Greater foot and footwear mechanical work associated with less ankle joint work during running.

Footwear energy storage and return is often suggested as one explanation for metabolic energy savings when running in Advanced Athletic Footwear. However, there is no common understanding of how footwear energy storage and return facilitates changes in muscle and joint kinetics. The purpose of this study was to evaluate the magnitude and timing of foot, footwear and lower limb joint powers and work while running in Advanced and Traditional Athletic Footwear. Fifteen runners participated in an overground motion analysis study. Since footwear kinetics are methodologically challenging to quantify, we leveraged distal rearfoot power analyses ('foot + footwear' power) and evaluated changes in the magnitude and timing of foot + footwear power and lower limb joint powers. Running in Advanced Footwear resulted in greater foot + footwear work, compared to Traditional Shoes, and lower positive ankle work, potentially reducing the muscular demand on the runner. The timing of foot + footwear power varied only slightly across footwear. There are exciting innovation opportunities to manipulate the timing of footwear energy and return. This study demonstrates the research value of quantifying time-series foot + footwear power, and points industry developers towards footwear innovation opportunities.

Evaluating wrapping alpine ski boots during on-snow carving.

Introduction: Alpine ski boots enable rapid and precise force transfer between skier and ski while carving. These boots are made of rigid plastic and fit tightly commonly through four buckles. Such a fit can improve speed and control but also pain and discomfort. In athletic footwear, alterations to the upper designed to wrap the foot improve performance during rapid changes of direction and during trail running. The purpose of this study was to systematically evaluate the performance and fit of two different ski boot shell closure mechanisms: a BOA closure and a Buckle closure. Materials and methods: This was a two-part study with 22 subjects performing on-mountain skiing and 10 of those subjects completing an in-laboratory pressure evaluation. Subjects skied in both boots three times each while data from inertial measurement units (IMUs) and plantar pressures were collected along with subjective data. In lab, static dorsal and plantar pressures were collected while the subjects flexed into the boots. Results: The BOA boots improved subjective and objective ski performance; qualitative carving scores were greater, likely through increasing the amount of normal force applied to the ski while turning. There were no differences in edge angles between the boots, as computed from IMUs. The BOA boot also reduced static peak plantar pressures in the rearfoot along with reducing overall static pressure on the dorsum as compared with the Buckle boot. Conclusions: This is the first study to systematically evaluate differences in ski boot closures. The improvements in carving performance in the BOA boot are supported by distinct differences in pressure distribution within each boot, which we speculate contributed to improved performance by reducing discomfort or pain while still facilitating effective force transfer.

Evaluation of Different Pressure-Based Foot Contact Event Detection Algorithms across Different Slopes and Speeds.

If validated, in-shoe pressure measuring technology allows for the field-based quantification of running gait, including kinematic and kinetic measures. Different algorithmic methods have been proposed to determine foot contact events from in-shoe pressure insole systems, however, these methods have not been evaluated for accuracy, reliability against a gold standard using running data across different slopes, and speeds. Using data from a plantar pressure measurement system, seven different foot contact event detection algorithms based on pressure signals (pressure sum) were compared to vertical ground reaction force data collected from a force instrumented treadmill. Subjects ran on level ground at 2.6, 3.0, 3.4, and 3.8 m/s, six degrees (10.5%) inclined at 2.6, 2.8, and 3.0 m/s, and six degrees declined at 2.6, 2.8, 3.0, and 3.4 m/s. The best performing foot contact event detection algorithm showed maximal mean absolute errors of only 1.0 ms and 5.2 ms for foot contact and foot off, respectively, on level grade, when compared to a 40 N ascending and descending force threshold from the force treadmill data. Additionally, this algorithm was unaffected by grade and had similar levels of errors across all grades.

A foot and footwear mechanical power theoretical framework: Towards understanding energy storage and return in running footwear.

There is extreme interest surrounding the influence of advanced running footwear on running performance. The magnitude, timing, and location of mechanical energy storage and return in footwear may elucidate one way footwear influences running performance. However, the complexity of footwear makes it challenging to model footwear energy storage and return during running. The purpose of this study was to develop a practical framework for evaluating foot and footwear mechanical power profiles during running. First, a unified deformable power analysis (distal rearfoot power) was used to quantify mechanical power of the foot + footwear system. Then, qualitative mechanical power profiles of individual foot and footwear structure were developed using prior literature, benchtop footwear material properties, and experimental kinetics and kinematics. The result is a framework for understanding foot and footwear mechanical power during running using a two-stage analysis. First, foot + footwear power can be experimentally compared when running in various footwear constructions. Second, the developed framework can provide qualitative insights into which foot and footwear structures may contribute to differences in measured foot + footwear power. To highlight the utility of this framework, the timing, magnitude, and location of foot + footwear power is compared when running in different footwear constructions and with different running styles. The framework developed here provides a practical tool for footwear developers and researchers to gain intuition about the timing, relative magnitude, and location of energy storage and return from footwear during running. There are opportunities to expand on this framework to further connect footwear construction to running performance.

Estimating Running Ground Reaction Forces from Plantar Pressure during Graded Running.

Ground reaction forces (GRFs) describe how runners interact with their surroundings and provide the basis for computing inverse dynamics. Wearable technology can predict time-continuous GRFs during walking and running; however, the majority of GRF predictions examine level ground locomotion. The purpose of this manuscript was to predict vertical and anterior-posterior GRFs across different speeds and slopes. Eighteen recreationally active subjects ran on an instrumented treadmill while we collected GRFs and plantar pressure. Subjects ran on level ground at 2.6, 3.0, 3.4, and 3.8 m/s, six degrees inclined at 2.6, 2.8, and 3.0 m/s, and six degrees declined at 2.6, 2.8, 3.0, and 3.4 m/s. We estimated GRFs using a set of linear models and a recurrent neural network, which used speed, slope, and plantar pressure as inputs. We also tested eliminating speed and slope as inputs. The recurrent neural network outperformed the linear model across all conditions, especially with the prediction of anterior-posterior GRFs. Eliminating speed and slope as model inputs had little effect on performance. We also demonstrate that subject-specific model training can reduce errors from 8% to 3%. With such low errors, researchers can use these wearable-based GRFs to understand running performance or injuries in real-world settings.

Changes in ankle work, foot work, and tibialis anterior activation throughout a long run.

BACKGROUND: The ankle and foot together contribute to over half of the positive and negative work performed by the lower limbs during running. Yet, little is known about how foot kinetics change throughout a run. The amount of negative foot work may decrease as tibialis anterior (TA) electromyography (EMG) changes throughout longer-duration runs. Therefore, we examined ankle and foot work as well as TA EMG changes throughout a changing-speed run. METHODS: Fourteen heel-striking subjects ran on a treadmill for 58 min. We collected ground reaction forces, motion capture, and EMG. Subjects ran at 110%, 100%, and 90% of their 10-km running speed and 2.8 m/s multiple times throughout the run. Foot work was evaluated using the distal rearfoot work, which provides a net estimate of all work contributors within the foot. RESULTS: Positive foot work increased and positive ankle work decreased throughout the run at all speeds. At the 110% 10-km running speed, negative foot work decreased and TA EMG frequency shifted lower throughout the run. The increase in positive foot work may be attributed to increased foot joint work performed by intrinsic foot muscles. Changes in negative foot work and TA EMG frequency may indicate that the TA plays a role in negative foot work in the early stance of a run. CONCLUSION: This study is the first to examine how the kinetic contributions of the foot change throughout a run. Future studies should investigate how increases in foot work affect running performance.

Evaluating footwear "in the wild": Examining wrap and lace trail shoe closures during trail running.

Trail running participation has grown over the last two decades. As a result, there have been an increasing number of studies examining the sport. Despite these increases, there is a lack of understanding regarding the effects of footwear on trail running biomechanics in ecologically valid conditions. The purpose of our study was to evaluate how a Wrap vs. Lace closure (on the same shoe) impacts running biomechanics on a trail. Thirty subjects ran a trail loop in each shoe while wearing a global positioning system (GPS) watch, heart rate monitor, inertial measurement units (IMUs), and plantar pressure insoles. The Wrap closure reduced peak foot eversion velocity (measured via IMU), which has been associated with fit. The Wrap closure also increased heel contact area, which is also associated with fit. This increase may be associated with the subjective preference for the Wrap. Lastly, runners had a small but significant increase in running speed in the Wrap shoe with no differences in heart rate nor subjective exertion. In total, the Wrap closure fit better than the Lace closure on a variety of terrain. This study demonstrates the feasibility of detecting meaningful biomechanical differences between footwear features in the wild using statistical tools and study design. Evaluating footwear in ecologically valid environments often creates additional variance in the data. This variance should not be treated as noise; instead, it is critical to capture this additional variance and challenges of ecologically valid terrain if we hope to use biomechanics to impact the development of new products.

The effects of shoe upper construction on mechanical ankle joint work during lateral shuffle movements.

Lateral shuffles are common movements in sports and are facilitated by the hip, knee, and ankle joints. Shoe uppers can change ankle kinetics during walking and running. However, it is not known how shoe upper modifications affect ankle kinetics during shuffling. The purpose of this study was to investigate the effects of shoe upper construction on mechanical ankle joint work during shuffling. It was hypothesized that a shoe with a reinforced upper will result in decreased negative ankle joint work. Twenty participants performed Maximal (MLST) and Submaximal Lateral Shuffle Tests (90% of MLST) in footwear with a minimal (MU) and reinforced upper (RU). Ground reaction forces and ankle kinematics were collected to compute ankle joint work. Performing lateral shuffles in the RU condition resulted in significantly reduced positive (MU: 0.62 ± 0.16 J/kg, RU: 0.55 ± 0.16 J/kg; p = 0.001, d = 0.44) and negative (MU: -0.60 ± 0.20 J/kg, RU: -0.53 ± 0.19 J/kg; p = 0.004, d = 0.41) ankle work. A decrease in positive and negative work could be a performance benefit, enabling the athlete to perform the same movement with a lower energy cost. More extreme upper interventions may yield even larger performance benefits.

Timing of gait events affects whole trajectory analyses: A statistical parametric mapping sensitivity analysis of lower limb biomechanics.

Time continuous analyses, such as statistical parametric mapping (SPM), have been increasingly used in biomechanics research to determine differences between populations, interventions and methodologies. Currently, it is not known how sensitive time-continuous analyses are to timing variability that occur in gait data. We evaluated this sensitivity by examining the frequency of significant SPM outcomes between two walking speeds when lower limb kinematics and kinetics were segmented and aligned based on 40 repeatable gait events. These events, defined in the supplementary material, include a commonly used event like foot contact and other events that have been previously demonstrated to be repeatable. Repeatable gait events were determined from joint and segment kinematics, joint kinetics as well as ground reaction forces. We examined the frequency of statistical outcomes for a single subject with different numbers of strides analyzed and for a cohort of 10 subjects. Our findings demonstrate that gait interventions, such as changes in walking speed, can induce temporal shifts that affect time-continuous outcomes for both cohort- and subject-level analyses. As both timing and magnitude are important in gait data, researchers are encouraged to perform additional analyses to understand how both of these variables affect time-continuous analysis outcomes. Finally, we demonstrate that multiple SPM tests can be performed to determine if statistical outcomes are due to temporal shifting or differences in magnitude. It is important to understand how both timing and magnitude of biomechanical data influences time continuous analyses as these analyses inform injury prevention, device development and basic understanding of biomechanics.

Shoe feature recommendations for different running levels: A Delphi study.

Providing runners with footwear that match their functional needs has the potential to improve footwear comfort, enhance running performance and reduce the risk of overuse injuries. It is currently not known how footwear experts make decisions about different shoe features and their properties for runners of different levels. We performed a Delphi study in order to understand: 1) definitions of different runner levels, 2) which footwear features are considered important and 3) how these features should be prescribed for runners of different levels. Experienced academics, journalists, coaches, bloggers and physicians that examine the effects of footwear on running were recruited to participate in three rounds of a Delphi study. Three runner level definitions were refined throughout this study based on expert feedback. Experts were also provided a list of 20 different footwear features. They were asked which features were important and what the properties of those features should be. Twenty-four experts, most with 10+ years of experience, completed all three rounds of this study. These experts came to a consensus for the characteristics of three different running levels. They indicated that 12 of the 20 footwear features initially proposed were important for footwear design. Of these 12 features, experts came to a consensus on how to apply five footwear feature properties for all three different running levels. These features were: upper breathability, forefoot bending stiffness, heel-to-toe drop, torsional bending stiffness and crash pad. Interestingly, the experts were not able to come to a consensus on one of the most researched footwear features, rearfoot midsole hardness. These recommendations can provide a starting point for further biomechanical studies, especially for features that are considered as important, but have not yet been examined experimentally.

Effects of toe length, foot arch length and toe joint axis on walking biomechanics.

Toe joint articulation has been shown to affect gait mechanics, as evidenced by walking simulations, biped robots, and foot prostheses. However, it is not known how parameters such as toe length, foot arch length (i.e., heel-to-toe-joint length) or toe joint axis angle affect human walking. We utilized a previously developed adjustable ankle-toe prosthesis to systematically examine these three foot parameters. We tested ten able-bodied persons walking on a force instrumented-treadmill while wearing a pair of adjustable prostheses attached bilaterally below simulator boots (which fixated their biological ankles). We collected motion and ground reaction force data to compute lower-limb kinematics and kinetics as well as COM power and work. We observed that increasing the foot arch length by 60 mm (35%) increased COM Push-off work by ~5 J, due to increased energy storage and return by the ankle spring. Increasing the toe length by 40 mm (80%) and changing the toe joint axis by ±9° from a neutral angle resulted in negligible effects on COM mechanics and lower limb kinetics. This study provides further insights regarding toe joint function; knowledge which may benefit the design/integration of toe joints into prostheses, exoskeletons and legged robots.

Unholey shoes: Experimental considerations when estimating ankle joint complex power during walking and running.

For studies that aim to assess biological ankle function, calculating ankle joint complex (AJC) power between the calcaneus and shank is recommended over conventional inverse dynamics estimates between a rigid-body foot and shank. However, when designing a new experiment, it remains unclear whether holes should be cut in footwear to permit motion tracking via skin-mounted markers, or whether marker placement locations should be tightly controlled across conditions. Here we provide data to assist researchers in answering these questions. We performed a gait analysis study of walking (0.8, 1.2, 1.6 m·s-1) and running (2.6, 2.8, 3.0 m·s-1) while subjects (N = 10) wore custom-modified footwear, which allowed markers to be placed either on the shoe, or on the skin via cut-out windows in the shoes. First, we compared foot markers affixed to the skin vs. on the same locations on the shoe. Using statistical non-parametric mapping techniques, we discovered that skin vs. shoe markers had no statistically significant effect on net AJC power estimates throughout stance phase, for all walking and running speeds. Second, we compared calcaneal markers in the nominal shoe configuration vs. markers in a nearby location (∼27 mm below) on the shoe. We observed significant differences when marker placement on the shoe was varied, which may be relevant to repeated-measures study designs. The results suggest that when computing AJC power for walking and running, you may want to put down the scissors (i.e., forego cutting holes in your footwear), and instead pick up a Sharpie® (pen) or use a template, to maintain consistent marker placement across trials and conditions.

Foot and shoe responsible for majority of soft tissue work in early stance of walking.

Soft tissues located throughout the human body are known to perform substantial mechanical work through wobbling and deforming, particularly following foot impacts with the ground. Yet, it is not known which specific tissues in the body are responsible for the majority of the soft tissue work. The purpose of this study was to quantify how much of the soft tissue work after foot contact was due to the foot and shoe, vs. from tissues elsewhere in the body, and how this distribution of work changed with walking speed and slope. We collected ground reaction forces and whole-body kinematics while ten subjects walked at five speeds (0.8-1.6 m/s) and on seven different slopes (9 degrees downhill to 9 degrees uphill). Using a previously-published Energy-Accounting analysis, we found that the majority of the soft tissue work during early stance was due to deformation of the foot and shoe. The percentage of work did not vary significantly with speed but did vary significantly with slope. The foot and shoe were responsible for ∼60-70% of the soft tissue work during level and uphill walking, and 80-90% during downhill walking.

Effect of toe joint stiffness and toe shape on walking biomechanics.

During typical human walking, the metatarsophalangeal joints undergo extension/flexion, which we term toe joint articulation. This toe joint articulation impacts locomotor performance, as evidenced by prior studies on prostheses, footwear, sports and humanoid robots. However, a knowledge gap exists in our understanding of how individual toe properties (e.g. shape, joint stiffness) affect bipedal locomotion. To address this gap, we designed and built a pair of adjustable foot prostheses that enabled us to independently vary different toe properties, across a broad range of physiological and non-physiological values. We then characterized the effects of varying toe joint stiffness across a range of different ankle joint stiffness conditions, and the effects of varying toe shape on walking biomechanics. Ten able-bodied individuals walked on a treadmill with prostheses mounted bilaterally underneath simulator boots (which immobilized their biological ankles). We collected motion capture and ground reaction force data, then computed joint kinematics and kinetics, and center-of-mass (COM) power and work. To our surprise, we found that varying toe joint stiffness affected COM Push-off dynamics during walking as much as, or in some cases even more than, varying ankle joint stiffness. Increasing toe joint stiffness increased COM Push-off work by up to 48% (6 J), and prosthetic anklefoot Push-off work by up to 181% (12 J). In contrast, large changes in toe shape had little effect on gait. This study brings attention to the toes, an aspect of prosthetic and robotic foot design that is often overlooked or overshadowed by design of the ankle. Optimizing toe joint stiffness in assistive and robotic devices (e.g. prostheses, exoskeletons, robot feet) may provide a complementary means of enhancing Push-off or other aspects of locomotor performance, in conjunction with the more conventional approach of augmenting ankle dynamics. Future studies are needed to isolate the effects of additional toe properties (e.g. toe length).

Ankle and foot power in gait analysis: Implications for science, technology and clinical assessment.

In human gait analysis studies, the entire foot is typically modeled as a single rigid-body segment; however, this neglects power generated/absorbed within the foot. Here we show how treating the entire foot as a rigid body can lead to misunderstandings related to (biological and prosthetic) foot function, and distort our understanding of ankle and muscle-tendon dynamics. We overview various (unconventional) inverse dynamics methods for estimating foot power, partitioning ankle vs. foot contributions, and computing combined anklefoot power. We present two case study examples. The first exemplifies how modeling the foot as a single rigid-body segment causes us to overestimate (and overvalue) muscle-tendon power generated about the biological ankle (in this study by up to 77%), and to misestimate (and misinform on) foot contributions; corroborating findings from previous multi-segment foot modeling studies. The second case study involved an individual with transtibial amputation walking on 8 different prosthetic feet. The results exemplify how assuming a rigid foot can skew comparisons between biological and prosthetic limbs, and lead to incorrect conclusions when comparing different prostheses/interventions. Based on analytical derivations, empirical findings and prior literature we recommend against computing conventional ankle power (between shank-foot). Instead, we recommend using an alternative estimate of power generated about the ankle joint complex (between shank-calcaneus) in conjunction with an estimate of foot power (between calcaneus-ground); or using a combined anklefoot power calculation. We conclude that treating the entire foot as a rigid-body segment is often inappropriate and ill-advised. Including foot power in biomechanical gait analysis is necessary to enhance scientific conclusions, clinical evaluations and technology development.

Inferring Muscle-Tendon Unit Power from Ankle Joint Power during the Push-Off Phase of Human Walking: Insights from a Multiarticular EMG-Driven Model.

INTRODUCTION: Inverse dynamics joint kinetics are often used to infer contributions from underlying groups of muscle-tendon units (MTUs). However, such interpretations are confounded by multiarticular (multi-joint) musculature, which can cause inverse dynamics to over- or under-estimate net MTU power. Misestimation of MTU power could lead to incorrect scientific conclusions, or to empirical estimates that misguide musculoskeletal simulations, assistive device designs, or clinical interventions. The objective of this study was to investigate the degree to which ankle joint power overestimates net plantarflexor MTU power during the Push-off phase of walking, due to the behavior of the flexor digitorum and hallucis longus (FDHL)-multiarticular MTUs crossing the ankle and metatarsophalangeal (toe) joints. METHODS: We performed a gait analysis study on six healthy participants, recording ground reaction forces, kinematics, and electromyography (EMG). Empirical data were input into an EMG-driven musculoskeletal model to estimate ankle power. This model enabled us to parse contributions from mono- and multi-articular MTUs, and required only one scaling and one time delay factor for each subject and speed, which were solved for based on empirical data. Net plantarflexing MTU power was computed by the model and quantitatively compared to inverse dynamics ankle power. RESULTS: The EMG-driven model was able to reproduce inverse dynamics ankle power across a range of gait speeds (R2 ≥ 0.97), while also providing MTU-specific power estimates. We found that FDHL dynamics caused ankle power to slightly overestimate net plantarflexor MTU power, but only by ~2-7%. CONCLUSIONS: During Push-off, FDHL MTU dynamics do not substantially confound the inference of net plantarflexor MTU power from inverse dynamics ankle power. However, other methodological limitations may cause inverse dynamics to overestimate net MTU power; for instance, due to rigid-body foot assumptions. Moving forward, the EMG-driven modeling approach presented could be applied to understand other tasks or larger multiarticular MTUs.