Consumer-priced wearable sensors combined with deep learning can be used to accurately predict ground reaction forces during various treadmill running conditions.

Ground reaction force (GRF) data is often collected for the biomechanical analysis of running, due to the performance and injury risk insights that GRF analysis can provide. Traditional methods typically limit GRF collection to controlled lab environments, recent studies have looked to combine the ease of use of wearable sensors with the statistical power of machine learning to estimate continuous GRF data outside of these restrictions. Before such systems can be deployed with confidence outside of the lab they must be shown to be a valid and accurate tool for a wide range of users. The aim of this study was to evaluate how accurately a consumer-priced sensor system could estimate GRFs whilst a heterogeneous group of runners completed a treadmill protocol with three different personalised running speeds and three gradients. Fifty runners (25 female, 25 male) wearing pressure insoles made up of 16 resistive sensors and an inertial measurement unit ran at various speeds and gradients on an instrumented treadmill. A long short term memory (LSTM) neural network was trained to estimate both vertical ( G R F v ) and anteroposterior ( G R F a p ) force traces using leave one subject out validation. The average relative root mean squared error (rRMSE) was 3.2% and 3.1%, respectively. The mean ( G R F v ) rRMSE across the evaluated participants ranged from 0.8% to 8.8% and from 1.3% to 17.3% in the ( G R F a p ) estimation. The findings from this study suggest that current consumer-priced sensors could be used to accurately estimate two-dimensional GRFs for a wide range of runners at a variety of running intensities. The estimated kinetics could be used to provide runners with individualised feedback as well as form the basis of data collection for running injury risk factor studies on a much larger scale than is currently possible with lab based methods.

Collision avoidance behaviours while young adults avoid a virtual pedestrian approaching on a 45° angle under attentionally demanding conditions.

Individuals rely on visual information to determine when to adapt their behaviours (i.e., by changing path and/or speed) to avoid an approaching object or person. After initiating an avoidance behaviour, individuals may control the space (i.e., minimum clearance distance) between themselves and another person or object. The current study aimed to determine the action strategies of young adults while avoiding a virtual pedestrian approaching along a 45° angle in an attentionally demanding task. Twenty-one young adults (22.9 ± 1.9 yrs., 11 males) were immersed in a virtual environment and were instructed to walk along a 7.5 m path towards a goal located along the midline. Two virtual pedestrians (VP) positioned 2.83 m to the left and right of the midline approached participants on a 45° angle. To manipulate the point at which the participants and the VP would intersect during different trials, the VP approached at one of three speeds: 0.8×, 1.0×, or 1.2× each participants' average walking speed. Participants were instructed to walk to a goal without colliding with the VP while performing the attention task; reporting whether a shape changed above the VPs' heads. Results revealed that young adults did not modulate their timing of avoidance to the approach characteristics of the VP, as they consistently avoided the collision 1.67 s after the VP began moving. However, young adults seem to control how they avoid an oncoming collision by maintaining a consistent safety margin after an avoidance behaviour was initiated.

Investigation of intersegmental coordination patterns in human walking.

BACKGROUND: Intersegmental coordination between thigh, shank, and foot plays a crucial role in human gait, facilitating stable and efficient human walking. Limb elevation angles during the gait cycle form a planar manifold describes the by the planar covariation law, a recognized fundamental aspect of human locomotion. RESEARCH QUESTION: How does the walking speed, age, BMI, and height, affect the size and orientation of the intersegmental coordination manifold and covariation plane? METHODS: This study introduces novel metrics for quantifying intersegmental coordination, including the mean radius of the manifold, rotation of the manifold about the origin, and the orientation of the plane with respect to the coordinate planes. A statistical investigation is conducted on a publicly available human walking dataset for subjects aged 19-67 years, walking at speeds between 0.18 and 2.3 m s-1 to determine correlations of the proposed quantities. We used two sample t-test and ANOVA to find statistical significance of changes in the metrics with respect to gender and walking speed, respectively. Regression analysis was used to establish relationships between the introduced metrics and walking speed. RESULTS: High correlations are observed between walking speed and the computed metrics, highlighting the sensitivity of these metrics to gait characteristics. Conversely, negligible correlations are found for demographic parameters like age, body mass index (BMI), and height. Male and female groups exhibit no practically significant differences in any of the considered metrics. Additionally, metrics tend to increase in magnitude as walking speed increases. SIGNIFICANCE: This study contributes numerical metrics to characterize ISC of lower limbs with respect to walking speed along with regression models to estimate these metrics and related kinematic quantities. These findings hold significance for enhancing clinical gait analysis, generating optimal walking trajectories for assistive devices, prosthetics, or rehabilitation, aiming to replicate natural gaits and improve the functionality of biomechanical devices.

Intersegmental coordination in human slip perturbation responses.

Intersegmental coordination (ISC) of lower limbs and planar covariation law (PCL) are important phenomena observed in biomechanics of human walking and other activities. Gait perturbations tend to cause deviation from the expected ISC pattern thus violating PCL. We used a data set of seven subjects, who experienced unexpected slips, to investigate and characterize the evolution of ISC during slip recoveries and falls. We have analyzed and presented the development of ISC patterns, encompassing the step preceding the slip initiation and duration of slip until it stops. The results show that the ISC patterns during slip recovery deviate considerably from the normal walking patterns. A newly proposed Euclidian distance-based metric (EDM) was used to quantify the deviation from the normal walking ISC pattern during four slip recoveries and three falls evaluated at gait events such as slip start, foot strike, and peak height of the swing foot. The timing of gait events after slip, pattern of EDM, placement of the feet after slip and temporal patterns of each limb angle have been presented. This initial investigation provides insight into the ISC during slip recovery which highlights the human natural recovery trajectories during such perturbations. The observed patterns of the ISC trajectories during slip can be used for the design of human-inspired controllers for exoskeleton devices that can provide external assistance to human subjects during balance recovery.

Faster stepping cadence partially explains the higher metabolic cost of walking among females versus males.

The metabolic cost of walking (MCOW), or oxygen uptake normalized to distance, provides information on the energy expended during movement. There are conflicting reports as to whether sex differences in MCOW exist, with scarce evidence investigating factors that explain potential sex differences. This study 1) tested the hypothesis that females exhibit a higher MCOW than males, 2) determined whether normalizing to stepping cadence ameliorates the hypothesized sex difference, and 3) explored whether more habitual step counts and time in intensity-related physical activity, and less sedentary time were associated with a decreased MCOW. Seventy-six participants (42 females, 24 ± 5 yr) completed a five-stage, graded treadmill protocol with speeds increasing from 0.89 to 1.79 m/s (6-min walking stage followed by 4-min passive rest). Steady-state oxygen uptake (via indirect calorimetry) and stepping cadence (via manual counts) were determined. Gross and net MCOW, normalized to distance traveled (km) and step-cadence (1,000 steps) were calculated for each stage. Thirty-nine participants (23 females) wore an activPAL on their thigh for 6.9 ± 0.4 days. Normalized to distance, females had greater gross MCOW (J/kg/km) at all speeds (P < 0.014). Normalized to stepping frequency, females exhibited greater gross and net MCOW at 1.12 and 1.79 m/s (J/kg/1,000 steps; P < 0.01) but not at any other speeds (P < 0.075). Stature was negatively associated with free-living cadence (r = -0.347, P = 0.030). Females expend more energy/kilometer traveled than males, but normalizing to stepping cadence attenuated these differences. Such observations provide an explanation for prior work documenting higher MCOW among females and highlight the importance of stepping cadence when assessing the MCOW.NEW & NOTEWORTHY Whether there are sex differences in the metabolic cost of walking (MCOW) and the factors that may contribute to these are unclear. We demonstrate that females exhibit a larger net MCOW than males. These differences were largely attenuated when normalized to stepping cadence. Free-living activity was not associated with MCOW. We demonstrate that stepping cadence, but not free-living activity, partially explains the higher MCOW in females than males.

Gait Variability at Different Walking Speeds.

Gait variability (GV) is a crucial measure of inconsistency of muscular activities or body segmental movements during repeated tasks. Hence, GV might serve as a relevant and sensitive measure to quantify adjustments of walking control. However, it has not been clarified whether GV is associated with walking speed, a clarification needed to exploit effective better bilateral coordination level. For this aim, fourteen male students (age 22.4 ± 2.7 years, body mass 74.9 ± 6.8 kg, and body height 1.78 ± 0.05 m) took part in this study. After three days of walking 1 km each day at a self-selected speed (SS) on asphalt with an Apple Watch S. 7 (AppleTM, Cupertino, CA, USA), the participants were randomly evaluated on a treadmill at three different walking speed intensities for 10 min at each one, SS - 20%/SS + 20%/ SS, with 5 min of passive recovery in-between. Heart rate (HR) was monitored and normalized as %HRmax, while the rate of perceived exertion (RPE) (CR-10 scale) was asked after each trial. Kinematic analysis was performed, assessing the Contact Time (CT), Swing Time (ST), Stride Length (SL), Stride Cycle (SC), and Gait Variability as Phase Coordination Index (PCI). RPE and HR increased as the walking speed increased (p = 0.005 and p = 0.035, respectively). CT and SC decreased as the speed increased (p = 0.0001 and p = 0.013, respectively), while ST remained unchanged (p = 0.277). SL increased with higher walking speed (p = 0.0001). Conversely, PCI was 3.81 ± 0.88% (high variability) at 3.96 ± 0.47 km·h-1, 2.64 ± 0.75% (low variability) at SS (4.94 ± 0.58 km·h-1), and 3.36 ± 1.09% (high variability) at 5.94 ± 0.70 km·h-1 (p = 0.001). These results indicate that while the metabolic demand and kinematics variables change linearly with increasing speed, the most effective GV was observed at SS. Therefore, SS could be a new methodological approach to choose the individual walking speed, normalize the speed intensity, and avoid a gait pattern alteration.

Automatic learning mechanisms for flexible human locomotion.

Movement flexibility and automaticity are necessary to successfully navigate different environments. When encountering difficult terrains such as a muddy trail, we can change how we step almost immediately so that we can continue walking. This flexibility comes at a cost since we initially must pay deliberate attention to how we are moving. Gradually, after a few minutes on the trail, stepping becomes automatic so that we do not need to think about our movements. Canonical theory indicates that different adaptive motor learning mechanisms confer these essential properties to movement: explicit control confers flexibility, while forward model recalibration confers automaticity. Here we uncover a distinct mechanism of treadmill walking adaptation - an automatic stimulus-response mapping - that confers both properties to movement. The mechanism is flexible as it learns stepping patterns that can be rapidly changed to suit a range of treadmill configurations. It is also automatic as it can operate without deliberate control or explicit awareness by the participants. Our findings reveal a tandem architecture of forward model recalibration and automatic stimulus-response mapping mechanisms for walking, reconciling different findings of motor adaptation and perceptual realignment.

Restoring walking ability in older adults with arm-in-arm gait training: study protocol for the AAGaTT randomized controlled trial.

CONTEXT: Falls are a significant problem among older adults. While balance and functional exercises have been shown to be effective, it remains unclear whether regular walking has specific effects on reducing the risk of falls. RATIONALE: Older people who fall frequently have impaired gait patterns. Recent studies have suggested using interpersonal synchronization: while walking arm-in-arm, an older person synchronizes steps with a younger person to reinstate a better gait pattern. This method of gait training may reduce the risk of falls. OBJECTIVE: The aim is to assess the efficacy of an arm-in-arm gait-training program in older people. DESIGN: The arm-in-arm gait training trial (AAGaTT) is a single-site, open label, two-arm, randomized controlled trial. PARTICIPANTS: We will enroll 66 dyads of older people and their younger "gait instructors". The older participants must be > 70 years old with adequate walking ability. They must have experienced a fall in the year prior to study entry. INTERVENTION: Dyads will walk an indoor course for 30 min either side-by-side without contact (control group) or arm-in-arm while synchronizing their gait (intervention group). The gait training will be repeated three times a week for four weeks. OUTCOMES: The main outcome will be the walking speed measured in five-minute walking trials performed at baseline and at the end of each intervention week (week 1 - week 4), and at week 7. Gait quality will be assessed using accelerometers. We will also assess perceived physical activity and health using questionnaires. Finally, we will monitor fall incidence over 18 months. We will evaluate whether outcomes are more improved in the intervention group compared to the control group. In addition, interviews will be conducted to assess the perception of the gait training. EXPECTED RESULTS: Recent advances in the neurophysiology of motor control have shown that synchronizing gait to external cues or to a human partner can increase the efficiency of gait training. The expected benefits of arm-in-arm gait training are: reduced risk of falls, safe treatment with no adverse effects, and high adherence. This gait training program could be a low-cost intervention with positive effects on the health and well-being of seniors. TRIAL REGISTRATION: ClinicalTrials.gov NCT05627453. Date of registration: 11.25.2022.

Tapping Into Skeletal Muscle Biomechanics for Design and Control of Lower Limb Exoskeletons: A Narrative Review.

Lower limb exoskeletons and exosuits ("exos") are traditionally designed with a strong focus on mechatronics and actuation, whereas the "human side" is often disregarded or minimally modeled. Muscle biomechanics principles and skeletal muscle response to robot-delivered loads should be incorporated in design/control of exos. In this narrative review, we summarize the advances in literature with respect to the fusion of muscle biomechanics and lower limb exoskeletons. We report methods to measure muscle biomechanics directly and indirectly and summarize the studies that have incorporated muscle measures for improved design and control of intuitive lower limb exos. Finally, we delve into articles that have studied how the human-exo interaction influences muscle biomechanics during locomotion. To support neurorehabilitation and facilitate everyday use of wearable assistive technologies, we believe that future studies should investigate and predict how exoskeleton assistance strategies would structurally remodel skeletal muscle over time. Real-time mapping of the neuromechanical origin and generation of muscle force resulting in joint torques should be combined with musculoskeletal models to address time-varying parameters such as adaptation to exos and fatigue. Development of smarter predictive controllers that steer rather than assist biological components could result in a synchronized human-machine system that optimizes the biological and electromechanical performance of the combined system.

Investigating the roles of reflexes and central pattern generators in the control and modulation of human locomotion using a physiologically plausible neuromechanical model.

Objective.Studying the neural components regulating movement in human locomotion is obstructed by the inability to perform invasive experimental recording in the human neural circuits. Neuromechanical simulations can provide insights by modeling the locomotor circuits. Past neuromechanical models proposed control of locomotion either driven by central pattern generators (CPGs) with simple sensory commands or by a purely reflex-based network regulated by state-machine mechanisms, which activate and deactivate reflexes depending on the detected gait cycle phases. However, the physiological interpretation of these state machines remains unclear. Here, we present a physiologically plausible model to investigate spinal control and modulation of human locomotion.Approach.We propose a bio-inspired controller composed of two coupled CPGs that produce the rhythm and pattern, and a reflex-based network simulating low-level reflex pathways and Renshaw cells. This reflex network is based on leaky-integration neurons, and the whole system does not rely on changing reflex gains according to the gait cycle state. The musculoskeletal model is composed of a skeletal structure and nine muscles per leg generating movement in sagittal plane.Main results.Optimizing the open parameters for effort minimization and stability, human kinematics and muscle activation naturally emerged. Furthermore, when CPGs were not activated, periodic motion could not be achieved through optimization, suggesting the necessity of this component to generate rhythmic behavior without a state machine mechanism regulating reflex activation. The controller could reproduce ranges of speeds from 0.3 to 1.9 m s-1. The results showed that the net influence of feedback on motoneurons (MNs) during perturbed locomotion is predominantly inhibitory and that the CPGs provide the timing of MNs' activation by exciting or inhibiting muscles in specific gait phases.Significance.The proposed bio-inspired controller could contribute to our understanding of locomotor circuits of the intact spinal cord and could be used to study neuromotor disorders.

Locomotion behavior of chronic Non-Specific Low Back Pain (cNSLBP) participants while walking through apertures.

BACKGROUND: Chronic Non-Specific Low Back Pain (cNSLBP) has been identified as one of the leading global causes of disability and is characterized by symptoms without clear patho-anatomical origin. The majority of clinical trials assess cNSLBP using scales or questionnaires, reporting an influence of cognitive, emotional and behavioral factors. However, few studies have explored the effect of chronic pain in daily life tasks such as walking and avoiding obstacles, which involves perceptual-motor processes to interact with the environment. RESEARCH QUESTION: Are action strategies in a horizontal aperture crossing paradigm affected by cNSLBP and which factors influence these decisions ? METHODS: 15 asymptomatic adults (AA) and 15 cNSLBP participants walked along a 14 m long path, crossing through apertures ranging from 0.9 to 1.8 times their shoulder width. Their movement was measured using the Qualisys system, and pain perception was evaluated by self-administered questionnaires. RESULTS: The cNSLBP participants stopped rotating their shoulders for a smaller aperture relative to their shoulder width (1.18) than the AA participants (1.33). In addition, these participants walked slower, which gave them more time to make the movement adaptations necessary to cross the aperture. No correlation was found between the variables related to pain perception and the critical point but the levels of pain were low with a small variability. SIGNIFICANCE: This study shows that during a horizontal aperture crossing task requiring shoulder rotation to pass through small apertures, cNSLBP participants appear to exhibit a riskier adaptive strategy than AA participants by minimizing rotations that could induce pain. This task thus makes it possible to discriminate between cNSLBP participants and pain-free participants without measuring the level of pain. The identification number registered in the clinical trials is NCT05337995.

Energy cost differences between marathon runners and soccer players: Constant versus shuttle running.

Purpose: In the last decades, the energy cost assessment provided new insight on shuttle or constant running as training modalities. No study, though, quantified the benefit of constant/shuttle running in soccer-players and runners. Therefore, the aim of this study was to clarify if marathon runners and soccer players present specific energy cost values related to their training experience performing constant and shuttle running. Methods: To this aim, eight runners (age 34 ± 7.30y; training experience 5.70 ± 0.84y) and eight soccer-players (age 18.38 ± 0.52y; training experience 5.75 ± 1.84y) were assessed randomly for 6' on shuttle-running or constant-running with 3 days of recovery in-between. For each condition, the blood lactate (BL) and the energy cost of constant (Cr) and shuttle running (CSh) was determined. To assess differences for metabolic demand in terms of Cr, CSh and BL over the two running conditions on the two groups a MANOVA was used. Results: V·O2max were 67.9 ± 4.5 and 56.8 ± 4.3 ml·min-1 kg-1 (p = 0.0002) for marathon runners and soccer players, respectively. On constant running, the runners had a lower Cr compared to soccer players (3.86 ± 0.16 J kg-1m-1 vs. 4.19 ± 0.26 J kg-1 m-1; F = 9.759, respectively; p = 0.007). On shuttle running, runners had a higher CSh compared to soccer players (8.66 ± 0.60 J kg-1 m-1 vs. 7.86 ± 0.51 J kg-1 m-1; F = 8.282, respectively; with p = 0.012). BL on constant running was lower in runners compared to soccer players (1.06 ± 0.07 mmol L-1 vs. 1.56 ± 0.42 mmol L-1, respectively; with p = 0.005). Conversely, BL on shuttle running was higher in runners compared to soccer players 7.99 ± 1.49 mmol L-1 vs. 6.04 ± 1.69 mmol L-1, respectively; with p = 0.028). Conclusion: The energy cost optimization on constant or shuttle running is strictly related to the sport practiced.

Experiment protocols for brain-body imaging of locomotion: A systematic review.

Introduction: Human locomotion is affected by several factors, such as growth and aging, health conditions, and physical activity levels for maintaining overall health and well-being. Notably, impaired locomotion is a prevalent cause of disability, significantly impacting the quality of life of individuals. The uniqueness and high prevalence of human locomotion have led to a surge of research to develop experimental protocols for studying the brain substrates, muscle responses, and motion signatures associated with locomotion. However, from a technical perspective, reproducing locomotion experiments has been challenging due to the lack of standardized protocols and benchmarking tools, which impairs the evaluation of research quality and the validation of previous findings. Methods: This paper addresses the challenges by conducting a systematic review of existing neuroimaging studies on human locomotion, focusing on the settings of experimental protocols, such as locomotion intensity, duration, distance, adopted brain imaging technologies, and corresponding brain activation patterns. Also, this study provides practical recommendations for future experiment protocols. Results: The findings indicate that EEG is the preferred neuroimaging sensor for detecting brain activity patterns, compared to fMRI, fNIRS, and PET. Walking is the most studied human locomotion task, likely due to its fundamental nature and status as a reference task. In contrast, running has received little attention in research. Additionally, cycling on an ergometer at a speed of 60 rpm using fNIRS has provided some research basis. Dual-task walking tasks are typically used to observe changes in cognitive function. Moreover, research on locomotion has primarily focused on healthy individuals, as this is the scenario most closely resembling free-living activity in real-world environments. Discussion: Finally, the paper outlines the standards and recommendations for setting up future experiment protocols based on the review findings. It discusses the impact of neurological and musculoskeletal factors, as well as the cognitive and locomotive demands, on the experiment design. It also considers the limitations imposed by the sensing techniques used, including the acceptable level of motion artifacts in brain-body imaging experiments and the effects of spatial and temporal resolutions on brain sensor performance. Additionally, various experiment protocol constraints that need to be addressed and analyzed are explained.

Modification of the locomotor pattern when deviating from the characteristic heel-to-toe rolling pattern during walking.

PURPOSE: Humans are amongst few animals that step first on the heel, and then roll on the ball of the foot and toes. While this heel-to-toe rolling pattern has been shown to render an energetic advantage during walking, the effect of different foot contact strategies, on the neuromuscular control of adult walking gaits has received less attention. We hypothesised that deviating from heel-to-toe rolling pattern affects the energy transduction and weight acceptance and re-propulsive phases in gait along with the modification of spinal motor activity. METHODS: Ten subjects walked on a treadmill normally, then placed their feet flat on the ground at each step and finally walked on the balls of the feet. RESULTS: Our results show that when participants deviate from heel-to-toe rolling pattern strategy, the mechanical work increases on average 85% higher (F = 15.5; p < 0.001), mainly linked to a lack of propulsion at late stance. This modification of the mechanical power is related to a differential involvement of lumbar and sacral segment activation. Particularly, the delay between the major bursts of activation is on average 65% smaller, as compared to normal walking (F = 43.2; p < 0.001). CONCLUSION: Similar results are observable in walking plantigrade animals, but also at the onset of independent stepping in toddlers, where the heel-to-toe rolling pattern is not yet established. These indications seem to bring arguments to the fact that the rolling of the foot during human locomotion has evolved to optimise gait, following selective pressures from the evolution of bipedal posture.

The effects of age and central field loss on maintaining balance control when stepping up to a new level under time-pressure.

Objective: To investigate the effects of age and central field loss on the landing mechanics and balance control when stepping up to a new level under time-pressure. Methods: Eight older individuals with age-related macular degeneration (AMD), eight visually normal older and eight visually normal younger individuals negotiated a floor-based obstacle followed by a 'step-up to a new level' task. The task was performed under (1) no-pressure; (2) time-pressure: an intermittent tone was played that increased in frequency and participants had to complete the task before the tone ceased. Landing mechanics and balance control for the step-up task was assessed with a floor-mounted force plate on the step. Results: Increased ground reaction forces and loading rates were observed under time-pressure for young and older visual normals but not for AMD participants. Across conditions, loading rates and ground reaction forces were higher in young normals compared to older normals and AMD participants. Young visual normals also demonstrated 35-39% shorter double support times prior to and during the step-up compared to older normals and AMD participants. All groups shortened their double support times (31-40%) and single support times (7-9%) in the time-pressure compared to no-pressure condition. Regarding balance control, the centre-of-pressure displacement and velocity in the anterior-poster direction were increased under time-pressure for young and older visual normals but not for AMD participants. The centre-of-pressure displacement and velocity in the medial-lateral direction were decreased for the AMD participants under time-pressure but not for young and older visual normals. Conclusions: Despite walking faster, AMD participants did not adapt their landing mechanics under time-pressure (i.e., they remained more cautious), whilst older and young adults with normal vision demonstrated more forceful landing mechanics with the young being most forceful. A more controlled landing might be a safety strategy to maintain balance control during the step-up, especially in time-pressure conditions when balance control in the anterior-posterior direction is more challenged.

Avoidance behaviours while circumventing to the left or right of someone with different shoulder widths and facing directions: How do side, width, or orientation matter?

BACKGROUND: Collision avoidance during locomotion is influenced by a variety of situational factors. When circumventing around an inanimate object, the amount of clearance is dependent on the side of avoidance. When avoiding other pedestrians, individuals most often choose to walk behind a moving pedestrian, and avoid people differently depending on their body size. However, side of avoidance has not been evaluated with human obstacles, nor facing direction of a stationary pedestrian, nor the size of a single pedestrian. Therefore, the aim of this study is to evaluate these knowledge gaps concurrently. RESEARCH QUESTION: How do people avoid a collision to the left-side or right-side of a single stationary pedestrian (interferer) of varying shoulder width and orientation? METHODS: Participants (n = 11) walked along a 10 m pathway towards a goal, while a stationary interferer stood 6.5 m from the start. The interferer faced one of three directions relative to the participant (orientation); forward, leftward, or rightward, with either their normal shoulder width or enlarged width created by wearing football shoulder pads. Participants were explicitly instructed as to which side of the interferer to avoid (forced-left vs forced-right). Each participant completed 32 randomized avoidance trials. Centre of Mass separation at the time of crossing was used to examine individual's avoidance behaviours. RESULTS: Results revealed no effect of interferer width, but a significant side of avoidance effect, where the centre of mass separation between the participant and interferer at the time of crossing was smallest when participants avoided to their left. SIGNIFICANCE: Findings suggest that changing the facing direction or artificially increasing the shoulder width of a stationary interferer will not affect one's avoidance behaviours. However, an asymmetry in side of avoidance is maintained similar to that observed in obstacle avoidance behaviours.

Validation of Inertial Sensors to Evaluate Gait Stability.

The portability of wearable inertial sensors makes them particularly suitable for measuring gait in real-world walking situations. However, it is unclear how well inertial sensors can measure and evaluate gait stability compared to traditional laboratory-based optical motion capture. This study investigated whether an inertial sensor-based motion-capture suit could accurately assess gait stability. Healthy adult participants were asked to walk normally, with eyes closed, with approximately twice their normal step width, and in tandem. Their motion was simultaneously measured by inertial measurement units (IMU) and optical motion capture (Optical). Gait stability was assessed by calculating the margin of stability (MoS), short-term Lyapunov exponents, and step variability, along with basic gait parameters, using each system. We found that IMUs were able to detect the same differences among conditions as Optical for all but one of the measures. Bland-Altman and intraclass correlation (ICC) analysis demonstrated that mediolateral parameters (step width and mediolateral MoS) were measured less accurately by IMUs compared to their anterior-posterior equivalents (step length and anterior-posterior MoS). Our results demonstrate that IMUs can be used to evaluate gait stability through detecting changes in stability-related measures, but that the magnitudes of these measures might not be accurate or reliable, especially in the mediolateral direction.

Multi-tasking deteriorates trunk movement control during and after obstacle avoidance.

Dynamic and cognitive multi-tasking might affect balance and walking negatively and increase risk of falling. Trunk movement control is critical for balance maintenance and fall-prevention. The impact of multi-tasking on trunk movement control has not been thoroughly studied. In a challenging dynamic multi-tasking condition such as walking and obstacle avoidance, presence of a cognitive task not only increases risk of tripping but also may increase risk of falling by deteriorating trunk control. Our objective was to investigate the impacts of a challenging dynamic and cognitive multi-tasking condition (walking + obstacle avoidance + cognitive task) on trunk kinematics and kinetics and compare those with other joints/segments. Trunk, pelvis, hip, knee, and ankle kinematics and kinetics of 12 young adults were compared between joints/segments and conditions. During walking and obstacle avoidance (dynamic multi-tasking), the trunk had the largest normalized increase in peak flexion angle and extension torque compared to walking, among the other joints/segments. The presence of a cognitive task during walking and obstacle avoidance (dynamic and cognitive multi-tasking) did not impact any of the joints/segments biomechanics except the trunk peak extension torque that was increased. Furthermore, trunk kinematics showed the largest residual differences (post-effects) in 3 cycles after obstacle avoidance compared to walking. The presence of a cognitive task (dynamic and cognitive multi-tasking) did not impact the post-effects of obstacle avoidance on any joints/segments except the trunk with its residual difference from normal walking further increased. These results suggest that a cognitive task deteriorates trunk control and interferes with the ability to regain normal trunk biomechanics after obstacle avoidance. In summary, the trunk requires the largest biomechanical adjustments in a challenging dynamic and cognitive multi-tasking condition where there is a risk of falling. Our study provides baseline results suggesting that trunk control demands more attention and is more negatively affected by dynamic and cognitive multi-tasking. Our results raise a concern for elderly population as their trunk control is already impaired and common daily multi-tasking could further deteriorate their trunk control and increase fall risk.

Complexity of locomotion activities in an outside-of-the-lab wearable motion capture dataset.

Gait complexity is widely used to understand risk factors for injury, rehabilitation, the performance of assistive devices, and other matters of clinical interest. We analyze the complexity of out-of-the-lab locomotion activities via measures that have previously been used in gait analysis literature, as well as measures from other domains of data analysis. We categorize these broadly as quantifying either the intrinsic dimensionality, the variability, or the regularity, periodicity, or self-similarity of the data from a nonlinear dynamical systems perspective. We perform this analysis on a novel full-body motion capture dataset collected in out-of-the-lab conditions for a variety of indoor environments. This is a unique dataset with a large amount (over 24 h total) of data from participants behaving without low-level instructions in out-of-the-lab indoor environments. We show that reasonable complexity measures can yield surprising, and even profoundly contradictory, results. We suggest that future complexity analysis can use these guidelines to be more specific and intentional about what aspect of complexity a quantitative measure expresses. This will become more important as wearable motion capture technology increasingly allows for comparison of ecologically relevant behavior with lab-based measurements.

When running is easier than walking: effects of experience and gait on human obstacle traversal in virtual reality.

Humans readily traverse obstacles irrespective of whether they walk or run, despite strong differences between these gaits. Assuming that the control of human obstacle traversal may be either gait-specific or gait-independent, the present study investigates whether previous experience in an obstacle traversal task transfers between the two gaits, and, if this was the case, whether transfer worked both ways. To this end, we conducted a within-group comparison of kinematic adjustments during human obstacle traversal in both walking and running, with distinct participant groups for the two gait sequences. Participants (n = 12/12 (f/m), avg. 25 yo) were motion captured as they traversed obstacles at walking and running speeds on a treadmill, surrounded by an immersive virtual reality (VR) environment. We find that kinematics recorded in our VR setup are consistent with that obtained in real-world experiments. Comparison of learning curves reveals that participants are able to utilize previous experience and transfer learned adjustments from one gait to another. However, this transfer is not symmetrical, with previous experience during running leading to increased success rate in walking, but not the other way round. From a range of step parameters we identified lacking toe height of the trailing leg as the main cause for this asymmetry.