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Correspondence to Dr Benno M Nigg, Human Performance Laboratory, Faculty of Kinesiology, University of Calgary, Calgary, AB T2L 1N4, Canada; nigg@ucalgary.ca The effect of shoe mid-sole construction on running performance was discussed with reference to the Nike Vaporfly 4%.1 Drs Burns and Tam described the mid-sole thickness as the major running shoe characteristic that contributes to changes in performance. [...]the results of the leg model (representative of average-level runners) correlated with the results of the field tests. [...]it appears inappropriate to regulate one specific footwear feature before understanding where these performance advantages originated from.7 However, our current knowledge suggests that, compared with the teeter-totter effect, all other shoe characteristic contributions to performance are small and negligible.

To date it has been thought that shoe midsole hardness does not affect vertical impact peak forces during running. This conclusion is based partially on results from experimental data using homogeneous samples of participants that found no difference in vertical impact peaks when running in shoes with different midsole properties. However, it is currently unknown how apparent joint stiffness is affected by shoe midsole hardness. An increase in apparent joint stiffness could result in a harder landing, which should result in increased vertical impact peaks during running. The purpose of this study was to quantify the effect of shoe midsole hardness on apparent ankle and knee joint stiffness and the associated vertical ground reaction force for age and sex subgroups during heel-toe running. 93 runners (male and female) aged 16-75 years ran at 3.33 ± 0.15 m/s on a 30 m-long runway with soft, medium and hard midsole shoes. The vertical impact peak increased as the shoe midsole hardness decreased (mean(SE); soft: 1.70BW(0.03), medium: 1.64BW(0.03), hard: 1.54BW(0.03)). Similar results were found for the apparent ankle joint stiffness where apparent stiffness increased as the shoe midsole hardness decreased (soft: 2.08BWm/º x 100 (0.05), medium: 1.92 BWm/º x 100 (0.05), hard: 1.85 BWm/º x 100 (0.05)). Apparent knee joint stiffness increased for soft (1.06BWm/º x 100 (0.04)) midsole compared to the medium (0.95BWm/º x 100 (0.04)) and hard (0.96BWm/º x 100 (0.04)) midsoles for female participants. The results from this study confirm that shoe midsole hardness can have an effect on vertical impact force peaks and that this may be connected to the hardness of the landing. The results from this study may provide useful information regarding the development of cushioning guidelines for running shoes.

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.

Human gait is as unique to an individual as is their fingerprint. It remains unknown, however, what gait characteristics differentiate well between individuals that could define the uniqueness of human gait. The purpose of this work was to determine the gait characteristics that were most relevant for a neural network to identify individuals based on their running patterns. An artificial neural network was trained to recognize kinetic and kinematic movement trajectories of overground running from 50 healthy novice runners (males and females). Using layer-wise relevance propagation, the contribution of each variable to the classification result of the neural network was determined. It was found that gait characteristics of the coronal and transverse plane as well as medio-lateral ground reaction forces provided more information for subject identification than gait characteristics of the sagittal plane and ground reaction forces in vertical or anterior-posterior direction. Additionally, gait characteristics during the early stance were more relevant for gait recognition than those of the mid and late stance phase. It was concluded that the uniqueness of human gait is predominantly encoded in movements of the coronal and transverse plane during early stance.

Skating is a fundamental movement in ice hockey; however little research has been conducted within the field of hockey skating biomechanics due to the difficulties of on-ice data collection. In this study a novel on-ice measurement approach was tested for reliability, and subsequently implemented to investigate the forward skating technique, as well as technique differences across skill levels. Nine high caliber (High) and nine low caliber (Low) hockey players performed 30 m forward skating trials. A 3D accelerometer was mounted to the right skate for the purpose of stride detection, with the 2nd and 6th strides defined as acceleration and steady-state, respectively. The activity of five lower extremity muscles was recorded using surface electromyography. Biaxial electro-goniometers were used to quantify hip and knee angles, and in-skate plantar force was measured using instrumented insoles. Reliability was assessed with the coefficient of multiple correlation, which demonstrated moderate (r>0.65) to excellent (r>0.95) scores across selected measured variables. Greater plantar-flexor muscle activity and hip extension were evident during acceleration strides, while steady state strides exhibited greater knee extensor activity and hip abduction range of motion (p<0.05). High caliber exhibited greater hip range of motion and forefoot force application (p<0.05). The successful implementation of this on-ice mobile measurement approach offers potential for athlete monitoring, biofeedback and training advice.

In recent years, increasing the midsole bending stiffness (MBS) of running shoes by embedding carbon fibre plates in the midsole resulted in many world records set during long-distance running competitions. Although several theories were introduced to unravel the mechanisms behind these performance benefits, no definitive explanation was provided so far. This study aimed to investigate how the function of the gastrocnemius medialis (GM) muscle and Achilles tendon is altered when running in shoes with increased MBS. Here, we provide the first direct evidence that the amount and velocity of GM muscle fascicle shortening is reduced when running with increased MBS. Compared to control, running in the stiffest condition at 90% of speed at lactate threshold resulted in less muscle fascicle shortening ( p  = 0.006, d  = 0.87), slower average shortening velocity ( p  = 0.002, d  = 0.93) and greater estimated Achilles tendon energy return ( p  ≤ 0.001, d  = 0.96), without a significant change in GM fascicle work ( p  = 0.335, d  = 0.40) or GM energy cost ( p  = 0.569, d  = 0.30). The findings of this study suggest that running in stiff shoes allows the ankle plantarflexor muscle–tendon unit to continue to operate on a more favourable position of the muscle’s force–length–velocity relationship by lowering muscle shortening velocity and increasing tendon energy return.

Postural control research describes ankle-, hip-, or multi-joint strategies as mechanisms to control upright posture. The objectives of this study were, first, development of an analysis technique facilitating a direct comparison of the structure of such multi-segment postural movement patterns between subjects; second, comparison of the complexity of postural movements between three stances of different difficulty levels; and third, investigation of between-subject differences in the structure of postural movements and of factors that may contribute to these differences. Twenty-nine subjects completed 100-s trials in bipedal (BP), tandem (TA) and one-leg stance (OL). Their postural movements were recorded using 28 reflective markers distributed over all body segments. These marker coordinates were interpreted as 84-dimensional posture vectors, normalized, concatenated from all subjects, and submitted to a principal component analysis (PCA) to extract principal movement components (PMs). The PMs were characterized by determining their relative contribution to the subject's entire postural movements and the smoothness of their time series. Four, eight, and nine PM were needed to represent 90% of the total variance in BP, TA, and OL, respectively, suggesting that increased task difficulty is associated with increased complexity of the movement structure. Different subjects utilized different combinations of PMs to control their posture. In several PMs, the relative contribution of a PM to a subject's overall postural movements correlated with the smoothness of the PM's time series, suggesting that utilization of specific postural PMs may depend on the subject's ability to control the PM's temporal evolution.

Studies on the paradigm of the preferred movement path are scarce, and as a result, many aspects of the paradigm remain elusive. It remains unknown, for instance, how muscle activity adapts when differences in joint kinematics, due to altered running conditions, are of low / high magnitudes. Therefore, the purpose of this work was to investigate changes in muscle activity of the lower extremities in runners with minimal ([less than or equal to] 3°) or substantial (> 3°) mean absolute differences in the ankle and knee joint angle trajectories when subjected to different running footwear. Mean absolute differences in the integral of the muscle activity were quantified for the tibialis anterior (TA), peroneus longus (PL), gastrocnemius medialis (GM), soleus (SO), vastus lateralis (VL), and biceps femoris (BF) muscles during over ground running. In runners with minimal changes in 3D joint angle trajectories ([less than or equal to] 3°), muscle activity was found to change drastically when comparing barefoot to shod running (TA: 35%; PL: 11%; GM: 17%; SO: 10%; VL: 27%; BF: 16%), and minimally when comparing shod to shod running (TA: 10%; PL: 9%; GM: 13%; SO: 8%; VL: 8%; BF: 12%). For runners who showed substantial changes in joint angle trajectories (> 3°), muscle activity changed drastically in barefoot to shod comparisons (TA: 39%; PL: 14%; GM: 16%; SO: 16%; VL: 25%; BF: 24%). It was concluded that a movement path can be maintained with small adaptations in muscle activation when running conditions are similar, while large adaptations in muscle activation are needed when running conditions are substantially different.

Placing a stronger focus on subject-specific responses to footwear may lead to a better functional understanding of footwear’s effect on running and its influence on comfort perception, performance, and pathogenesis of injuries. We investigated subject-specific responses to different footwear conditions within ground reaction force (GRF) data during running using a machine learning-based approach. We conducted our investigation in three steps, guided by the following hypotheses: (I) For each subject x footwear combination, unique GRF patterns can be identified. (II) For each subject, unique GRF characteristics can be identified across footwear conditions. (III) For each footwear condition, unique GRF characteristics can be identified across subjects. Thirty male subjects ran ten times at their preferred (self-selected) speed on a level and approximately 15 m long runway in four footwear conditions (barefoot and three standardised running shoes). We recorded three-dimensional GRFs for one right-foot stance phase per running trial and classified the GRFs using support vector machines. The highest median prediction accuracy of 96.2% was found for the subject x footwear classification (hypothesis I). Across footwear conditions, subjects could be discriminated with a median prediction accuracy of 80.0%. Across subjects, footwear conditions could be discriminated with a median prediction accuracy of 87.8%. Our results suggest that, during running, responses to footwear are unique to each subject and footwear design. As a result, considering subject-specific responses can contribute to a more differentiated functional understanding of footwear effects. Incorporating holistic analyses of biomechanical data is auspicious for the evaluation of (subject-specific) footwear effects, as unique interactions between subjects and footwear manifest in versatile ways. The applied machine learning methods have demonstrated their great potential to fathom subject-specific responses when evaluating and recommending footwear.

Treadmill running is a common method of exercise and to study human locomotion. Research has examined the kinematics and kinetics of overground and treadmill running, but there has been less focus on the levels of muscle activity during treadmill running. We investigated if muscle activity is different while running overground compared to running on a variety of treadmills. A total of 11 healthy individuals ran at 3 speeds (2.6, 3.6, 4.5 m/s) under 4 different running conditions (3 treadmills, overground). The three treadmills included a typical home exercise treadmill, a midsize commercial research treadmill, and a large, instrumented research treadmill. Surface EMG of the tibialis anterior (TA), gastrocnemius medialis (GM), rectus femoris (RF) and biceps femoris (BF) muscles were measured for each running condition. The integrated EMG was computed for each running condition for the stance and swing phase, as well as 100 ms before and after the heel-strike. Friedman analysis revealed significant effects during the stance phase for GM and RF at all speeds, such that muscle activation was lower on the treadmills relative to overground. During the stance phase at faster speeds, the muscle activity was higher for the TA and lower for the BF while running on the different treadmills compared to overground running. Before heel-strike, the TA was significantly less active during treadmill compared to overground running at 2.6 m/s and the RF showed significantly higher activity at 3.6 m/s and 4.5 m/s while running on the different treadmills. Summarizing, differences were mainly observed between the different treadmill conditions relative to overground running. Muscle activation differences between the different treadmill conditions were observed at faster running speeds for RF during the pre-heel-strike phase only. Different types of treadmills with different mechanical properties affects the muscle activity during stance phase as well as in preparation to heel-strike. Additionally, the muscle activity is greater during overground compared to treadmill running during the stance phase for the GM, BF, and RF.