Validity and reliability of peak tibial accelerations as real-time measure of impact loading during over-ground rearfoot running at different speeds

Sex- and age-related differences in kinetics and tibial accelerations during military-relevant movement tasks in U.S. Army trainees

Lower extremity injuries are prevalent in military trainees, especially in female and older trainees. Modifiable factors that lead to higher injury risk in these subgroups are not clear. The purpose of this study was to identify whether external loading variables during military-relevant tasks differ by age and sex in U.S. Army trainees. Data was collected on 915 trainees in the first week of Basic Combat Training. Participants performed running and ruck marching (walking with 18.1 kg pack) on a treadmill, as well as double-/single-leg drop landings. Variables included: vertical force loading rates, vertical stiffness, first peak vertical forces, peak vertical and resultant tibial accelerations. Comparisons were made between sexes and age groups (young, ≤19 years; middle, 20-24 years; older, ≥25 years). Significant main effects of sex were found, with females showing higher vertical loading rates during ruck marching, and peak tibial accelerations during running and ruck marching (p ≤ 0.03). Males showed higher vertical stiffness during running and peak vertical tibial accelerations during drop landings (p < 0.01). A main effect of age was found for vertical loading rates during running (p = 0.03), however no significant pairwise differences were found between age groups. These findings suggest that higher external loading may contribute to higher overall injury rates in female trainees. Further, higher stiffness during running may contribute to specific injuries, such as Achilles Tendinopathy, that are more prevalent in males. The lack of differences between age groups suggests that other factors contribute more to higher injury rates in older trainees.

Rethinking running biomechanics: a critical review of ground reaction forces, tibial bone loading, and the role of wearable sensors

This study presents a comprehensive review of the correlation between tibial acceleration (TA), ground reaction forces (GRF), and tibial bone loading, emphasizing the critical role of wearable sensor technology in accurately measuring these biomechanical forces in the context of running. This systematic review and meta-analysis searched various electronic databases (PubMed, SPORTDiscus, Scopus, IEEE Xplore, and ScienceDirect) to identify relevant studies. It critically evaluates existing research on GRF and tibial acceleration (TA) as indicators of running-related injuries, revealing mixed findings. Intriguingly, recent empirical data indicate only a marginal link between GRF, TA, and tibial bone stress, thus challenging the conventional understanding in this field. The study also highlights the limitations of current biomechanical models and methodologies, proposing a paradigm shift towards more holistic and integrated approaches. The study underscores wearable sensors' potential, enhanced by machine learning, in transforming the monitoring, prevention, and rehabilitation of running-related injuries.

Learning effects in over-ground running gait retraining: A six-month follow-up of a quasi-randomized controlled trial

This study evaluated learning and recall effects following a feedback-based retraining program. A 6-month follow-up of a quasi-randomized controlled trial was performed with and without recall. Twenty runners were assigned to experimental or control groups and completed a 3-week running program. A body-worn system collected axial tibial acceleration and provided real-time feedback on peak tibial acceleration for six running sessions in an athletic training facility. The experimental group received music-based biofeedback in a faded feedback scheme. The controls received tempo-synchronized music as a placebo for blinding purposes. The peak tibial acceleration and vertical loading rate of the ground reaction force were determined in a lab at baseline and six months following the intervention to assess retention and recall. The impacts of the experimental group substantially decreased at follow-up following a simple verbal recall (i.e., run as at the end of the program): peak tibial acceleration:-32%, p = 0.018; vertical loading rate:-34%, p = 0.006. No statistically significant changes were found regarding the retention of the impact variables. The impact magnitudes did not change over time in the control group. The biofeedback-based intervention did not induce clear learning at follow-up, however, a substantial impact reduction was recallable through simple cueing in the absence of biofeedback.

Sensor location influences the associations between IMU and motion capture measurements of impact landing in healthy male and female runners at multiple running speeds

This study investigated the relationships between inertial measurement unit (IMU) acceleration at multiple body locations and 3D motion capture impact landing measures in runners. Thirty healthy runners ran on an instrumented treadmill at five running speeds (9-17 km/h) during 3D motion capture. Axial and resultant acceleration were collected from IMUs at the distal and proximal tibia, distal femur and sacrum. Relationships between peak acceleration from each IMU location and patellofemoral joint (PFJ) peak force and loading rate, impact peak and instantaneous vertical loading rate (IVLR) were investigated using linear mixed models. Acceleration was positively related to IVLR at all lower limb locations (p < 0.01). Models predicted a 1.9-3.2 g peak acceleration change at the tibia and distal femur, corresponding with a 10% IVLR change. Impact peak was positively related to acceleration at the distal femur only (p < 0.01). PFJ peak force was positively related to acceleration at the distal (p = 0.03) and proximal tibia (p = 0.03). PFJ loading rate was positively related to the tibia and femur acceleration in males only (p < 0.01). These findings suggest multiple IMU lower limb locations are viable for measuring peak acceleration during running as a meaningful indicator of IVLR.

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.

Association of tibial acceleration during walking to pain and impact loading in adults with knee osteoarthritis

BACKGROUND

Higher impact loading during walking is implicated in the pathogenesis of knee osteoarthritis. Accelerometry enables the measurement of peak tibial acceleration outside the laboratory. We characterized the relations of peak tibial acceleration to knee pain and impact loading during walking in adults with knee osteoarthritis.

METHODS

Adults with knee osteoarthritis reported knee pain then walked at a self-selected speed on an instrumented treadmill for 3 min with an ankle-worn inertial measurement unit. Ground reaction forces and tibial acceleration data were sampled for 1 min. Vertical impact peaks, and average and peak instantaneous load rates were determined and averaged across 10 steps. Peak tibial acceleration was extracted for all steps and averaged. Pearson's correlations and multiple linear regression analyses assessed the relation of peak tibial acceleration to pain and impact loading metrics, independently and after controlling for gait speed and pain.

FINDINGS

Higher peak tibial acceleration was associated with worse knee pain (r = 0.39; p = 0.01), and higher vertical average (r = 0.40; p = 0.01) and instantaneous (r = 0.46; p = 0.004) load rates. After adjusting for gait speed and pain, peak tibial acceleration was a significant predictor of vertical average (R2 = 0.33; p = 0.003) and instantaneous (R2 = 0.28; p = 0.02) load rates, but not strongly associated with vertical impact peak.

INTERPRETATIONS

Peak tibial acceleration during walking is associated with knee pain and vertical load rates in those with knee osteoarthritis. Clinicians can easily access measures of peak tibial acceleration with wearable sensors equipped with accelerometers. Future work should determine the feasibility of improving patient outcomes by using peak tibial acceleration to inform clinical management.

Evaluating a Wearable Solution for Measuring Lower Extremity Asymmetry During Landing

Purpose

Force plates can be used to monitor landing asymmetries during rehabilitation, but they are not widely available. Accelerometer-based wearable technology may be a more feasible solution. The purpose of this article was to determine the agreement between impact accelerations measured with force plates and accelerometer-derived measures of (1) centre of mass (COM) acceleration and (2) tibial acceleration asymmetries during bilateral landings.

Method

Participants completed three countermovement jumps (CMJ) and three squat jumps (SJ) on dual force plates with triaxial accelerometers attached to each tibia and lower back, near the COM. Bland and Altman 95% limits of agreement (95% LOA) were calculated.

Results

19 adults (n = 11; 58% women, n = 8; 42% men) participated in the study. The mean differences between impact and COM accelerations were 0.24 g (95% LOA: -1.34 g to 1.82 g) and 0.38 g (95% LOA: -1.15 to 1.91 g) for the CMJ and SJ, respectively. The mean differences between the impact and tibial acceleration-based lower limb asymmetries in the CMJ and SJ were -6% (95% LOA: -32% to 19%) and 0% (95% LOA: -45% to 45%), respectively.

Conclusions

Our findings show acceptable agreement between impact acceleration and accelerometer-based COM acceleration and lack of agreement between impact accelerations and accelerometer-based tibial acceleration asymmetries. COM acceleration could be used to quantify landing impacts during rehabilitation, but we do not consider the accelerometer-based asymmetry measures to be a suitable alternative for force plate-based measures. Future work should focus on determining normative values for lower extremity asymmetries during landing tasks.

Running towards injury? A prospective investigation of factors associated with running injuries

BACKGROUND

Given the high incidence and heavy burden of running related injuries, large-scale, prospective multifactorial investigations examining potential risk factors are warranted. This study aimed to identify factors associated with running related injuries and to evaluate their potential in injury screening.

STUDY DESIGN

Prospective cohort study.

MATERIALS AND METHODS

Two hundred and seventy-four recreational runners were recruited. Clinical measures (strength, range of motion, foot position), injury and training history (via questionnaire), impact loading (via accelerometery) and running technique measures were collected at baseline. Runners were tracked for injury for one year via fortnightly check-ins. A binary logistic regression, (injury versus no injury), was performed for each variable univariably, and then adjusting for age, sex and mileage. A multivariable regression was also performed to evaluate the model's discriminative ability.

RESULTS

Of the 225 runners included in the final analysis 52% experienced a running related injury. Injury history in the past year, less navicular drop, and measures of running technique (knee, hip, and pelvis kinematics) were associated with increased odds of injury (p < .05). The multivariable logistic regression model was statistically significant, χ2(11) = 56.45, p < .001, correctly classifying 74% of cases with a sensitivity and specificity of 72% and 76%, respectively. The area under the receiver operating characteristic curve was 0.79 (CI95% = 0.73-0.85), demonstrating acceptable discriminative ability.

CONCLUSIONS

This study found a number of clinical and running technique factors to be associated with prospective running related injuries among recreational runners. With the exception of injury history, the factors identified as being significantly associated with injury may be modifiable and therefore, could form the basis of interventions. Range of motion, spatiotemporal parameters and strength measures were not associated with injury and thus their utilisation in injury prevention practices should be reconsidered.

Relationships between tibial accelerations and ground reaction forces during walking with load carriage

Peak tibial accelerations (TAs) during running are strongly related to early stance vertical ground reaction forces (GRFs), which are associated with musculoskeletal injury. However, few studies have examined these correlations during walking, and none have evaluated them during walking with loads, a relevant activity for military personnel. Our purpose was to determine the relationships between GRFs and TAs in US Army trainees (n = 649) walking with loads. An inertial measurement unit was attached over their distal antero-medial tibia. Participants walked on an instrumented treadmill at 1.21-1.34 m/s, with a pack loaded with 18.1 kg, for a 3-min warm-up followed by a minimum of 14 strides of data collection. Simple linear regression models were calculated for peak vertical and resultant TAs with vertical and posterior GRF loading rates and peak forces. The strongest relationships were between vertical loading rates and peak vertical TA (R = 0.43-0.50), however the relationships were weaker than has been reported for unloaded walking and running (R > 0.7). All other relationships were trivial to small (R = 0.06-0.27). The weaker relationships for vertical GRFs and TAs may be due to methodological differences between studies, or differences in gait mechanics, such as a longer double-limb support phase in loaded vs. unloaded walking.

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.

Evaluation of a Restoration Algorithm Applied to Clipped Tibial Acceleration Signals

Wireless accelerometers with various operating ranges have been used to measure tibial acceleration. Accelerometers with a low operating range output distorted signals and have been found to result in inaccurate measurements of peaks. A restoration algorithm using spline interpolation has been proposed to restore the distorted signal. This algorithm has been validated for axial peaks within the range of 15.0-15.9 g. However, the accuracy of peaks of higher magnitude and the resultant peaks have not been reported. The purpose of the present study is to evaluate the measurement agreement of the restored peaks using a low-range accelerometer (±16 g) against peaks sampled using a high-range accelerometer (±200 g). The measurement agreement of both the axial and resultant peaks were examined. In total, 24 runners were equipped with 2 tri-axial accelerometers at their tibia and completed an outdoor running assessment. The accelerometer with an operating range of ±200 g was used as reference. The results of this study showed an average difference of -1.40 ± 4.52 g and -1.23 ± 5.48 g for axial and resultant peaks. Based on our findings, the restoration algorithm could skew data and potentially lead to incorrect conclusions if used without caution.

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.

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.

Peak tibial acceleration should not be used as indicator of tibial bone loading during running

Peak tibial acceleration (PTA) is a widely used indicator of tibial bone loading. Indirect bone loading measures are of interest to reduce the risk of stress fractures during running. However, tibial compressive forces are caused by both internal muscle forces and external ground reaction forces. PTA might reflect forces from outside the body, but likely not the compressive force from muscles on the tibial bone. Hence, the strength of the relationship between PTA and maximum tibial compression forces in rearfoot-striking runners was investigated. Twelve runners ran on an instrumented treadmill while tibial acceleration was captured with accelerometers. Force plate and inertial measurement unit data were spatially aligned with a novel method based on the centre of pressure crossing a virtual toe marker. The correlation coefficient between maximum tibial compression forces and PTA was 0.04 ± 0.14 with a range of -0.15 to +0.28. This study showed a very weak and non-significant correlation between PTA and maximum tibial compression forces while running on a level treadmill at a single speed. Hence, PTA as an indicator for tibial bone loading should be reconsidered, as PTA does not provide a complete picture of both internal and external compressive forces on the tibial bone.  .

Biomechanical adaptations following a music-based biofeedback gait retraining program to reduce peak tibial accelerations

PURPOSE

The present study aimed to determine whether runners can reduce impact measures after a six-session in-the-field gait retraining program with real-time musical biofeedback on axial peak tibial acceleration (PTA_a ) and identify the associated biomechanical adaptations.

METHODS

Twenty trained high-impact runners were assigned to either the biofeedback or the music-only condition. The biofeedback group received real-time feedback on the PTA_a during the gait retraining program, whereas the music-only condition received a sham treatment. Three-dimensional gait analysis was conducted in the laboratory before (PRE) and within one week after completing the gait retraining program (POST). Subjects were instructed to replicate the running style from the last gait retraining session without receiving feedback while running overground at a constant speed of 2.9 m∙s^-1 .

RESULTS

Only the biofeedback group showed significant reductions in both PTA_a (∆x̅ = -26.9%, p = 0.006) and vertical instantaneous loading rate (∆x̅ = -29.2%, p = 0.003) from PRE to POST. In terms of biomechanical adaptations, two strategies were identified. Two subjects transitioned toward a more forefoot strike. The remaining eight subjects used a pronounced rearfoot strike and posteriorly inclined shank at initial contact combined with less knee extension at toe-off while reducing vertical excursion of the center of mass.

CONCLUSIONS

After completing a music-based biofeedback gait retraining program, runners can reduce impact while running overground in a laboratory. We identified two distinct self-selected strategies used by the participants to achieve reductions in impact.

Relative and absolute reliability of shank and sacral running impact accelerations over a short- and long-term time frame

Whilst running is hugely popular, running-related injuries (RRIs) are prevalent. High impact loading has been proposed to contribute to RRIs, with accelerometers becoming increasingly popular in estimating segmental loading for injury detection and biofeedback training. However, there is a lack of research examining the reliability of measures of impact acceleration across short- and long-term time periods, both prior to and following exerted running. The aim of this study was to assess the absolute and relative reliability of shank and sacral impact accelerations over a short- and long-term time period. Peak (Peakaccel) and rate (Rateaccel) of impact acceleration at the shank and sacrum were assessed in 18 recreational runners over short- and long-term time frames, across fixed and self-selected speeds. The relative and absolute reliabilities were investigated for pre- and post-exerted states of running. There was high-to-excellent relative reliability, and predominantly moderate absolute reliability for shank and sacrum Peakaccel and Rateaccel in the short- and long-term time frames between pre- and post-exerted states. High to excellent relative reliability of Peakaccel and Rateaccel at the shank and sacrum are appropriate and acceptable measures across short- and long-term time frames. These findings were consistent with different levels of speed and exertion. The minimal detectable change % was large for both sensors and associated measurements, indicating that their use may be limited to intervention studies that elicit large change (>30%) in these measures.

One hundred marathons in 100 days: Unique biomechanical signature and the evolution of force characteristics and bone density

BACKGROUND

An extraordinary long-term running performance may benefit from low dynamic loads and a high load-bearing tolerance. An extraordinary runner (age = 55 years, height = 1.81 m, mass = 92 kg) scheduled a marathon a day for 100 consecutive days. His running biomechanics and bone density were investigated to better understand successful long-term running in the master athlete.

METHODS

Overground running gait analysis and bone densitometry were conducted before the marathon-a-day challenge and near its completion. The case's running biomechanics were compared pre-challenge to 31 runners who were matched by a similar foot strike pattern.

RESULTS

The case's peak vertical loading rate (Δx̄ = -61.9 body weight (BW)/s or -57%), peak vertical ground reaction force (Δx̄ = -0.38 BW or -15%), and peak braking force (Δx̄ = -0.118 BW or -31%) were remarkably lower (p < 0.05) than the control group at ∼3.3 m/s. The relatively low loading-related magnitudes were attributed to a remarkably high duty factor (0.41) at the evaluated speed. The foot strike angle of the marathoner (29.5°) was greater than that of the control group, affecting the peak vertical loading rate. Muscle powers in the lower extremity were also remarkably low in the case vs. controls: peak power of knee absorption (Δx̄ = -9.16 watt/kg or -48%) and ankle generation (Δx̄ = -3.17 watt/kg or -30%). The bone mineral density increased to 1.245 g/cm² (+2.98%) near completion of the challenge, whereas the force characteristics showed no statistically significant change.

CONCLUSION

The remarkable pattern of the high-mileage runner may be useful in developing or evaluating load-shifting strategies in distance running.

A machine learning approach to identify risk factors for running-related injuries: study protocol for a prospective longitudinal cohort trial

BACKGROUND

Running is a very popular sport among both recreational and competitive athletes. However, participating in running is associated with a comparably high risk of sustaining an exercise-related injury. Due to the often multifactorial and individual reasons for running injuries, a shift in thinking is required to account for the dynamic process of the various risk factors. Therefore, a machine learning approach will be used to comprehensively analyze biomechanical, biological, and loading parameters in order to identify risk factors and to detect risk patterns in runners.

METHODS

The prospective longitudinal cohort study will include competitive adult athletes, running at least 20 km per week and being free of injuries three months before the start of the study. At baseline and the end of the study period, subjective questionnaires (demographics, injury history, sports participation, menstruation, medication, psychology), biomechanical measures (e.g., stride length, cadence, kinematics, kinetics, tibial shock, and tibial acceleration) and a medical examination (BMI, laboratory: blood count, creatinine, calcium, phosphate, parathyroid hormone, vitamin D, osteocalcin, bone-specific alkaline phosphatase, DPD cross-links) will be performed. During the study period (one season), continuous data collection will be performed for biomechanical parameters, injuries, internal and external load. Statistical analysis of the data is performed using machine learning (ML) methods. For this purpose, the correlation of the collected data to possible injuries is automatically learned by an ML model and from this, a ranking of the risk factors can be determined with the help of sensitivity analysis methods.

DISCUSSION

To achieve a comprehensive risk reduction of injuries in runners, a multifactorial and individual approach and analysis is necessary. Recently, the use of ML processes for the analysis of risk factors in sports was discussed and positive results have been published. This study will be the first prospective longitudinal cohort study in runners to investigate the association of biomechanical, bone health, and loading parameters as well as injuries via ML models. The results may help to predict the risk of sustaining an injury and give way for new analysis methods that may also be transferred to other sports.

TRIAL REGISTRATION

DRKS00026904 (German Clinical Trial Register DKRS), date of registration 18.10.2021.

Evaluating daily physical activity and biomechanical measures using wearable technology in people with Achilles tendinopathy: A descriptive exploratory study

BACKGROUND

Load management is considered an important factor for prevention and treatment of Achilles tendinopathy. However, little attention has been given to monitoring daily load objectively in this population.

OBJECTIVES

We aimed to explore patterns in proxies of daily load derived from a six-axis inertial measurement unit (IMU) over a one-week period and the concordance between day-to-day fluctuation in pain intensity and IMU measures.

DESIGN

Descriptive exploratory study.

METHOD

Ten participants with Achilles tendinopathy (age: 53.00 ± 12.37) wore an IMU on the affected ankle for one week. Participants were contacted via text message three times daily to rate their worst pain intensity. Physical activity and biomechanical measures derived from the IMU signals including daily number of steps, peak stride rate, peak shank acceleration, and peak shank angular velocity were calculated.

RESULTS

The relationship between weekly worst pain and physical activity levels appeared modest; with increased steps not seeming to be linked to increased or reduced pain levels. According to the daily pain and daily IMU measures, a concordant pattern was evident in younger, highly active participants. However, in the middle-aged/older less active participants, there was either a fluctuation in pain intensity without fluctuation in the IMU measures, or a stable pattern of both pain and IMU measures.

CONCLUSIONS

Our exploratory study results suggest that continuous monitoring of proxies of daily load measures in parallel with pain may provide information about load management strategies in people with Achilles tendinopathy. Monitoring of these proxies may ultimately have a role in improving Achilles tendinopathy management.

Running Injury Paradigms and Their Influence on Footwear Design Features and Runner Assessment Methods: A Focused Review to Advance Evidence-Based Practice for Running Medicine Clinicians

Many runners seek health professional advice regarding footwear recommendations to reduce injury risk. Unfortunately, many clinicians, as well as runners, have ideas about how to select running footwear that are not scientifically supported. This is likely because much of the research on running footwear has not been highly accessible outside of the technical footwear research circle. Therefore, the purpose of this narrative review is to update clinical readers on the state of the science for assessing runners and recommending running footwear that facilitate the goals of the runner. We begin with a review of basic footwear construction and the features thought to influence biomechanics relevant to the running medicine practitioner. Subsequently, we review the four main paradigms that have driven footwear design and recommendation with respect to injury risk reduction: Pronation Control, Impact Force Modification, Habitual Joint (Motion) Path, and Comfort Filter. We find that evidence in support of any paradigm is generally limited. In the absence of a clearly supported paradigm, we propose that in general clinicians should recommend footwear that is lightweight, comfortable, and has minimal pronation control technology. We further encourage clinicians to arm themselves with the basic understanding of the known effects of specific footwear features on biomechanics in order to better recommend footwear on a patient-by-patient basis.

Is This the Real Life, or Is This Just Laboratory? A Scoping Review of IMU-Based Running Gait Analysis

Inertial measurement units (IMUs) can be used to monitor running biomechanics in real-world settings, but IMUs are often used within a laboratory. The purpose of this scoping review was to describe how IMUs are used to record running biomechanics in both laboratory and real-world conditions. We included peer-reviewed journal articles that used IMUs to assess gait quality during running. We extracted data on running conditions (indoor/outdoor, surface, speed, and distance), device type and location, metrics, participants, and purpose and study design. A total of 231 studies were included. Most (72%) studies were conducted indoors; and in 67% of all studies, the analyzed distance was only one step or stride or <200 m. The most common device type and location combination was a triaxial accelerometer on the shank (18% of device and location combinations). The most common analyzed metric was vertical/axial magnitude, which was reported in 64% of all studies. Most studies (56%) included recreational runners. For the past 20 years, studies using IMUs to record running biomechanics have mainly been conducted indoors, on a treadmill, at prescribed speeds, and over small distances. We suggest that future studies should move out of the lab to less controlled and more real-world environments.

Foot strike determines the center of pressure behavior and affects impact severity in heel-toe running

This study assessed the centre of pressure (COP) behaviour and the relationship with impact severity during heel-toe running in conventional athletic footwear. We hypothesized that the COP behaviour depends on its location at foot strike, which would be associated with the vertical loading rate and peak tibial accelerations in heel-toe running. Ground reaction force and tibial acceleration were measured in 104 distance runners running level at ~3.2 m/s. High-speed plantar pressure captured at high temporal resolution (500 Hz) and spatial resolution (7.62 · 5.08 mm/sensor) allowed for localization of the COP directly in the footprint during running in self-selected athletic footwear. More lateral X-coordinates of the COP at first foot contact had, in general, more anterior Y-coordinates (adj.R²:0.609). In heel-toe running, a more anterior foot strike had a greater refined strike index, which was associated with a quicker roll-over in the rearfoot zone. This strike index contributed to greater maximum vertical loading rates (R²:0.121), and greater axial (R²:0.047) and resultant (R²:0.247) peak tibial accelerations. These findings indicate that (1) the COP progression is dependend on the COP location at foot strike; (2) more anterior rearfoot strikes are more likely to have greater impact severity than posterior rearfoot strikes.

Reducing the peak tibial acceleration of running by music-based biofeedback: A quasi-randomized controlled trial

BACKGROUND

Running retraining with the use of biofeedback on an impact measure has been executed or evaluated in the biomechanics laboratory. Here, the execution and evaluation of feedback-driven retraining are taken out of the laboratory.

PURPOSE

To determine whether biofeedback can reduce the peak tibial acceleration with or without affecting the running cadence in a 3-week retraining protocol.

STUDY DESIGN

Quasi-randomized controlled trial.

METHODS

Twenty runners with high peak tibial acceleration were allocated to either the retraining (n=10, 32.1±7.8 yrs., 10.9±2.8 g) or control groups (n=10, 39.1±10.4 yrs., 13.0±3.9 g). They performed six running sessions in an athletic training environment. A body-worn system collected axial tibial acceleration and provided real-time feedback. The retraining group received music-based biofeedback in a faded feedback scheme. Pink noise was superimposed on tempo-synchronized music when the peak tibial acceleration was ≥70% of the runner's baseline. The control group received tempo-synchronized music, which acted as a placebo for blinding purposes. Speed feedback was provided to obtain a stable running speed of ~2.9 m·s^-1 . Peak tibial acceleration and running cadence were evaluated.

RESULTS

A significant group by feedback interaction effect was detected for peak tibial acceleration. The experimental group had a decrease in peak tibial acceleration by 25.5% (mean: 10.9±2.8 g versus 8.1±3.9 g, p=0.008, d=1.08, mean difference = 2.77 [0.94, 4.61]) without changing the running cadence. The control group had no change in peak tibial acceleration nor in running cadence.

CONCLUSION

The retraining protocol was effective at reducing the peak tibial acceleration in high-impact runners by reacting to music-based biofeedback that was provided in real-time per wearable technology in a training environment. This reduction magnitude may have meaningful influences on injury risk.

CARL: a running recognition algorithm for free-living accelerometer data

Wearable accelerometers hold great promise for physical activity epidemiology and sports biomechanics. However, identifying and extracting data from specific physical activities, such as running, remains challenging.Objective. To develop and validate an algorithm to identify bouts of running in raw, free-living accelerometer data from devices worn at the wrist or torso (waist, hip, chest).Approach. The CARL (continuous amplitude running logistic) classifier identifies acceleration data with amplitude and frequency characteristics consistent with running. The CARL classifier was trained on data from 31 adults wearing accelerometers on the waist and wrist, then validated on free-living data from 30 new, unseen subjects plus 166 subjects from previously-published datasets using different devices, wear locations, and sample frequencies.Main results. On free-living data, the CARL classifier achieved mean accuracy (F₁score) of 0.984 (95% confidence interval 0.962-0.996) for data from the waist and 0.994 (95% CI 0.991-0.996) for data from the wrist. In previously-published datasets, the CARL classifier identified running with mean accuracy (F₁score) of 0.861 (95% CI 0.836-0.884) for data from the chest, 0.911 (95% CI 0.884-0.937) for data from the hip, 0.916 (95% CI 0.877-0.948) for data from the waist, and 0.870 (95% CI 0.834-0.903) for data from the wrist. Misclassification primarily occurred during activities with similar torso acceleration profiles to running, such as rope jumping and elliptical machine use.Significance. The CARL classifier can accurately identify bouts of running as short as three seconds in free-living accelerometry data. An open-source implementation of the CARL classifier is available atgithub.com/johnjdavisiv/carl.

Reliability and Validity of Running Cadence and Stance Time Derived from Instrumented Wireless Earbuds

Instrumented earbuds equipped with accelerometers were developed in response to limitations of currently used running wearables regarding sensor location and feedback delivery. The aim of this study was to assess test-retest reliability, face validity and concurrent validity for cadence and stance time in running. Participants wore an instrumented earbud (new method) while running on a treadmill with embedded force-plates (well-established method). They ran at a range of running speeds and performed several instructed head movements while running at a comfortable speed. Cadence and stance time were derived from raw earbud and force-plate data and compared within and between both methods using t-tests, ICC and Bland-Altman analysis. Test-retest reliability was good-to-excellent for both methods. Face validity was demonstrated for both methods, with cadence and stance time varying with speed in to-be-expected directions. Between-methods agreement for cadence was excellent for all speeds and instructed head movements. For stance time, agreement was good-to-excellent for all conditions, except while running at 13 km/h and shaking the head. Overall, the measurement of cadence and stance time using an accelerometer embedded in a wireless earbud showed good test-retest reliability, face validity and concurrent validity, indicating that instrumented earbuds may provide a promising alternative to currently used wearable systems.

Objective assessment of fast bowling delivery intensity in amateur male cricketers

Wearable microtechnology is effective in detecting fast deliveries in cricket, however methods to quantify delivery intensity have not been established. This study aimed to investigate the utility of wearable sensors in quantifying cricket fast bowling intensity.Fifteen sub-elite male fast bowlers performed deliveries at warm-up, match, and maximal intensities. A principal component analysis resulted in the selection of perceived exertion and seven variables of bowling exertion derived from trunk- (PlayerLoad™, trunk flexion velocity, trunk forward rotation velocity) and tibia-mounted (tibial acceleration at back foot contact, front foot contact, back foot re-contact and front foot re-contact) inertial measurement units for further analysis. Repeated measures ANOVAs were used to investigate the effect of intensity on outcome variables. Significant main effects of intensity and large effect sizes were identified for all variables (p < .05, n_p² > 0.14). Measures from the match and maximal conditions were significantly larger compared with the warm-up condition (P_holm < .05). No differences were observed between the match and maximal conditions (p > .05). Inertial measurement metrics can distinguish between a warm-up effort and both match and maximal fast bowling delivery intensity. These devices provide a unique, time-efficient approach to cricket fast bowling exertion quantification.

The Use of Wearable Sensor Technology to Detect Shock Impacts in Sports and Occupational Settings: A Scoping Review

Shock impacts during activity may cause damage to the joints, muscles, bones, or inner organs. To define thresholds for tolerable impacts, there is a need for methods that can accurately monitor shock impacts in real-life settings. Therefore, the main aim of this scoping review was to present an overview of existing methods for assessments of shock impacts using wearable sensor technology within two domains: sports and occupational settings. Online databases were used to identify papers published in 2010-2020, from which we selected 34 papers that used wearable sensor technology to measure shock impacts. No studies were found on occupational settings. For the sports domain, accelerometry was the dominant type of wearable sensor technology utilized, interpreting peak acceleration as a proxy for impact. Of the included studies, 28 assessed foot strike in running, head impacts in invasion and team sports, or different forms of jump landings or plyometric movements. The included studies revealed a lack of consensus regarding sensor placement and interpretation of the results. Furthermore, the identified high proportion of validation studies support previous concerns that wearable sensors at present are inadequate as a stand-alone method for valid and accurate data on shock impacts in the field.

Treadmill and Running Speed Effects on Acceleration Impacts: Curved Non-Motorized Treadmill vs. Conventional Motorized Treadmill

An increase in the popularity of running can be seen over the last decades, with a large number of injuries on it. Most of the running injuries are related to impact accelerations and are due to overuse. In order to reduce the risk of injury or to improve performance and health new treadmill designs have been created, as it can be the curved non-motorized treadmill. The aim of this study was to analyse impact accelerations, spatio-temporal parameters and perceptual differences while running on curved non-motorized treadmill (cNMT) compared to motorized treadmill (MT) at different speeds. Therefore, 27 recreational runners completed two tests consisting of 10 min warm-up and three bouts of 8 min running at 2.77 m/s, 3.33 m/s and self-selected speed on cNMT and MT, previously randomised. Although the surface did not influence spatio-temporal parameters, a reduction in impact accelerations, head acceleration rate (mean effect size [ES] = 0.86), tibia peak (mean ES = 0.45) and tibia magnitude (mean ES = 0.55), was observed while running on cNMT in comparison with running on MT. Moreover, higher heart rate (HR) (mean ES = 0.51) and rating of perceived effort (RPE) (mean ES = 0.34) were found while running on cNMT. These findings demonstrated that higher intensity training and lower impact accelerations are experimented on cNMT, what can be used by trainers and athletes while planning training sessions.

The Effect of Footwear, Running Speed, and Location on the Validity of Two Commercially Available Inertial Measurement Units During Running

Introduction: Most running-related injuries are believed to be caused by abrupt changes in training load, compounded by biomechanical movement patterns. Wearable technology has made it possible for runners to quantify biomechanical loads (e.g., peak positive acceleration; PPA) using commercially available inertial measurement units (IMUs). However, few devices have established criterion validity. The aim of this study was to assess the validity of two commercially available IMUs during running. Secondary aims were to determine the effect of footwear, running speed, and IMU location on PPA.

Materials and Methods: Healthy runners underwent a biomechanical running analysis on an instrumented treadmill. Participants ran at their preferred speed in three footwear conditions (neutral, minimalist, and maximalist), and at three speeds (preferred, +10%, −10%) in the neutral running shoes. Four IMUs were affixed at the distal tibia (IMeasureU-Tibia), shoelaces (RunScribe and IMeasureU-Shoe), and insole (Plantiga) of the right shoe. Pearson correlations were calculated for average vertical loading rate (AVLR) and PPA at each IMU location.

Results: The AVLR had a high positive association with PPA (IMeasureU-Tibia) in the neutral and maximalist (r = 0.70–0.72; p ≤ 0.001) shoes and in all running speed conditions (r = 0.71–0.83; p ≤ 0.001), but low positive association in the minimalist (r = 0.47; p < 0.05) footwear condition. Conversely, the relationship between AVLR and PPA (Plantiga) was high in the minimalist (r = 0.75; p ≤ 0.001) condition and moderate in the neutral (r = 0.50; p < 0.05) and maximalist (r = 0.57; p < 0.01) footwear. The RunScribe metrics demonstrated low to moderate positive associations (r = 0.40–0.62; p < 0.05) with AVLR across most footwear and speed conditions.

Discussion: Our findings indicate that the commercially available Plantiga IMU is comparable to a tibia-mounted IMU when acting as a surrogate for AVLR. However, these results vary between different levels of footwear and running speeds. The shoe-mounted RunScribe IMU exhibited slightly lower positive associations with AVLR. In general, the relationship with AVLR improved for the RunScribe sensor at slower speeds and improved for the Plantiga and tibia-mounted IMeasureU sensors at faster speeds.

Principal Component Analysis of the Running Ground Reaction Forces With Different Speeds

Ground reaction force (GRF) is a key metric in biomechanical research, including parameters of loading rate (LR), first impact peak, second impact peak, and transient between first and second impact peaks in heel strike runners. The GRFs vary over time during stance. This study was aimed to investigate the variances of GRFs in rearfoot striking runners across incremental speeds. Thirty female and male runners joined the running tests on the instrumented treadmill with speeds of 2.7, 3.0, 3.3, and 3.7 m/s. The discrete parameters of vertical average loading rate in the current study are consistent with the literature findings. The principal component analysis was modeled to investigate the main variances (95%) in the GRFs over stance. The females varied in the magnitude of braking and propulsive forces (PC1, 84.93%), whereas the male runners varied in the timing of propulsion (PC1, 53.38%). The female runners dominantly varied in the transient between the first and second peaks of vertical GRF (PC1, 36.52%) and LR (PC2, 33.76%), whereas the males variated in the LR and second peak of vertical GRF (PC1, 78.69%). Knowledge reported in the current study suggested the difference of the magnitude and patterns of GRF between male and female runners across different speeds. These findings may have implications for the prevention of sex-specific running-related injuries and could be integrated with wearable signals for the in-field prediction and estimation of impact loadings and GRFs.

Validity and Reliability of an Instrumented Treadmill with an Accelerometry System for Assessment of Spatio-Temporal Parameters and Impact Transmission

Running retraining programs focused on concurrent feedback of acceleration impacts have been demonstrated to be a good strategy to reduce running-related injuries (RRI), as well as to improve running economy and reduce acceleration impacts and injury running incidence. Traditionally, impacts have been registered by mean of accelerometers attached directly to the athletes, which is inaccessible to the entire population, because it requires laboratory conditions. This study investigated the validity and reliability of a new device integrated directly into the treadmill, compared to a traditional acceleration impact system. Thirty healthy athletes with no history of RRI were tested on two separate days over the instrumented treadmill (AccTrea) and simultaneously with an acceleration impact system attached to the participant (AccAthl). AccTrea was demonstrated to be a valid and reliable tool for measuring spatio-temporal parameters like step length (validity intraclass correlation coefficient (ICC) = 0.94; reliability ICC = 0.92), step time (validity ICC = 0.95; reliability ICC = 0.96), and step frequency (validity ICC = 0.95; reliability ICC = 0.96) during running. Peak acceleration impact variables showed a high reliability for the left (reliability ICC = 0.88) and right leg (reliability ICC = 0.85), and peak impact asymmetry showed a modest validity (ICC = 0.55). These results indicated that the AccTrea system is a valid and reliable way to assess spatio-temporal variables, and a reliable tool for measuring acceleration impacts during running.

Music-based biofeedback to reduce tibial shock in over-ground running: a proof-of-concept study

Methods to reduce impact in distance runners have been proposed based on real-time auditory feedback of tibial acceleration. These methods were developed using treadmill running. In this study, we extend these methods to a more natural environment with a proof-of-concept. We selected ten runners with high tibial shock. They used a music-based biofeedback system with headphones in a running session on an athletic track. The feedback consisted of music superimposed with noise coupled to tibial shock. The music was automatically synchronized to the running cadence. The level of noise could be reduced by reducing the momentary level of tibial shock, thereby providing a more pleasant listening experience. The running speed was controlled between the condition without biofeedback and the condition of biofeedback. The results show that tibial shock decreased by 27% or 2.96 g without guided instructions on gait modification in the biofeedback condition. The reduction in tibial shock did not result in a clear increase in the running cadence. The results indicate that a wearable biofeedback system aids in shock reduction during over-ground running. This paves the way to evaluate and retrain runners in over-ground running programs that target running with less impact through instantaneous auditory feedback on tibial shock.

Implications of sample size and acquired number of steps to investigate running biomechanics

Low reproducibility and non-optimal sample sizes are current concerns in scientific research, especially within human movement studies. Therefore, this study aimed to examine the implications of different sample sizes and number of steps on data variability and statistical outcomes from kinematic and kinetics running biomechanical variables. Forty-four participants ran overground using their preferred technique (normal) and minimizing the contact sound volume (silent). Running speed, peak vertical, braking forces, and vertical average loading rate were extracted from > 40 steps/runner. Data stability was computed using a sequential estimation technique. Statistical outcomes (p values and effect sizes) from the comparison normal vs silent running were extracted from 100,000 random samples, using various combinations of sample size (from 10 to 40 runners) and number of steps (from 5 to 40 steps). The results showed that only 35% of the study sample could reach average stability using up to 10 steps across all biomechanical variables. The loading rate was consistently significantly lower during silent running compared to normal running, with large effect sizes across all combinations. However, variables presenting small or medium effect sizes (running speed and peak braking force), required > 20 runners to reach significant differences. Therefore, varying sample sizes and number of steps are shown to influence the normal vs silent running statistical outcomes in a variable-dependent manner. Based on our results, we recommend that studies involving analysis of traditional running biomechanical variables use a minimum of 25 participants and 25 steps from each participant to provide appropriate data stability and statistical power.

Predicting gait events from tibial acceleration in rearfoot running: A structured machine learning approach

BACKGROUND

Gait event detection of the initial contact and toe off is essential for running gait analysis, allowing the derivation of parameters such as stance time. Heuristic-based methods exist to estimate these key gait events from tibial accelerometry. However, these methods are tailored to very specific acceleration profiles, which may offer complications when dealing with larger data sets and inherent biological variability.

RESEARCH QUESTION

Can a structured machine learning approach achieve a more accurate prediction of running gait event timings from tibial accelerometry, compared to the previously utilised heuristic approaches?

METHODS

Force-based event detection acted as the criterion measure in order to assess the accuracy, repeatability and sensitivity of the predicted gait events. 3D tibial acceleration and ground reaction force data from 93 rearfoot runners were captured. A heuristic method and two structured machine learning methods were employed to derive initial contact, toe off and stance time from tibial acceleration signals.

RESULTS

Both a structured perceptron model (median absolute error of stance time estimation: 10.00 ± 8.73 ms) and a structured recurrent neural network model (median absolute error of stance time estimation: 6.50 ± 5.74 ms) significantly outperformed the existing heuristic approach (median absolute error of stance time estimation: 11.25 ± 9.52 ms). Thus, results indicate that a structured recurrent neural network machine learning model offers the most accurate and consistent estimation of the gait events and its derived stance time during level overground running.

SIGNIFICANCE

The machine learning methods seem less affected by intra- and inter-subject variation within the data, allowing for accurate and efficient automated data output during rearfoot overground running. Furthermore offering possibilities for real-time monitoring and biofeedback during prolonged measurements, even outside the laboratory.

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 (R_s = 0.86, p < 0.001) and peak lateral tibial accelerations were correlated with peak medial loading rates (R_s = 0.91, p < 0.001). A lower correlation was found between anterior accelerations and posterior loading rates (R_s = 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.

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.

Tibial Acceleration Reliability and Minimal Detectable Difference During Overground and Treadmill Running

Measurements of tibial acceleration during running must be reliable to ensure valid results and reduce errors. The purpose of this study was to determine the reliability and minimal detectable difference (MDD) of peak axial and peak resultant tibial acceleration during overground and treadmill running. The authors also compared reliability and MDDs when peak tibial accelerations were determined by averaging 5 or 10 trials. Tibial acceleration was measured during overground and treadmill running of 19 participants using a lightweight accelerometer mounted to the tibia. Peak axial and peak resultant tibial accelerations were determined for each trial. Intraclass correlation coefficients determined within-session reliability, and MDDs were also calculated. Within-session reliability was excellent for all conditions (intraclass correlation coefficients = .95-.99). The MDDs ranged from 0.6 to 1.4 g for peak axial acceleration and from 1.6 to 2.0 g for peak resultant acceleration and were lowest for peak axial tibial acceleration during overground running. Averaging 10 trials did not improve reliability compared to averaging 5 trials but did result in small reductions in MDDs. For peak axial tibial acceleration only, lower MDDs indicate that overground running may be the better option for detecting small differences.

Effects of Wearable Devices with Biofeedback on Biomechanical Performance of Running-A Systematic Review

This present review includes a systematic search for peer-reviewed articles published between March 2009 and March 2020 that evaluated the effects of wearable devices with biofeedback on the biomechanics of running. The included articles did not focus on physiological and metabolic metrics. Articles with patients, animals, orthoses, exoskeletons and virtual reality were not included. Following the PRISMA guidelines, 417 articles were first identified, and nineteen were selected following the removal of duplicates and articles which did not meet the inclusion criteria. Most reviewed articles reported a significant reduction in positive peak acceleration, which was found to be related to tibial stress fractures in running. Some previous studies provided biofeedback aiming to increase stride frequencies. They produced some positive effects on running, as they reduced vertical load in knee and ankle joints and vertical displacement of the body and increased knee flexion. Some other parameters, including contact ground time and speed, were fed back by wearable devices for running. Such devices reduced running time and increased swing phase time. This article reviews challenges in this area and suggests future studies can evaluate the long-term effects in running biomechanics produced by wearable devices with biofeedback.

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.

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 (ICC_3,1) 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.

Change-Point Detection of Peak Tibial Acceleration in Overground Running Retraining

A method is presented for detecting changes in the axial peak tibial acceleration while adapting to self-discovered lower-impact running. Ten runners with high peak tibial acceleration were equipped with a wearable auditory biofeedback system. They ran on an athletic track without and with real-time auditory biofeedback at the instructed speed of 3.2 m·s^-1. Because inter-subject variation may underline the importance of individualized retraining, a change-point analysis was used for each subject. The tuned change-point application detected major and subtle changes in the time series. No changes were found in the no-biofeedback condition. In the biofeedback condition, a first change in the axial peak tibial acceleration occurred on average after 309 running gait cycles (3'40"). The major change was a mean reduction of 2.45 g which occurred after 699 running gait cycles (8'04") in this group. The time needed to achieve the major reduction varied considerably between subjects. Because of the individualized approach to gait retraining and its relatively quick response due to a strong sensorimotor coupling, we want to highlight the potential of a stand-alone biofeedback system that provides real-time, continuous, and auditory feedback in response to the axial peak tibial acceleration for lower-impact running.

Tibial Acceleration-Based Prediction of Maximal Vertical Loading Rate During Overground Running: A Machine Learning Approach

Ground reaction forces are often used by sport scientists and clinicians to analyze the mechanical risk-factors of running related injuries or athletic performance during a running analysis. An interesting ground reaction force-derived variable to track is the maximal vertical instantaneous loading rate (VILR). This impact characteristic is traditionally derived from a fixed force platform, but wearable inertial sensors nowadays might approximate its magnitude while running outside the lab. The time-discrete axial peak tibial acceleration (APTA) has been proposed as a good surrogate that can be measured using wearable accelerometers in the field. This paper explores the hypothesis that applying machine learning to time continuous data (generated from bilateral tri-axial shin mounted accelerometers) would result in a more accurate estimation of the VILR. Therefore, the purpose of this study was to evaluate the performance of accelerometer-based predictions of the VILR with various machine learning models trained on data of 93 rearfoot runners. A subject-dependent gradient boosted regression trees (XGB) model provided the most accurate estimates (mean absolute error: 5.39 ± 2.04 BW⋅s^–1, mean absolute percentage error: 6.08%). A similar subject-independent model had a mean absolute error of 12.41 ± 7.90 BW⋅s^–1 (mean absolute percentage error: 11.09%). All of our models had a stronger correlation with the VILR than the APTA (p < 0.01), indicating that multiple 3D acceleration features in a learning setting showed the highest accuracy in predicting the lab-based impact loading compared to APTA.