Humans optimally anticipate and compensate for an uneven step during walking

Neuromechanical Strategies for Obstacle Negotiation during Overground Locomotion following Incomplete Spinal Cord Injury in Adult Cats

Following incomplete spinal cord injury in animals, including humans, substantial locomotor recovery can occur. However, functional aspects of locomotion, such as negotiating obstacles, remains challenging. We collected kinematic and electromyography data in 10 adult cats (5 males, 5 females) before and at weeks 1-2 and 7-8 after a lateral mid-thoracic hemisection on the right side of the cord while they negotiated obstacles of three different heights. Intact cats always cleared obstacles without contact. At weeks 1-2 after hemisection, the ipsilesional right hindlimb contacted obstacles in ∼50% of trials, triggering a stumbling corrective reaction or absent responses, which we termed Other. When complete clearance occurred, we observed exaggerated ipsilesional hindlimb flexion when crossing the obstacle with contralesional Left limbs leading. At weeks 7-8 after hemisection, the proportion of complete clearance increased, Other responses decreased, and stumbling corrective reactions remained relatively unchanged. We found redistribution of weight support after hemisection, with reduced diagonal supports and increased homolateral supports, particularly on the left contralesional side. The main neural strategy for complete clearance in intact cats consisted of increased knee flexor activation. After hemisection, ipsilesional knee flexor activation remained, but it was insufficient or more variable as the limb approached the obstacle. Intact cats also increased their speed when stepping over an obstacle, an increase that disappeared after hemisection. The increase in complete clearance over time after hemisection paralleled the recovery of muscle activation patterns or new strategies. Our results suggest partial recovery of anticipatory control through neuroplastic changes in the locomotor control system.SIGNIFICANCE STATEMENT Most spinal cord injuries (SCIs) are incomplete and people can recover some walking functions. However, the main challenge for people with SCIs that do recover a high level of function is to produce a gait that can adjust to everyday occurrences, such as turning, stepping over an obstacle, etc. Here, we use the cat model to answer two basic questions: How does an animal negotiate an obstacle after an incomplete SCI and why does it fail to safely clear it? We show that the inability to clear an obstacle is because of improper activation of muscles that flex the knee. Animals recover a certain amount of function thanks to new strategies and changes within the nervous system.

Electrical Brain Activity during Human Walking with Parametric Variations in Terrain Unevenness and Walking Speed

Mobile brain imaging with high-density electroencephalography (EEG) can provide insight into the cortical processes involved in complex human walking tasks. While uneven terrain is common in the natural environment and poses challenges to human balance control, there is limited understanding of the supraspinal processes involved with traversing uneven terrain. The primary objective of this study was to quantify electrocortical activity related to parametric variations in terrain unevenness for neurotypical young adults. We used high-density EEG to measure brain activity when thirty-two young adults walked on a novel custom-made uneven terrain treadmill surface with four levels of difficulty at a walking speed tailored to each participant. We identified multiple brain regions associated with uneven terrain walking. Alpha (8 - 13 Hz) and beta (13 - 30 Hz) spectral power decreased in the sensorimotor and posterior parietal areas with increasing terrain unevenness while theta (4 - 8 Hz) power increased in the mid/posterior cingulate area with terrain unevenness. We also found that within stride spectral power fluctuations increased with terrain unevenness. Our secondary goal was to investigate the effect of parametric changes in walking speed (0.25 m/s, 0.5m/s, 0.75 m/s, 1.0 m/s) to differentiate the effects of walking speed from uneven terrain. Our results revealed that electrocortical activities only changed substantially with speed within the sensorimotor area but not in other brain areas. Together, these results indicate there are distinct cortical processes contributing to the control of walking over uneven terrain versus modulation of walking speed on smooth, flat terrain. Our findings increase our understanding of cortical involvement in an ecologically valid walking task and could serve as a benchmark for identifying deficits in cortical dynamics that occur in people with mobility deficits.

Humans plan for the near future to walk economically on uneven terrain

Humans experience small fluctuations in their gait when walking on uneven terrain. The fluctuations deviate from the steady, energy-minimizing pattern for level walking and have no obvious organization. But humans often look ahead when they walk, and could potentially plan anticipatory fluctuations for the terrain. Such planning is only sensible if it serves some an objective purpose, such as maintaining constant speed or reducing energy expenditure, that is also attainable within finite planning capacity. Here, we show that humans do plan and perform optimal control strategies on uneven terrain. Rather than maintaining constant speed, they make purposeful, anticipatory speed adjustments that are consistent with minimizing energy expenditure. A simple optimal control model predicts economical speed fluctuations that agree well with experiments with humans (N = 12) walking on seven different terrain profiles (correlated with model [Formula: see text] , [Formula: see text] all terrains). Participants made repeatable speed fluctuations starting about six to eight steps ahead of each terrain feature (up to ±7.5 cm height difference each step, up to 16 consecutive features). Nearer features matter more, because energy is dissipated with each succeeding step's collision with ground, preventing momentum from persisting indefinitely. A finite horizon of continuous look-ahead and motor working space thus suffice to practically optimize for any length of terrain. Humans reason about walking in the near future to plan complex optimal control sequences.

Selection of gait parameters during constrained walking

It is commonly thought that at prescribed speeds humans choose gait parameters that minimize the cost of transportation. However, it is unclear whether and how the relationship between step length and step frequency is affected by the additional physiological factors caused by constraints. We performed a series of experiments to understand the selection of gait parameters under different constraints from a probabilistic perspective. First, we show that the effect of constraining step length on step frequency (i.e., monotonically decrease, Experiment I) is different from the effect of constraining step frequency on step length (i.e., inverted-U, Experiment II). Using the results from Experiment I and II, we summarized the marginal distribution of step length and step frequency and built their joint distribution in a probabilistic model. The probabilistic model predicts the selection of gait parameters by achieving the maximum probability of joint distribution of step length and step frequency. In Experiment III, the probabilistic model could well predict gait parameters at prescribed speeds, and it is similar to minimizing the cost of transportation. Finally, we show that the distribution of step length and step frequency were completely different between constrained and non-constrained walking. We argue that constraints in walking are major factors determining how humans choose gait parameters due to their involvement of mediators, i.e., attention or active control. Using the probabilistic model to account for gait parameters has an advantage compared with fixed-parameter models in that it can still include the effect of hidden mechanical, neurophysiological, or psychological variables by grouping them into distribution curves.

Uneven terrain versus dual-task walking: differential challenges imposed on walking behavior in older adults are predicted by cognitive and sensorimotor function

Aging is associated with declines in walking function. To understand these mobility declines, many studies have obtained measurements while participants walk on flat surfaces in laboratory settings during concurrent cognitive task performance (dual-tasking). This may not adequately capture the real-world challenges of walking at home and around the community. Here, we hypothesized that uneven terrains in the walking path impose differential changes to walking speed compared to dual-task walking. We also hypothesized that changes in walking speed resulting from uneven terrains will be better predicted by sensorimotor function than cognitive function. Sixty-three community-dwelling older adults (65-93 yrs old) performed overground walking under varying walking conditions. Older adults were classified into two mobility function groups based on scores of the Short Physical Performance Battery. They performed uneven terrain walking across four surface conditions (Flat, Low, Medium, and High unevenness) and performed single and verbal dual-task walking on flat ground. Participants also underwent a battery of cognitive (cognitive flexibility, working memory, inhibition) and sensorimotor testing (grip strength, 2-pt discrimination, pressure pain threshold). Our results showed that walking speed decreased during both dual-task walking and across uneven terrain walking conditions compared to walking on flat terrain. Participants with lower mobility function had even greater decreases in uneven terrain walking speeds. The change in uneven terrain speed was associated with attention and inhibitory function. Changes in both dual-task and uneven terrain walking speeds were associated with 2-point tactile discrimination. This study further documents associations between mobility, executive functions, and somatosensation, highlights the differential costs to walking imposed by uneven terrains, and identifies that older adults with lower mobility function are more likely to experience these changes to walking function.

Optimization of energy and time predicts dynamic speeds for human walking

Humans make a number of choices when they walk, such as how fast and for how long. The preferred steady walking speed seems chosen to minimize energy expenditure per distance traveled. But the speed of actual walking bouts is not only steady, but rather a time-varying trajectory, which can also be modulated by task urgency or an individual's movement vigor. Here we show that speed trajectories and durations of human walking bouts are explained better by an objective to minimize Energy and Time, meaning the total work or energy to reach destination, plus a cost proportional to bout duration. Applied to a computational model of walking dynamics, this objective predicts dynamic speed vs. time trajectories with inverted U shapes. Model and human experiment (N=10) show that shorter bouts are unsteady and dominated by the time and effort of accelerating, and longer ones are steadier and faster and dominated by steady-state time and effort. Individual-dependent vigor may be characterized by the energy one is willing to spend to save a unit of time, which explains why some may walk faster than others, but everyone may have similar-shaped trajectories due to similar walking dynamics. Tradeoffs between energy and time costs can predict transient, steady, and vigor-related aspects of walking.

Uneven terrain treadmill walking in younger and older adults

We developed a method for altering terrain unevenness on a treadmill to study gait kinematics. Terrain consisted of rigid polyurethane disks (12.7 cm diameter, 1.3-3.8 cm tall) which attached to the treadmill belt using hook-and-loop fasteners. Here, we tested four terrain unevenness conditions: Flat, Low, Medium, and High. The main objective was to test the hypothesis that increasing the unevenness of the terrain would result in greater gait kinematic variability. Seventeen younger adults (age 20-40 years), 25 higher-functioning older adults (age 65+ years), and 29 lower-functioning older adults (age 65+ years, Short Physical Performance Battery score < 10) participated. We customized the treadmill speed to each participant's walking ability, keeping the speed constant across all four terrain conditions. Participants completed two 3-minute walking trials per condition. Using an inertial measurement unit placed over the sacrum and pressure sensors in the shoes, we calculated the stride-to-stride variability in step duration and sacral excursion (coefficient of variation; standard deviation expressed as percentage of the mean). Participants also self-reported their perceived stability for each condition. Terrain was a significant predictor of step duration variability, which roughly doubled from Flat to High terrain for all participant groups: younger adults (Flat 4.0%, High 8.2%), higher-functioning older adults (Flat 5.0%, High 8.9%), lower-functioning older adults (Flat 7.0%, High 14.1%). Similarly, all groups exhibited significant increases in sacral excursion variability for the Medium and High uneven terrain conditions, compared to Flat. Participants were also significantly more likely to report feeling less stable walking over all three uneven terrain conditions compared to Flat. These findings support the hypothesis that altering terrain unevenness on a treadmill will increase gait kinematic variability and reduce perceived stability in younger and older adults.

A biomechanics dataset of healthy human walking at various speeds, step lengths and step widths

The biomechanics of human walking are well documented for standard conditions such as for self-selected step length and preferred speed. However, humans can and do walk with a variety of other step lengths and speeds during daily living. The variation of biomechanics across gait conditions may be important for describing and determining the mechanics of locomotion. To address this, we present an open biomechanics dataset of steady walking at a broad range of conditions, including 33 experimentally-controlled combinations of speed (0.7–2.0 m·s⁻¹), step length (0.5–1.1 m), and step width (0–0.4 m). The dataset contains ground reaction forces and motions from healthy young adults (N = 10), collected using split-belt instrumented treadmill and motion capture systems respectively. Most trials also include pre-computed inverse dynamics, including 3D joint positions, angles, torques and powers, as well as intersegmental forces. Apart from raw data, we also provide five strides of good quality data without artifacts for each trial, and sample software for visualization and analysis.

Measurement(s)	ground reaction force • body position
Technology Type(s)	force platform • motion capture
Factor Type(s)	walking speed • step frequency • step length • step width

Evaluating anticipatory control strategies for their capability to cope with step-down perturbations in computer simulations of human walking

Previous simulation studies investigated the role of reflexes and central pattern generators to explain the kinematic and dynamic adaptations in reaction to step-down perturbations. However, experiments also show preparatory adaptations in humans based on visual anticipation of a perturbation. In this study, we propose a high-level anticipatory strategy augmenting a low-level muscle-reflex control. This strategy directly changes the gain of the reflex control exclusively during the last contact prior to a drop in ground level. Our simulations show that especially the anticipatory reduction of soleus activity and the increase of hamstrings activity result in higher robustness. The best results were obtained when the change in stimulation of the soleus muscle occurred 300 ms after the heel strike of the contralateral leg. This enabled the model to descend perturbation heights up to - 0.21 m and the resulting kinematic and dynamic adaptations are similar to the experimental observations. This proves that the anticipatory strategy observed in experiments has the purpose of increasing robustness. Furthermore, this strategy outperforms other reactive strategies, e.g., pure feedback control or combined feedback and feed-forward control, with maximum perturbation heights of - 0.03 and - 0.07 m, respectively.