visual feedbacks associated with the intended action are provided by multiple vibration and VR. This may offer a powerful tool to stimulate neuroplasticity after neurological injury.

Publication

Tapin, A., Duclos, N.C., Jamal, K. et al. Perception of gait motion during multiple lower-limb vibrations in young healthy individuals: a pilot study. Exp Brain Res (2021).  https://doi.org/10.1007/s00221-021-06199-1

About the Author

By Liana Tennant

Common sense tells us that flip-flops should never be worn in the chemistry lab or when cutting the grass, but could flip-flops increase injury risk in less obvious situations? We were approached by a forensic engineering company who wanted to determine the role flip-flops might play in a slip and fall incident. In addition to evaluating slip dynamics on wet and dry tile, the firm also wanted to know how slips change when the foot is also wet, a scenario that might be encountered on a rainy day. We expected that with a wet foot, it might move around inside the flip-flop during a slip. A slip within a slip if you will.

To answer these questions, we invoked slips from a standing posture by pulling one ankle forward using a cable and pulley device (Figure 1). Although the slip speeds using this method were higher than those reported during walking, it allowed us to control some of the variables that can affect how slips occur and progress. We tracked the foot and flip-flop separately using a 3D motion capture system. We found that there was minimal relative motion between the foot and flip-flop during slips, so long as the flip-flop stayed on the foot; however, in several instances the flip-flop slid forward off the participant’s heel, which we called ‘decoupling.’ Decoupling occurs when the friction between the foot and flip-flop is insufficient to halt the forward momentum of the flip-flop caused by the initial pull at the ankle. Sometimes the flip-flop came off entirely (see video Figure 2 )! Decoupling happened in at least 1 of 27 slips for 12 of the 17 participants. We saw decoupling less often on wet tile with a dry foot, and more often when both the tile and foot were either dry or wet.

This study highlighted that friction between the foot and flip-flop matters. When flip-flops are worn, two different yet important slips may occur: 1) your flip-flop can slip along the ground or 2) your foot can slip inside the flip-flop. If you lose your flip-flop during a slip, you could injure your unprotected foot, or it might make it harder for you to catch yourself when falling. The results also have implications for flip-flop design. As consumers, we likely focus on how comfortable our footwear is, but the materials and the surface texture of the flip-flop footbed could also be important from a safety perspective. Future work evaluating real-life scenarios like walking or going downstairs is needed to see if decoupling occurs as frequently in these situations as what we saw when we invoked a slip.

Figure1. The experimental setup. The participant stood with their right foot on a tile mounted on a force plate. Their ankle was connected to a cable and pulley machine loaded with 25% of the participant’s body weight (weight stack was hidden from view). An active motion capture system was used to track the foot and flip-flop. The participant wore a harness tethered to the ceiling to protect them in the event of a fall.

Figure 2. This video shows an example of the decoupling phenomenon we observed during some of the slips. Playback is at 0.5x speed. The flip-flop is represented by the white planar surface.

Publication

Tennant, L.M., Fok, D.J., Kingston, D.C., Winberg, T.B., Parkinson, R.J., Laing, A.C., Callaghan, J.P., 2021. Analysis of invoked slips while wearing flip-flops in wet and dry conditions: Does alternative footwear alter slip kinematics? Applied Ergonomics 92, 103318. https://doi.org/10.1016/j.apergo.2020.103318

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 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

By Prokopios Antonellis

Walking on level ground demands little effort, but walking on grades quickly becomes challenging. Is it possible to minimize energy expenditure with shoe outsoles that offset downhill or uphill grades? We investigated the interaction effects of outsole geometry and grade on the metabolic rate and biomechanics of walking.

We developed a modular shoe that allows for altering the inclination of the foot relative to the ground. Shoe height differences were between 3 to 6 cm between the heel and toe region. We tested the effect of these different shoe inclinations on the metabolic rate and biomechanics of downhill and uphill walking at different grades, including level walking. Each condition lasted 5 minutes. We expected that offsetting the downhill or uphill grade would minimize metabolic rate. Remarkably, shoes that exactly offset the grade did not minimize the metabolic rate. Instead, shoes that compensated for about half of the grade (by using a raised heel for uphill walking and a raised toe for downhill walking) proved to be optimal. Shoe inclination primarily influenced (distal) ankle joint parameters (e.g., soleus activity, ankle moment, and work rate), whereas grade influenced (whole-body) ground reaction force and center-of-mass parameters, as well as (distal) ankle joint parameters.

Walking on uneven terrain with uphill and downhill sections, the metabolic rate is mostly affected by the uphill portions. As such, it could be advantageous to use shoes with a slight downward shoe inclination in these situations (Figure). It could also be possible to design shoes that allow for changing the inclination depending on the grade of the terrain to avoid repetitive overstretching of the calf muscles. Our results could further explain some of the differences in metabolic rate between walking on stairs and ramps at an equivalent average grade. Current construction guidelines recommend the use of ramps for low grades and the use of stairs for higher grades. The benefit of shoes that partially offset the average grade, as observed in the current study, might, therefore, be seen as indirect evidence of the benefit of stairs. Overall, these modular shoes could be used as a research instrument to optimize parameters other than metabolic rate, such as minimizing joint loading to prevent injuries or assisting with walking on rolling terrain.

Figure: Modular shoe that allows for offsetting uphill and downhill grades. The shoe shown here has a downward outsole configuration for facilitating uphill walking. The figure evokes a potential outdoor application. The experiments were conducted during indoor walking between treadmill grades of -6° and 6°.

Publication

Antonellis, P., Frederick, C. M., Gonabadi, A. M., & Malcolm, P. (2020). Modular footwear that partially offsets downhill or uphill grades minimizes the metabolic cost of human walking. Royal Society open science, 7(2), 191527. https://doi.org/10.1098/rsos.191527

About the Author

By Dr Matthew King

Investigations of biomechanics are an ever-growing field of scientific research, with the assessment of “gait” being a popular choice to inform both clinical and experimental directions. However, what cannot be gleaned from the term “gait” is the type of locomotion that is being studied. Are the participants walking, running, crawling or jogging?

Initially, the study of human movement was so novel, that the term “gait” may have been all-encompassing. Over time, the term “gait” has been substituted to describe walking. However, “gait” is not mutually exclusive to walking, nor humans. Horses gallop and trot, fish swim, and humans run (just to name a few). What is not know is the task (or type of locomotion) being performed – as “gait” is the pattern produced during a mode of locomotion, not locomotion itself.

To demonstrate the ambiguous use of the term “gait”, our recent publication reviewed the 319 papers published in Gait and Posture in 2019. In summary, approximately half of the papers that directly evaluated locomotion described the task as “gait” in the title with no quantifier (noun, verb, or gerund) for the actual task being performed (FIG).

Our primary goal for completing this paper and outlining this information, is to shed light on various, and often incorrect, use of the word “gait”. Together, as clinicians, academics, and scientists alike, we must rise to the challenge in being more literal in what we study and why. In particular with the use of the word “gait”. In doing so, search strategies will be streamlined, titles will provide insight into the task studied, and the ability for individuals to locate relevant research studies to further their evidence-based practice will be simplified.

Figure. Use of the word “gait” in the titles of papers published in Gait and Posture in 2019

Publication

Gill, N., Kean, C., & King, M. G. (2020). Let’s take the dog for a gait…. Gait & Posture, 79, pp. 1-2. doi: https://doi.org/10.1016/j.gaitpost.2020.03.018

About the Author

By Fabian Herold and Dennis Hamacher

Most people go to the gym to become fitter, build muscles, and shape their body, but they may not be fully aware that they strengthen their brain, too. In recent years, the evidence showing that resistance exercise training can improve cognitive functions has accumulated. However, the processes which lead to an improvement of cognitive functions are currently not well understood. In the sense of “use-it-or-lose-it”, one explanatory approach postulates that resistance exercise “indirectly” trains higher cognitive functions because their execution demands higher cognitive processes (e.g., attention). This phenomenon might be comparable with a cognitive training (e.g., doing a Sudoku or memory game such as pairs) in which specific cognitive functions are trained by engaging those regularly. Such a regular engagement triggers biological processes (e.g., changes in functional brain activation) leading to the preservation or the increase in cognitive performance. In this regard, resistance exercise training might “indirectly” train specific higher cognitive functions because higher cognitive processes are engaged to execute a resistance exercise. Although it is likely that this assumption is true, whether resistance exercise requires higher cognitive processes has only been sparsely studied so far. Therefore, this study aimed to investigate whether higher cognitive processes are involved in the execution of a resistance exercise. For this purpose, we used a dual- task paradigm in which the change in performance from single-task condition to dual-task condition is used to probe the amount of cognitive resources that are required to execute the motor task (e.g., resistance exercise).

In this study, twenty-four young healthy adults were asked to solve a cognitive task (serial subtractions of 7’s) during standing (single-task condition) and during low-load barbell back squatting (dual-task condition). Additionally, we used questionnaires to quantify the level of experience in strength training and relative perceived exertion. We observed that the numbers of total and of correct responses to the cognitive task were significantly lower during squatting than during standing (see Figure 1) whereas accuracy scores (percentage of correct responses relative to total amount of responses given) did not change significantly. Furthermore, we did not find significant correlations between level of strength training experience or relative perceived exertion and changes in cognitive performance.

In the dual-task paradigm, the changes in cognitive performance from single-task to dual-task are used to probe the amount of cognitive resources which are needed to perform a motor task (e.g., resistance exercises). A motor task that is relatively automatized would not require higher cognitive resources and would, in turn, not lead to a decrease in cognitive performance in a dual-task situation. Vice versa, motor tasks which rely on higher cognitive resources would lead to a decrease in cognitive performance in a dual-task situation. As we observed (i) that the number of correct responses is lower during squatting and (ii) that there is no correlation between relative perceived exertion and cognitive performance, our findings therefore suggest that the execution of low-load barbell back squatting requires higher cognitive processes and, in turn, supports the idea that the regular execution of resistance exercise may “indirectly” train higher cognitive functions. While our study provides initial evidence that low-load barbell squatting is not a brainless exercise, it will be interesting to see if our findings can be generalized to other resistance exercises (e.g., bench press) and other cohorts (e.g., older individuals) in future studies.

Figure. Medians, interquartile range, and total range (minimum to maximum) of (A) Number of total answers and (B) Number of correct answers in single-task condition and dual-task condition are presented. An asterisk (*) marks significant differences between single-task condition and dual-task condition. The hash (#) indicates a significant difference between the first and fifth set in the dual-task condition. A “black dot” represents an outlier.

Publication

Herold F, Hamacher D, Törpel A, Goldschmidt L, Müller NG and Schega L. (2020): Does squatting need attention?—A dual-task study on cognitive resources in resistance exercise. In: PLOS ONE 15 (1), e0226431. DOI: 10.1371/journal.pone.0226431.

About the Author

By Victoria Rapos

On a daily basis, individuals are constantly required to avoid another moving person in order to avoid a collision. Successfully avoiding a potential collision requires both walkers to mutually adapt their speed and orientation. The metric, Minimum Predicted Distance (MPD) has been used as a predictor variable in order to determine the risk of collision over time between two adult walkers. We were interested in determining whether MPD could be used to predict future risks of collisions between middle-aged children and adults.

Eighteen middle-aged children (mean±SD=10±1.5years) and eighteen adults (34±9.6years) walked at their normal pace, along a 12.6m pathway while avoiding another individual (child or adult). Three adults and three children were recruited per session. The study consisted of four obstructing walls (2.3m long), 90° to one another acting as barriers, such that participants were unaware who they were interacting with until they reached a steady walking speed. Each adult interacted with another adult 20 times, each child interacted with another child 20 times, and each adult interacted with a child 21 times. Motion capture of each participant’s head was recorded. The location of each participant’s head at each point in time was used to compute MPD and the walking speed of each participant. MPD(t) represents the progression of the distance between the two walkers if both walkers did not change their speed or path orientation at that instant in time. Trials were categorized as adult-adult, child-child, adult-child passing second, and child-adult passing second for statistical analysis.

The results of this study demonstrated that MPD(t) can be used to predict a future collision in children. When a child was involved in an interaction, MPD(t) was always lower compared to when two adults were interacting, with the lowest progression of MPD(t) being when two children interacted with one another. This is likely due to the differences in body size of the individuals. Since MPD(t) is an absolute measure, it does not consider body anthropometrics. Similar to previous collision avoidance research, the walker passing second, even when it is a child, contributes more to avoidance behaviour compared to the walker passing first. Therefore, the findings from the present study demonstrate that middle-aged children are capable of making adult-like decisions during a collision avoidance task involving two walkers. MPD is smaller in children compared to adults which may be due to person-specific characteristics or developmental changes. Body anthropometrics/characteristics should be considered when determining collision avoidance strategies between children and adults.

Figure. Mean evolution of minimum predicted distance (MPD(t)) over time for each group. In other words, the predicted distance two walkers would avoid one another if no adaptation to their behaviours occurred at each time point (i.e., 100% is the final crossing distance) Interactions were separated into adult-adult (AA), child-child (CC), adult-child passing second (AC), and child- adult passing second (CA).(Figure revised from Rapos et al., 2019).

Publication

Rapos, V., Cinelli, M., Snyder, N., Crétual, A., & Olivier, A-H. (2019). Minimum predicted distance: Applying a common metric to collision avoidance strategies between children and adult walkers. Gait & Posture, 72, 16-21. DOI: https://doi.org/10.1016/j.gaitpost.2019.05.016

About the Author