Comparison of Concurrent and Asynchronous Running Kinematics and Kinetics From Marker-Based and Markerless Motion Capture Under Varying Clothing Conditions.

As markerless motion capture is increasingly used to measure 3-dimensional human pose, it is important to understand how markerless results can be interpreted alongside historical marker-based data and how they are impacted by clothing. We compared concurrent running kinematics and kinetics between marker-based and markerless motion capture, and between 2 markerless clothing conditions. Thirty adults ran on an instrumented treadmill wearing motion capture clothing while concurrent marker-based and markerless data were recorded, and ran a second time wearing athletic clothing (shorts and t-shirt) while markerless data were recorded. Differences calculated between the concurrent signals from both systems, and also between each participant's mean signals from both asynchronous clothing conditions were summarized across all participants using root mean square differences. Most kinematic and kinetic signals were visually consistent between systems and markerless clothing conditions. Between systems, joint center positions differed by 3 cm or less, sagittal plane joint angles differed by 5° or less, and frontal and transverse plane angles differed by 5° to 10°. Joint moments differed by 0.3 N·m/kg or less between systems. Differences were sensitive to segment coordinate system definitions, highlighting the effects of these definitions when comparing against historical data or other motion capture modalities.

The Effects of a Simple Sensor Reorientation Procedure on Peak Tibial Accelerations during Running and Correlations with Ground Reaction Forces.

While some studies have found strong correlations between peak tibial accelerations (TAs) and early stance ground reaction forces (GRFs) during running, others have reported inconsistent results. One potential explanation for this is the lack of a standard orientation for the sensors used to collect TAs. Therefore, our aim was to test the effects of an established sensor reorientation method on peak Tas and their correlations with GRFs. Twenty-eight runners had TA and GRF data collected while they ran at a self-selected speed on an instrumented treadmill. Tibial accelerations were reoriented to a body-fixed frame using a simple calibration trial involving quiet standing and kicking. The results showed significant differences between raw and reoriented peak TAs (p < 0.01) for all directions except for the posterior (p = 0.48). The medial and lateral peaks were higher (+0.9-1.3 g), while the vertical and anterior were lower (-0.5-1.6 g) for reoriented vs. raw accelerations. Correlations with GRF measures were generally higher for reoriented TAs, although these differences were fairly small (Δr2 = 0.04-0.07) except for lateral peaks (Δr2 = 0.18). While contingent on the position of the IMU on the tibia used in our study, our results first showed systematic differences between reoriented and raw peak accelerations. However, we did not find major improvements in correlations with GRF measures for the reorientation method. This method may still hold promise for further investigation and development, given that consistent increases in correlations were found.

The Effect of Sensor Placement on Measured Distal Tibial Accelerations During Running.

Inertial measurement units (IMUs) attached to the distal tibia are a validated method of measuring lower-extremity impact accelerations, called tibial accelerations (TAs), in runners. However, no studies have investigated the effects of small errors in IMU placement, which would be expected in real-world, autonomous use of IMUs. The purpose of this study was to evaluate the effect of a small proximal shift in IMU location on mean TAs and relationships between TAs and ground reaction force loading rates. IMUs were strapped to 18 injury-free runners at a specified standard location (∼1 cm proximal to medial malleolus) and 2 cm proximal to the standard location. TAs and ground reaction forces were measured while participants ran at self-selected and 10% slower/faster speeds. Mean TA was lower at the standard versus proximal IMU location in the faster running condition (P = .026), but similar in the slower (P = .643) and self-selected conditions (P = .654). Mean TAs measured at the standard IMU explained more variation in ground reaction force loading rates (r2 = .79-.90; P < .001) compared with those measured at the proximal IMU (r2 = .65-.72; P < .001). These results suggest that careful attention should be given to IMU placement when measuring TAs during running.

Agreement Between Sagittal Foot and Tibia Angles During Running Derived From an Open-Source Markerless Motion Capture Platform and Manual Digitization.

Several open-source platforms for markerless motion capture offer the ability to track 2-dimensional (2D) kinematics using simple digital video cameras. We sought to establish the performance of one of these platforms, DeepLabCut. Eighty-four runners who had sagittal plane videos recorded of their left lower leg were included in the study. Data from 50 participants were used to train a deep neural network for 2D pose estimation of the foot and tibia segments. The trained model was used to process novel videos from 34 participants for continuous 2D coordinate data. Overall network accuracy was assessed using the train/test errors. Foot and tibia angles were calculated for 7 strides using manual digitization and markerless methods. Agreement was assessed with mean absolute differences and intraclass correlation coefficients. Bland-Altman plots and paired t tests were used to assess systematic bias. The train/test errors for the trained network were 2.87/7.79 pixels, respectively (0.5/1.2 cm). Compared to manual digitization, the markerless method was found to systematically overestimate foot angles and underestimate tibial angles (P < .01, d = 0.06-0.26). However, excellent agreement was found between the segment calculation methods, with mean differences ≤1° and intraclass correlation coefficients ≥.90. Overall, these results demonstrate that open-source, markerless methods are a promising new tool for analyzing human motion.

Reliability of wearable sensors to assess impact metrics during sport-specific tasks.

There is little information on the reliability of inertial measurement units for capturing impact load metrics during sport-specific movements. The purpose of this study is to determine the reliability of the Blue Trident IMU sensors in measuring impact load, step count and cumulative bone stimulus during a series of soccer-related tasks. Ten healthy recreational soccer players (age: 27.9 ± 2.18; height: 1.77 ± 0.10 m; mass: 79.02 ± 13.07 kg) volunteered for a 3-visit study and performed 4 tasks. Bilateral impact load, total number of steps and cumulative bone stimulus during the tasks were collected. Data were sampled using a dual-g sensor. Intraclass correlation coefficients (ICC3,1) with 95% confidence intervals assessed between-day reliability. Impact load (0.58-0.89) and cumulative bone stimulus (0.90-0.97) had good to excellent reliability across tasks. ICC values for right/left step count were good to excellent during acceleration-deceleration (0.728-0.837), change direction (0.734-0.955) and plant/cut manoeuvres (0.701-0.866) and fair to good during the ball kick (0.588-0.683). This suggests that wearable sensors can reliably measure the cumulative impact load during outdoor functional movements; however, kicking manoeuvres are less reliable. Measuring impact load in the field expands the ability to capture more ecologically valid data.

Quantifying Achievable Levels of Improvement in Knee Joint Biomechanics During Gait After Total Knee Arthroplasty Relative to Osteoarthritis Severity.

Total knee arthroplasty (TKA) surgery improves knee joint kinematics and kinetics during gait for most patients, but a lack of evidence exists for the level and incidence of improvement that is achieved. The objective of this study was to quantify patient-specific improvements in knee biomechanics relative to osteoarthritis (OA) severity levels. Seventy-two patients underwent 3-dimensional (3D) gait analysis before and 1 year after TKA surgery, as well as 72 asymptomatic adults and 72 with moderate knee OA. A combination of principal component analysis and discriminant analyses were used to categorize knee joint biomechanics for patients before and after surgery relative to asymptomatic, moderate, and severe OA. Post-TKA, 63% were categorized with knee biomechanics consistent with moderate OA, 29% with severe OA, and 8% asymptomatic. The magnitude and pattern of the knee adduction moment and angle (frontal plane features) were the most significant contributors in discriminating between pre-TKA and post-TKA knee biomechanics. Standard of care TKA improves knee biomechanics during gait to levels most consistent with moderate knee OA and predominately targets frontal plane features. These results provide evidence for the level of improvement in knee biomechanics that can be expected following surgery and highlight the biomechanics most targeted by surgery.

Markerless motion capture provides repeatable gait outcomes in patients with knee osteoarthritis.

Motion analysis has seen minimal adoption for orthopaedic clinical assessments. Markerless motion capture solutions, namely Theia3D, address limitations of previous methods and provide gait outcomes that are robust to clothing choice and repeatable in healthy adults. Repeatability in orthopaedic populations has not been investigated and is important for clinical utility and adoption. The purpose of this study was to evaluate the repeatability of Theia3D for gait analysis in a knee osteoarthritis population. Ten orthopaedic patients with knee osteoarthritis underwent gait analysis on three visits, with an average of 8 days between. Participants were recorded during one-minute overground walking trials at self-selected typical and fast speeds by 8 synchronized video cameras. Video data were processed using Theia3D. Intraclass correlations were used to examine the repeatability of temporal distance metrics as well as segment lengths of the underlying kinematic model. Inter-trial and inter-session variability of lower extremity joint angles were estimated for each point of the gait cycle. Intraclass correlations were greater than 0.98 for all temporal distance metrics for both speeds. Lower body segment lengths had intraclass correlations above 0.90. Participant average joint angle waveforms displayed consistent patterns between visits. The average inter-trial and inter-session variability in joint angles across speeds were 1.17 and 1.45 degrees, respectively. The variability in joint angles between visits was less than typically reported for marker-based methods. Gait outcomes measured with Theia3D were highly repeatable in patients with knee osteoarthritis providing further validation for its use in clinical assessment and longitudinal studies.

Identification of footstrike pattern using accelerometry and machine learning.

Recent reports have suggested that there may be a relationship between footstrike pattern and overuse injury incidence and type. With the recent increase in wearable sensors, it is important to identify paradigms where the footstrike pattern can be detected in real-time from minimal data. Machine learning was used to classify tibial acceleration data into three distinct footstrike patterns: rearfoot, midfoot, or forefoot. Tibial accelerometry data were collected during treadmill running from 58 participants who each ran with rearfoot, midfoot, and forefoot strike patterns. These data were used as inputs into an artificial neural network classifier. Models were created by using three distinct acceleration data sets, using the first 100%, 75%, and 40% of stance phase. All models were able to predict the footstrike pattern with up to 89.9% average accuracy. The highest error was associated with the identification of the midfoot versus forefoot strike pattern. This technique required no pre-selection of features or filtering of the data and may be easily incorporated into a wearable device to aid with real-time footstrike pattern detection.

Factors Associated With High-Risk and Low-Risk Bone Stress Injury in Female Runners: Implications for Risk Factor Stratification and Management.

Background: Bone stress injury (BSI) is a common overuse injury in active women. BSIs can be classified as high-risk (pelvis, sacrum, and femoral neck) or low-risk (tibia, fibula, and metatarsals). Risk factors for BSI include low energy availability, menstrual dysfunction, and poor bone health. Higher vertical load rates during running have been observed in women with a history of BSI. Purpose/Hypothesis: The purpose of this study was to characterize factors associated with BSI in a population of premenopausal women, comparing those with a history of high-risk or low-risk BSI with those with no history of BSI. It was hypothesized that women with a history of high-risk BSI would be more likely to exhibit lower bone mineral density (BMD) and related factors and less favorable bone microarchitecture compared with women with a history of low-risk BSI. In contrast, women with a history of low-risk BSI would have higher load rates. Study Design: Cross-sectional study; Level of evidence, 3. Methods: Enrolled were 15 women with a history of high-risk BSI, 15 with a history of low-risk BSI, and 15 with no history of BSI. BMD for the whole body, hip, and spine was standardized using z scores on dual-energy x-ray absorptiometry. High-resolution peripheral quantitative computed tomography was used to quantify bone microarchitecture at the radius and distal tibia. Participants completed surveys characterizing factors that influence bone health-including sleep, menstrual history, and eating behaviors-utilizing the Eating Disorder Examination Questionnaire (EDE-Q). Each participant completed a biomechanical assessment using an instrumented treadmill to measure load rates before and after a run to exertion. Results: Women with a history of high-risk BSI had lower spine z scores than those with low-risk BSI (-1.04 ± 0.76 vs -0.01 ± 1.15; P < .05). Women with a history of high-risk BSI, compared with low-risk BSI and no BSI, had the highest EDE-Q subscores for Shape Concern (1.46 ± 1.28 vs 0.76 ± 0.78 and 0.43 ± 0.43) and Eating Concern (0.55 ± 0.75 vs 0.16 ± 0.38 and 0.11 ± 0.21), as well as the greatest difference between minimum and maximum weight at current height (11.3 ± 5.4 vs 7.7 ± 2.9 and 7.6 ± 3.3 kg) (P < .05 for all). Women with a history of high-risk BSI were more likely than those with no history of BSI to sleep <7 hours on average per night during the week (80% vs 33.3%; P < .05). The mean and instantaneous vertical load rates were not different between groups. Conclusion: Women with a history of high-risk BSI were more likely to exhibit risk factors for poor bone health, including lower BMD, while load rates did not distinguish women with a history of BSI.

High tibiofemoral contact and muscle forces during gait are associated with radiographic knee OA progression over 3 years.

BACKGROUND: The objective of this study was to investigate differences in tibiofemoral joint contact forces between individuals with moderate medial OA who exhibit radiographic knee OA progression within 3 years versus those who do not, and to understand the relationship between model-predicted contact forces and net external moments for this population. METHODS: 27 individuals with moderate medial compartment knee OA underwent baseline instrumented gait analysis. OA progressors were defined as those who experienced at least a one grade increase in medial joint space narrowing at three years. An electromyography-driven musculoskeletal model was used to estimate muscle and tibiofemoral contact forces at baseline, which were compared between progressors and non-progressors using t-tests. RESULTS: Seven individuals experienced radiographic OA progression by 3 years. Progressors walked with significantly higher peaks of medial and total tibiofemoral contact forces, and higher impulse of medial contact forces. Significant and high correlations were found between: first peaks of medial and total contact forces with first peak of the knee adduction moment (R2 = 0.74; R2 = 0.59); second peaks of medial and total knee contact forces with second peaks of knee adduction and flexion moments (R2 = 0.71; R2 = 0.68); medial knee contact force impulse with knee adduction moment impulse (R2 = 0.76). CONCLUSIONS: Higher tibiofemoral joint contact forces during walking were associated with three-year radiographic knee OA progression based on medial joint space narrowing. These results support the need for strategies that reduce compressive knee contact forces through the reduction of adduction and flexion moments during walking.

Predicting ankle and knee sagittal kinematics and kinetics using an ankle-mounted inertial sensor.

The purpose of this study was to develop a machine learning model to reconstruct time series kinematic and kinetic profiles of the ankle and knee joint across six different tasks using an ankle-mounted IMU. Four male collegiate basketball players performed repeated tasks, including walking, jogging, running, sidestep cutting, max-height jumping, and stop-jumping, resulting in a total of 102 movements. Ankle and knee flexion-extension angles and moments were estimated using motion capture and inverse dynamics and considered 'actual data' for the purpose of model fitting. Synchronous acceleration and angular velocity data were collected from right ankle-mounted IMUs. A time-series feature extraction model was used to determine a set of features used as input to a random forest regression model to predict the ankle and knee kinematics and kinetics. Five-fold cross-validation was performed to verify the model accuracy, and statistical parametric mapping was used to determine the difference between the predicted and experimental time series. The random forest regression model predicted the time-series profiles of the ankle and knee flexion-extension angles and moments with high accuracy (Kinematics: R2 ranged from 0.782 to 0.962, RMSE ranged from 2.19° to 11.58°; Kinetics: R2 ranged from 0.711 to 0.966, RMSE ranged from 0.10 Nm/kg to 0.41 Nm/kg). There were differences between predicted and actual time series for the knee flexion-extension moment during stop-jumping and walking. An appropriately trained feature-based regression model can predict time series knee and ankle joint angles and moments across a wide range of tasks using a single ankle-mounted IMU.

Impact loading in female runners with single and multiple bone stress injuries during fresh and exerted conditions.

BACKGROUND: Bone stress injuries (BSIs) are common in female runners, and recurrent BSI rates are high. Previous work suggests an association between higher impact loading during running and tibial BSI. However, it is unknown whether impact loading and fatigue-related loading changes discriminate women with a history of multiple BSIs. This study compared impact variables at the beginning of a treadmill run to exertion and the changes in those variables with exertion among female runners with no history of BSI as well as among those with a history of single or multiple BSIs. METHODS: We enrolled 45 female runners (aged 18-40 years) for this cross-sectional study: having no history of diagnosed lower extremity BSI (N-BSI, n = 14); a history of 1 lower extremity BSI (1-BSI, n = 16); and diagnosed by imaging, or a history of multiple (≥3) lower extremity BSIs (M-BSI, n = 15). Participants completed a 5-km race speed run on an instrumented treadmill while wearing an Inertial Measurement Unit. The vertical average loading rate (VALR), vertical instantaneous loading rate (VILR), vertical stiffness during impact via instrumented treadmill, and tibial shock determined as the peak positive tibial acceleration via Inertial Measurement Unit were measured at the beginning and the end of the run. RESULTS: There were no differences between groups in VALR, VILR, vertical stiffness, or tibial shock in a fresh or exerted condition. However, compared to N-BSI, women with M-BSI had greater increase with exertion in VALR (-1.8% vs. 6.1%, p = 0.01) and VILR (1.5% vs. 4.8%, p = 0.03). Similarly, compared to N-BSI, vertical stiffness increased more with exertion among women with M-BSI (-0.9% vs. 7.3%, p = 0.006) and 1-BSI (-0.9% vs. 1.8%, p = 0.05). Finally, compared to N-BSI, the increase in tibial shock from fresh to exerted condition was greater among women with M-BSI (0.9% vs. 5.5%, p = 0.03) and 1-BSI (0.9% vs. 11.2%, p = 0.02). CONCLUSION: Women with 1-BSI or M-BSIs experience greater exertion-related increases in impact loading than women with N-BSI. These observations imply that exertion-related changes in gait biomechanics may contribute to risk of BSI.

Clothing condition does not affect meaningful clinical interpretation in markerless motion capture.

Markerless motion capture allows whole-body movements to be captured without the need for physical markers to be placed on the body. This enables motion capture analyses to be conducted in more ecologically valid environments. However, the influences of varied clothing on video-based markerless motion capture assessments remain largely unexplored. This study investigated two types of clothing conditions, "Sport" (gym shirt and shorts) and "Street" (unrestricted casual clothing), on gait parameters during overground walking by 29 participants at self-selected speeds using markerless motion capture. Segment lengths, gait spatiotemporal parameters, and lower-limb kinematics were compared between the two clothing conditions. Mean differences in segment length for the forearm, upper arm, thigh, and shank between clothing conditions ranged from 0.2 cm for the forearm to 0.9 cm for the thigh (p < 0.05 for thigh and shank) but below typical marker placement errors (1 - 2 cm). Seven out of 9 gait spatiotemporal parameters demonstrated statistically significant differences between clothing conditions (p < 0.05), however, these differences were approximately ten times smaller than minimal detectable changes in movement-related pathologies including multiple sclerosis and cerebral palsy. Hip, knee, and ankle joint angle root-mean-square deviation values averaged 2.6° and were comparable to previously reported average inter-session variability for this markerless system (2.8°). The results indicate that clothing, a potential limiting factor in markerless motion capture performance, would negligibly alter meaningful clinical interpretations under the conditions investigated.

Metatarsal Bone Marrow Edema on Magnetic Resonance Imaging and Its Correlation to Bone Stress Injuries in Male Collegiate Basketball Players.

BACKGROUND: The presence of bone marrow edema (BME) on magnetic resonance imaging (MRI) has been used to evaluate for bone stress injuries in athletes. PURPOSE: To examine the prevalence of MRI findings, including BME, in a single male collegiate basketball team before and after a single season and to assess its association with clinically symptomatic metatarsal bone stress injuries. STUDY DESIGN: Cohort Study; Level of evidence, 3. METHODS: A total of 16 men on a single collegiate basketball team (mean age, 20.0 ± 1.8 years) underwent 1.5-T MRI focused on both midfeet during the preseason, and 13 underwent repeat MRI during the postseason. MRI findings included the presence of BME and the radiographic classification of the bone stress injury (grades 1-4). Injury surveillance performed by athletic trainers was used to identify metatarsal bone stress injuries over the course of the season. RESULTS: Preseason MRI demonstrated metatarsal BME in 5 of the 16 participants, and postseason MRI demonstrated metatarsal BME in 4 of the 13 participants. All 4 of the participants with postseason BME had MRI findings of BME in the same metatarsals. Compared to those without BME, participants with metatarsal BME had a shorter history of basketball exposure (preseason: 10.4 ± 4.1 vs 14.2 ± 1.9 years, respectively [P = .023]; postseason: 9.6 ± 4.1 vs 14.0 ± 2.1 years, respectively [P = .024]), and those with postseason BME had started playing at an older age (9.8 ± 4.3 vs 6.2 ± 1.6 years, respectively; P = .050). The preseason MRI classification for metatarsals included grade 1 (n = 3), followed by grades 2 and 3 (n = 2 each). In the 4 participants with postseason MRI findings, the grade increased from 1 to 4 in 1 participant and was stable in the other 3. No participants were diagnosed clinically with a metatarsal bone stress injury during the season. BME of the sesamoids was identified in 6 participants, who trended toward being older (21.0 ± 2.2 vs 19.4 ± 1.3 years, respectively; P < .10), with the abnormalities persisting on postseason MRI in all players. CONCLUSION: Collegiate male basketball players may have a high prevalence of BME, often without associated symptoms. The absence of foot pain or a corresponding diagnosis of a metatarsal bone stress injury in this study suggests that MRI findings of BME in asymptomatic athletes should be interpreted with caution.

Relationships between tibial acceleration and ground reaction force measures in the medial-lateral and anterior-posterior planes.

Peak vertical tibial accelerations during running have shown strong correlations with vertical ground reaction force loading rates and some associations with injury. However, little attention has been given to tibial accelerations along the medial-lateral and anterior-posterior axes. Therefore, our purpose was to examine the correlation between peak tibial accelerations and ground reaction force loading rates in the medial-lateral and posterior directions. Eighteen recreational runners were recruited who ran with a rearfoot strike pattern (10 men/ 8 women, mean age (yrs) = 33 ± 11). Tibial accelerations and ground reaction forces were collected while participants ran on an instrumented treadmill at a self-selected speed. Correlations were developed for: a) peak medial and lateral accelerations with lateral and medial loading rates, respectively, b) peak anterior tibial accelerations and posterior loading rates. Significant correlations were found between tibial accelerations and loading rates in all planes. Peak medial tibial accelerations were correlated with lateral loading rates (Rs = 0.86, p < 0.001) and peak lateral tibial accelerations were correlated with peak medial loading rates (Rs = 0.91, p < 0.001). A lower correlation was found between anterior accelerations and posterior loading rates (Rs = 0.51, p = 0.030). Tibial accelerations in the medial-lateral plane seem to be a valid surrogate for the respective ground reaction force measures during running on a treadmill, explaining 74-83% of the variance in loading rates. However, with only 26% of the variance explained, the same may not be true for anterior tibial accelerations and posterior loading rates.

Multifactorial Determinants of Running Injury Locations in 550 Injured Recreational Runners.

PURPOSE: Despite the health benefits of running, the prevalence of running-related injuries (RRI) remains high. The underlying risk factors between these injuries are still not well understood. Therefore, the aim of this study was to compare biomechanical, anthropometric, and demographic injury risk factors between different locations in injured recreational runners. METHODS: In this retrospective case-control analysis, 550 injured runners (49.6% female) with a medically diagnosed RRI were included. All runners had undergone an instrumented treadmill analysis to determine habitual footstrike pattern, vertical instantaneous load rate, peak vertical ground reaction force (vGRF) and cadence. Injuries were classified by location according to a recent consensus statement. A logistic regression model was used to determine the association between the biomechanical parameters and RRI locations. Because injuries can be associated with age, sex, and body mass index, these variables were also entered into the logistic regression. RESULTS: Strike pattern and peak vGRF were the only biomechanical variable distinguishing an injury from the group of injuries. A midfoot strike differentiated Achilles tendon injuries (odds ratio [OR], 2.27; 90% confidence interval [CI], 1.17-4.41) and a forefoot strike distinguished posterior lower leg injuries (OR, 2.59; 90% CI, 1.50-4.47) from the rest of the injured group. Peak vGRF was weakly associated with hip injuries (OR, 1.14; 90% CI, 1.05-1.24). Female sex was associated with injuries to the lower leg (OR, 2.65; 90% CI, 1.45-4.87) and hip/groin (OR, 2.22; 90% CI, 1.43-3.45). Male sex was associated with Achilles tendon injuries (OR, 1.923; 90% CI, 1.094-3.378). CONCLUSIONS: Sex, foot strike pattern, and vGRF were the only factors that distinguished specific injury locations from the remaining injury locations.

Tibial Acceleration Measured from Wearable Sensors Is Associated with Loading Rates in Injured Runners.

BACKGROUND: The loadrate of the vertical ground reaction force at impact has been associated with a variety of running injuries. Peak tibial shocks occur during the early stance phase and has been shown to be correlated to the loadrates in healthy runners using a rearfoot strike pattern. As a result, tibial accelerometry has been used as a surrogate for loadrates. However, these correlations have not been assessed in injured runners nor in runners with differing footstrike patterns. OBJECTIVE: To examine the relationship between tibial acceleration and loadrates in injured runners who are habitual rearfoot (RFS), midfoot (MFS), and forefoot (FFS) strikers. Tibial acceleration was expected to be positively associated with loadrates across all footstrike patterns. DESIGN: Cross-sectional cohort. SETTING: Academic medical center with biomechanics laboratory. PARTICIPANTS: One hundred sixty-nine injured runners (age 38.7 ± 13.1 years, 127 RFS, 17 MFS, 25 FFS). METHODS: Each participant completed a biomechanical assessment for injury including evaluation on a force treadmill with a triaxial accelerometer fastened by a Velcro strap to the distal medial tibia. Peak vertical and resultant tibial acceleration (VTA, RTA) were measured from the accelerometer. Vertical average and instantaneous loadrates (VALR, VILR) and the resultant instantaneous loadrate (RILR) were determined from the force data. MAIN OUTCOME MEASUREMENTS: The relationship between tibial acceleration and loadrates measured using Pearson's correlation coefficient (r). RESULTS: Loadrates were each associated with VTA (r = 0.66-0.82, P < .001) and RTA (r = 0.41-0.68, P < .05) across all footstrike groups with the exception of association of VILR to RTA in the FFS group. The strength in correlations was lowest between RTA and loadrates for the FFS runners (r = 0.41-0.47, P < .05). CONCLUSION: Vertical tibial acceleration is the stronger surrogate for loadrates in injured runners across differing footstrike patterns.

A comparison of attachment methods of skin mounted inertial measurement units on tibial accelerations.

Peak tibial accelerations during running are of interest because of their correlation with vertical ground reaction force load rates and association with running injury. Previous work has demonstrated systematically lower accelerations measured with a bone- compared to skin-mounted accelerometer. However, no studies have assessed the effects of more or less secure attachment methods for skin mounted sensors. Our purpose was to compare two methods of attaching a skin mounted sensor on mean tibial accelerations, stride-to-stride variability, and correlations with vertical load rates. 18 injury-free runners were recruited as participants. An inertial measurement unit, containing a tri-axial accelerometer, was used to record tibial accelerations while participants ran at a self-selected speed on an instrumented treadmill to collect ground reaction forces. The two attachment methods for securing the sensor to the skin were a manufacturer-provided strap (strap condition) and a combination of tape and elastic wraps (wrap condition). Mean vertical accelerations were significantly lower in the wrap condition (p = 0.02, d = 0.57). No differences were detected in resultant accelerations, vertical loading rates, or stride-to-stride variability. Correlations between tibial accelerations and vertical loading rates were strong (r = 0.79-0.91) and similar between conditions. These results provide two key findings of evidence. Evidenced by systematically lower vertical accelerations, a more secure attachment method may be necessary for capturing the most representative measure of tibial accelerations during running. However, a less secure method (i.e. the strap) is sufficient for capturing tibial accelerations as a surrogate for impact loading forces.

Impact-Related Ground Reaction Forces Are More Strongly Associated With Some Running Injuries Than Others.

BACKGROUND: Inconsistent associations have been reported for impact-related ground reaction force variables and running injuries when grouping all injuries together. However, previous work has shown more consistent associations when focusing on specific injuries. PURPOSE: To compare ground reaction force variables between healthy and injured runners as a group and within specific common injuries. STUDY DESIGN: Controlled laboratory study. METHODS: A total of 125 runners presenting with patellofemoral pain, tibial bone stress injury, plantar fasciitis, Achilles tendinopathy, or iliotibial band syndrome and 65 healthy controls completed an instrumented treadmill assessment at a self-selected speed. Impact-related ground reaction force variables included vertical average (VALR) and instantaneous (VILR) load rates, posterior and medial/lateral instantaneous load rates, and vertical stiffness at initial loading (VSIL). Mean comparisons were made between the general and specific injury and control groups (α = .05). Cutoff thresholds were established and evaluated using several criteria. RESULTS: VALR (+17.5%; P < .01), VILR (+15.8%; P < .01), and VSIL (+19.7%; P < .01) were significantly higher in the overall injured versus control groups. For individual injuries, VALR, VILR, and VSIL were significantly higher for patellofemoral pain (+23.4%-26.4%; P < .01) and plantar fasciitis (+17.5%-29.0%; P < .01), as well as VSIL for Achilles tendinopathy (+29.4%; P < .01). Cutoff thresholds showed better diagnostic criteria for individual versus grouped injuries. CONCLUSION: Impact variables (VALR, VILR, and VSIL) were significantly higher when assessing the injured group as a whole. However, these findings were driven by specific injury groups, highlighting the importance of taking an injury-specific approach to biomechanical risk factors for running injury. CLINICAL RELEVANCE: These results suggest that practitioners may want to address impact loading in their treatment of injured runners, especially in those with patellofemoral pain and plantar fasciitis.

Comparison of Tibial Shock during Treadmill and Real-World Running.

The degree to which standard laboratory gait assessments accurately reflect impact loading in an outdoor running environment is currently unknown. PURPOSE: To compare tibial shock between treadmill and road marathon conditions. METHODS: One hundred ninety-two runners (men/women, 105/87; age, 44.9 ± 10.8 yr) completed a treadmill gait assessment while wearing a tibial-mounted inertial measurement unit, several days before completing a marathon race. Participants ran at 90% of their projected race speed and 30 s of tibial shock data were collected. Participants then wore the sensors during the race and tibial shock was averaged over the 12th, 23rd, and 40th kilometers. One-way analysis of covariance and correlation coefficients were used to compare vertical/resultant tibial shock between treadmill and marathon conditions. Analyses were adjusted for differences in running speed between conditions. RESULTS: A significant main effect of condition was found for mean vertical and resultant tibial shock (P < 0.001). Early in the marathon (12-km point), runners demonstrated higher mean tibial shock adjusted for speed compared with the treadmill data (vertical = +24.3% and resultant = +30.3%). Mean differences decreased across the course of the marathon. Vertical tibial shock at the 40th kilometer of the race was similar to treadmill data, and resultant shock remained higher. Vertical and resultant tibial shock were significantly correlated between treadmill and the 12th kilometer of the race (rs = 0.64-0.65, P < 0.001), with only 40% to 42% of the variance in outdoor tibial shock explained by treadmill measures. Correlations for tibial shock showed minimal changes across stages of the marathon. CONCLUSIONS: These results demonstrate that measures of impact loading in an outdoor running environment are not fully captured on a treadmill.