Steep (30°) uphill walking vs. running: COM movements, stride kinematics, and leg muscle excitations

The effect of marathon running on the lower extremity kinematics and muscle activities during walking and running tasks

Patellofemoral pain syndrome (PFPS) is a common injury among runners, and it is thought that abnormal lower extremity biomechanics contribute to its development. However, the relationship between biomechanical changes after a marathon and PFPS injury remains limited. This study aims to investigate whether differences in knee and hip kinematics and lower extremity muscle activities exist in recreational runners before and after a marathon. Additionally, it aims to explore the relationship between these biomechanical changes and the development of PFPS injury. 12 recreational runners participated in the study. Kinematics and muscle activities of the lower extremity were recorded during walking (5 km/h) and running (10 km/h) tasks within 24 hours before and within 5 hours after a marathon. After the marathon, there was a significant decrease in peak knee flexion (walking: p = 0.006; running: p = 0.006) and an increase in peak hip internal rotation (walking: p = 0.026; running: p = 0.015) during the stance phase of both walking and running compared to before the marathon. The study demonstrates a decrease in knee flexion and an increase in hip internal rotation during the stance phase of gait tasks after completing a marathon, which may increase the risk of developing PFPS injury.

Acceleration-Based Estimation of Vertical Ground Reaction Forces during Running: A Comparison of Methods across Running Speeds, Surfaces, and Foot Strike Patterns

Twenty-seven methods of estimating vertical ground reaction force first peak, loading rate, second peak, average, and/or time series from a single wearable accelerometer worn on the shank or approximate center of mass during running were compared. Force estimation errors were quantified for 74 participants across different running surfaces, speeds, and foot strike angles and biases, repeatability coefficients, and limits of agreement were modeled with linear mixed effects to quantify the accuracy, reliability, and precision. Several methods accurately and reliably estimated the first peak and loading rate, however, none could do so precisely (the limits of agreement exceeded ±65% of target values). Thus, we do not recommend first peak or loading rate estimation from accelerometers with the methods currently available. In contrast, the second peak, average, and time series could all be estimated accurately, reliably, and precisely with several different methods. Of these, we recommend the 'Pogson' methods due to their accuracy, reliability, and precision as well as their stability across surfaces, speeds, and foot strike angles.

Relationship between biomechanics and energy cost in graded treadmill running

The objective of this study was to determine whether the relationships between energy cost of running (Cr) and running mechanics during downhill (DR), level (LR) and uphill (UR) running could be related to fitness level. Nineteen athletes performed four experimental tests on an instrumented treadmill: one maximal incremental test in LR, and three randomized running bouts at constant speed (10 km h^-1) in LR, UR and DR (± 10% slope). Gas exchange, heart rate and ground reaction forces were collected during steady-state. Subjects were split into two groups using the median Cr for all participants. Contact time, duty factor, and positive external work correlated with Cr during UR (all, p < 0.05), while none of the mechanical variables correlated with Cr during LR and DR. Mechanical differences between the two groups were observed in UR only: contact time and step length were higher in the economical than in the non-economical group (both p < 0.031). This study shows that longer stance duration during UR contributes to lower energy expenditure and Cr (i.e., running economy improvement), which opens the way to optimize specific running training programs.

A forefoot strike pattern during 18° uphill walking leads to greater ankle joint and plantar flexor loading

BACKGROUND

The ankle joint is one of the most involved joints in uphill walking. Furthermore, it is well known that toe walking increases the external dorsiflexion moment in the first half of stance during level walking. However, the effects of different foot-strike patterns on plantar flexor muscle forces, ankle joint forces, and other lower limb joint and muscle forces are unknown.

RESEARCH QUESTION

Do foot-strike patterns during 18° uphill walking affect lower limb sagittal joint angles and moments, as well as joint contact and muscle forces?

METHODS

This study was based on a data subset from previous publications, analysing uphill walking on an 18° ramp at a preset speed of 1.1 m/s in 18 male participants (34 limbs analyzed, 27 ± 5 years). Participants were divided into two groups based on their foot-strike pattern at initial contact: heel (HC) and forefoot (FC). Lower limb sagittal joint angles and moments as well as joint contact and muscle forces were assessed. Differences between the groups were assessed using two-sample t-tests.

RESULTS

FC showed increased soleus and gastrocnemius muscle forces as well as ankle joint forces during loading response and mid stance compared to HC. The soleus muscle force impulse was 51.1% higher in the FC group than in the HC group (p < 0.001). On the other hand, FC had a lower absolute centre of mass vertical displacement and reduced knee and hip joint, as well as iliopsoas and hamstring muscle force impulses.

SIGNIFICANCE

In terms of plantar flexor and ankle joint loading, it is advantageous to exhibit a heel strike pattern. The current results can be used to recommend foot-strike patterns for uphill walking, particularly in the presence or prevention of musculoskeletal issues.

Comparison of EMG Activity in Leg Muscles between Overground and Treadmill Running

INTRODUCTION

Treadmills have been widely used for training and performance testing during which the treadmill grade is usually set to 0%-2% grade. The purpose of our study was to compare the level of activation of lower body muscles when running at two speeds in an overground condition and on a treadmill at 0%, 1%, and 2% grades.

METHODS

We recorded EMG data of eight lower body muscles from 13 recreationally active individuals during overground and treadmill running at 2.92 and 4.58 m·s -1 . Maximal voluntary contraction (MVC) tests were performed (3 × 6 s) to identify maximal torque and EMG values. The stride cycles, from one foot strike to the next, were identified using a pair of triaxial accelerometers. A two-way repeated-measures ANOVA was used to examine the differences in EMG activity across running conditions and speeds. Cohen's d effect size was calculated to indicate the difference between the overground and the treadmill running conditions.

RESULTS

The effect sizes were moderate to negligible for differences between the EMG integral values for overground running and the three treadmill grades. The coefficient of variation for stride time during overground running was significantly larger than that of the treadmill running at 4.58 m·s -1 .

CONCLUSIONS

The results showed that the overall EMG profiles of the thigh and shank muscles were similar for the overground and treadmill conditions, but the similarity was greatest for thigh muscles when running on the treadmill at 1% grade and for shank muscles at 2% grade. The variability in stride time was greater during overground running than when running on a treadmill and was associated with elevated EMG activity of some muscles.

Humans trade off whole-body energy cost to avoid overburdening muscles while walking

Metabolic cost minimization is thought to underscore the neural control of locomotion. Yet, avoiding high muscle activation, a cause of fatigue, often outperforms energy minimization in computational predictions of human gait. Discerning the relative importance of these criteria in human walking has proved elusive, in part, because they have not been empirically decoupled. Here, we explicitly decouple whole-body metabolic cost and 'fatigue-like' muscle activation costs (estimated from electromyography) by pitting them against one another using two distinct gait tasks. When experiencing these competing costs, participants (n = 10) chose the task that avoided overburdening muscles (fatigue avoidance) at the expense of higher metabolic power (p < 0.05). Muscle volume-normalized activation more closely models energy use and was also minimized by the participants' decision (p < 0.05), demonstrating that muscle activation was, at best, an inaccurate signal for metabolic energy. Energy minimization was only observed when there was no adverse effect on muscle activation costs. By decoupling whole-body metabolic and muscle activation costs, we provide among the first empirical evidence of humans embracing non-energetic optimality in favour of a clearly defined neuromuscular objective. This finding indicates that local muscle fatigue and effort may well be key factors dictating human walking behaviour and its evolution.

Pole Walking Is Faster but Not Cheaper During Steep Uphill Walking

PURPOSE

The aim of this study was to compare pole walking (PW) and walking without poles (W) on a steep uphill mountain path (1.3 km, 433 m of elevation gain) at 2 different intensities: a maximal effort that would simulate a vertical kilometer intensity and a lower intensity (80% of maximal) simulating an ultratrail race.

METHODS

On the first day, we tested the participants in the laboratory to determine their maximal physiological parameters, respiratory compensation point, and gas exchange threshold. Then, they completed 4 uphill tests along a mountain path on 4 separate days, 2 at their maximum effort (PWmax and Wmax, randomized order) and 2 at 80% of the mean vertical velocity maintained during the first 2 trials (PW80 and W80, randomized order). We collected metabolic data, heart rate, blood lactate concentration, and rating of perceived exertion at the end of each trial. We also collected rating of perceived exertion at every 100 m of elevation gain during PW80 and W80.

RESULTS

Participants completed the maximal effort faster with poles versus without poles (18:51 [03:12] vs 19:19 [03:01] in min:s, P = .013, d = 0.08, small). Twelve of the 15 participants (80%) improved their performance when they used poles. During PW80 and W80, none of the physiological or biomechanical parameters were different.

CONCLUSION

In the examined condition, athletes should use poles during steep uphill maximal efforts to obtain the best performance. Conversely, during submaximal effort, the use of poles does not provide advantages in uphill PW.

Predicting continuous ground reaction forces from accelerometers during uphill and downhill running: a recurrent neural network solution

BACKGROUND

Ground reaction forces (GRFs) are important for understanding human movement, but their measurement is generally limited to a laboratory environment. Previous studies have used neural networks to predict GRF waveforms during running from wearable device data, but these predictions are limited to the stance phase of level-ground running. A method of predicting the normal (perpendicular to running surface) GRF waveform using wearable devices across a range of running speeds and slopes could allow researchers and clinicians to predict kinetic and kinematic variables outside the laboratory environment.

PURPOSE

We sought to develop a recurrent neural network capable of predicting continuous normal (perpendicular to surface) GRFs across a range of running speeds and slopes from accelerometer data.

METHODS

Nineteen subjects ran on a force-measuring treadmill at five slopes (0°, ±5°, ±10°) and three speeds (2.5, 3.33, 4.17 m/s) per slope with sacral- and shoe-mounted accelerometers. We then trained a recurrent neural network to predict normal GRF waveforms frame-by-frame. The predicted versus measured GRF waveforms had an average ± SD RMSE of 0.16 ± 0.04 BW and relative RMSE of 6.4 ± 1.5% across all conditions and subjects.

RESULTS

The recurrent neural network predicted continuous normal GRF waveforms across a range of running speeds and slopes with greater accuracy than neural networks implemented in previous studies. This approach may facilitate predictions of biomechanical variables outside the laboratory in near real-time and improves the accuracy of quantifying and monitoring external forces experienced by the body when running.

Does the preferred walk-run transition speed on steep inclines minimize energetic cost, heart rate or neither?

As walking speed increases, humans choose to transition to a running gait at their preferred transition speed (PTS). Near that speed, it becomes metabolically cheaper to run rather than to walk and that defines the energetically optimal transition speed (EOTS). Our goals were to determine: (1) how PTS and EOTS compare across a wide range of inclines and (2) whether the EOTS can be predicted by the heart rate optimal transition speed (HROTS). Ten healthy, high-caliber, male trail/mountain runners participated. On day 1, subjects completed 0 and 15 deg trials and on day 2, they completed 5 and 10 deg trials. We calculated PTS as the average of the walk-to-run transition speed (WRTS) and the run-to-walk transition speed (RWTS) determined with an incremental protocol. We calculated EOTS and HROTS from energetic cost and heart rate data for walking and running near the expected EOTS for each incline. The intersection of the walking and running linear regression equations defined EOTS and HROTS. We found that PTS, EOTS and HROTS all were slower on steeper inclines. PTS was slower than EOTS at 0, 5 and 10 deg, but the two converged at 15 deg. Across all inclines, PTS and EOTS were only moderately correlated. Although EOTS correlated with HROTS, EOTS was not predicted accurately by heart rate on an individual basis.