Search Results (141)

Conventional ground reaction force (GRF) and load rate (LR) analyses may overlook temporal and waveform characteristics that reflect injury status and acuity. This study used an alternative GRF processing methodology to characterize GRF waveforms among runners with symptomatic medial tibial stress fractures (MTSS) and those recovering from tibial stress fractures (TSF; both unilateral [UL] and bilateral [BL]). This cross-sectional analysis of runners (n = 66) included four groups: symptomatic MTSS, recovering from UL or BL TSF, or uninjured case-matched controls. Participants ran at self-selected speed on an instrumented treadmill. Kinematics were collected with a 3D optical motion analysis system. Double-Gaussian models described the biphasic loading pattern of running gait (initial impact, active phases). Gaussian parameters described relative differences in the GRF waveform by injury condition. LR was calculated using the central difference numerical derivative of the raw normalized net force data. During the impact phase (0–20% of stance), controls and BL TSF produced higher GRF amplitudes than UL TSF and MTSS (p < 0.05). BL TSF and controls had greater maximal positive LR and minimum LR than UL TSF and MTSS. Peak medial GRF was 18–43% higher in the BL TSF group than in MTSS and UL TSF (p < 0.05). Correlations existed between tibial pain severity and early stance net GRF (r = 0.512; p = 0.016) and between pain severity and the duration since diagnosis for LR values during the impact phase (r values = 0.389–0.522; all p < 0.05). Collectively, these data suggest that this waveform modeling approach can differentiate injury status and pain acuity in runners. Early stance GRF and LR may offer novel insight into the management of running-related injuries. Full article

Understanding the foot strike pattern (FSP) and impact force of running-related injuries is crucial for athletes and researchers. This study investigated a novel method for detecting FSP using the loadsol^® sensor insole during treadmill running. Twelve collegiate athletes ran at three different speeds (12, 15, and 20 km/h), with their FSP determined using both the kinematic method based on the foot strike angle and the loadsol^® method based on the plantar force applied to the rear-, mid-, and forefoot sensor areas. This study provides significant insights into FSP detection. Comparing the kinematic method to the loadsol^® method, the rearfoot, midfoot, and forefoot strike detection rates were 94.7%, 37.1%, and 81.8%, respectively. Moreover, the FSP was not uniform, even during treadmill running at a constant speed, with most participants exhibiting mixed patterns across different speeds. The loadsol^® sensor insole could offer a promising device for in-field measurement of FSP and impact forces, potentially helping researchers and athletes better understand and predict the potential running-related injury risks by monitoring step-to-step variations in running biomechanics. Full article

Background: Dog agility is a rapidly growing sport involving a partnership between a dog and the handler, running through an obstacle course. Despite its increasing popularity and physical benefits, research on handler injuries remains limited. This study aimed to assess injury epidemiology of athletes practicing dog agility. Methods: This cross-sectional study was conducted using a comprehensive online survey consisting of 124 items, available in both English and Italian. The questionnaire was divided into four sections: Introduction collected demographic data and medical history; Materials and Methods focused on agility-related activities; Results explored injuries sustained in the past 12 months; Discussion examined training habits unrelated to agility. Results: Among 389 participants, the most represented age group ranged between 30 and 40 years old. Overall, 7% reported upper limb injuries, while 27% experienced at least one lower limb injury. Additionally, 20% of participants used medication, and 25% reported at least one chronic illness. On average, handlers trained twice per week and competed in two events per month. Lower limb injuries were predominantly muscular (49%) or ligamentous (14%) and most commonly occurred on grass pitches (56%). These injuries were more common in participants with a higher BMI, those using dynamic handling styles, and those competing at higher levels. Conclusions: This cross-sectional study highlighted the importance of identifying risk factors associated with dog agility handlers. Lower limb injuries were the most common, often associated with increased physical demands and handling styles involving intensive running and correlated with reduced physical fitness. Athletic conditioning, including structured warm-up and cool-down practices, might help decline injury risks. Full article

Vertical ground reaction force (vGRF) plays an important role in the study of running-related injuries (RRIs). This study explores the synchronization method between inertial measurement unit (IMU) and vGRF data of running and develops ANN models to accurately predict vGRF. Fifteen runners participated in this study. Acceleration data and vGRF values of eight rearfoot strikers and seven forefoot strikers running at 12, 14, and 16 km/h were collected by a single IMU and an instrumented treadmill. The sliding time window synchronization (STWS) algorithm was developed to sync IMU data with vGRF data. The wavelet neural network model (WNN) and feed-forward neural network model (FFNN) were adapted to predict vGRF using three-axis or sagittal-axis acceleration data in the stance phase, respectively. One rearfoot striker and one forefoot striker were randomly selected as a test set, while the other participants formed training sets. After synchronization, mean absolute errors for stride time of the IMU and vGRF data were less than 11.2 ms. The coefficient of multiple correlations for vGRF measured curves and predicted curves was more than 0.97. The normalized root mean square errors (NRMSEs) between two curves were 4.6~9.2%, and R² was 0.93~0.99. For peak vGRF, the NRMSEs were 1.6~8.2%, except for rearfoot strike runners at 16 km/h using the FFNN model (10.7% and 11.1%). The Bland–Altman plots indicate that the errors for both the WNN and FFNN models are within acceptable limits. The STWS algorithm can effectively achieve the data synchronization between the IMU and the force plate during running. Both WNN and FFNN models demonstrated good accuracy and agreement in predicting vGRF. Using sagittal-axis acceleration data may be an ideal model with good prediction accuracy and less input data. This work provides direction for developing ANN models of personalized monitoring of lower limb load. Full article

Background: To the best of the authors’ knowledge, the different injury mechanisms of the hamstring muscle group have not been defined in detail in men’s professional football. For this reason, the main aim of this study is to determine the mechanisms and contextual patterns associated with hamstring muscle group injuries in professional male football players in competition, using a systematic video analysis method. Methods: Video recordings of official matches from two consecutive seasons (2017/18 and 2018/19) of the Spanish First Division of Football (LaLiga^TM) were used for this research. The process to determine the moment of injury was carried out by two independent evaluators using an ad hoc observation tool and, subsequently, all relevant data were collected to detail the specific patterns of injury events observed. Results: In total, 78 cases of hamstring injuries were included for the final analysis of specific patterns. The most outstanding results were that, (1) although the sprint-related pattern (SP) is predominate (54%; 42 cases), the combined pattern 2 (COMB2) is another mechanism that appears frequently (26%; 20 cases), (2) within the SP, curved runs show a greater number of cases (52% of SP; 22 cases), (3) the majority of the injuries occur without contact (83%; 65 cases) and with the presence of the ball (88%; 69 cases), and finally, (4) the most injured positions were fullbacks/wingbacks (28%; 22 cases), central defenders (27%; 21 cases), and wingers/wide midfielders (23%; 18 cases). Conclusions: The SP remains the most frequent pattern in hamstring injuries; however, the present study presents other mechanisms that are also quite common and should be considered, such as curvilinear runs in SP and COMB2. Full article

This case report analyses the physiological changes of a nine-time world champion triathlete over a competitive season. The triathlete, aged 34, resumed training after a 3-month injury-related break. The study monitored key physiological variables at three points: pre-season (PRE), base period (BASE), and peak performance (PEAK). The athlete trained an average of 25,000 m swimming, 400 km cycling, and 90 km running weekly. Incremental cycling tests were performed at each stage, measuring power output, oxygen uptake (VO₂), ventilatory thresholds (VT1, VT2), muscle oxygen saturation (SmO₂), heart rate, and lactate levels. Results showed significant improvements in relative power output (+37.2% at VT1), VO₂ max (+12.6%), and body composition (body fat reduced from 10.43% to 7.33%). Heart rate and lactate concentration remained stable, while SmO₂ showed a greater difference between VT2 and peak performance. The triathlete achieved top-10 finishes in all key events, including a win at the Ironman 70.3 World Championship. The findings suggest that elite triathletes can regain peak performance after injury through structured training, with improvements in ventilatory efficiency and body composition contributing to better competition results. This study provides valuable insights for coaches on the recovery and performance optimization of elite triathletes. Full article

Background: Running-related injuries are often associated with biomechanical inefficiencies, particularly in the sagittal and frontal planes. This study evaluates the effects of three interventions—reduced heel-to-toe drop (HTD) shoes, increased cadence, and inversion foot orthoses—on key kinematic parameters: ankle dorsiflexion, knee flexion, and hip adduction (measured at foot strike and at their respective peak joint angles during the stance phase). Methods: Nineteen recreational runners (ten males and nine females; mean ± SD: age 26.4 ± 4.3 years; height 174.2 ± 7.8 cm; weight 68.3 ± 9.6 kg; BMI 22.5 ± 2.1 kg/m²) participated in a 3D motion capture study under five experimental conditions: baseline (10 mm HTD, no cadence adjustment, no foot orthoses), full intervention (5 mm HTD, +10% cadence, orthoses), and three partial interventions: HTD combined with orthoses, HTD combined with increased cadence, and cadence increase alone. Kinematic changes were analyzed for statistical significance. Results: The full intervention significantly increased ankle dorsiflexion at foot strike (from 8.11° to 10.44°; p = 0.005) and reduced peak knee flexion (from 45.43° to 43.07°; p = 0.003). Cadence adjustments consistently produced improvements, while orthoses and HTD alone showed effects on ankle flexion only. Conclusions: Combining structural (HTD and orthoses) and dynamic (cadence) modifications optimizes running biomechanics, providing evidence-based strategies for injury prevention and performance enhancement. Full article

Running-induced fatigue affects several biomechanical parameters, and yet few studies are focused on the acceleration spikes’ asymmetries. This study aimed to evaluate the effects of a 30 min run on lower limbs spikes’ asymmetries. Eighteen recreational runners (35.6 ± 7.5 years; seven women) performed a treadmill running protocol at a moderate speed and acceleration spikes’ asymmetries and kinematic (temporal) parameters were measured via accelerometers—on the tibias and sacrum—and photogrammetry. Acceleration spikes’ parameters were continuously measured and averaged per minute to assess the relationship between fatigue and acceleration spike asymmetries via a linear regression model. Right tibial acceleration spikes increased over time (r = 0.9; p < 0.001) and left tibia spikes decreased (r = 0.78; p < 0.001), with a rise in tibial load asymmetry from 9% to 25% at the end (r = 0.98; p < 0.001). This study suggest that fatigue affects the acceleration spikes of the two legs differently, with increasingly greater acceleration spikes in the right (dominant) leg. These findings should be considered, as greater asymmetries are related to overuse injuries and lower efficiency. Also, in studies focusing on running mechanics with fatigue, it is recommended that researchers collect data from both limbs, and not only from the right (dominant) leg. Full article

Adductor strains are prevalent injuries in professional soccer. The purpose of this study is to identify further evidence of characteristics associated with adductor injury. MLS and other worldwide leagues have differing styles of play warranting further investigation of injury mechanisms. A descriptive cohort study was conducted with a single professional team in the MLS. Injury data was collected between the 2016 to 2022 seasons to characterize adductor injury. Player position type, age, previous injury, and mechanism(s) of injury (MOI) were assessed to understand the injured population. Generalized estimating equations (GEEs) were utilized to assess the odds of future injury among the injured and non-injured populations. Adductor strains (n = 30) made up 15.5% of all soft-tissue, lower extremity injuries (n = 194) in a single MLS cohort. These injuries were the second most common defined soft-tissue, non-contact injury after hamstring strains (26.4%) and before quadricep strains (11.9%). Among the position types, 28% of defenders, 25% of goalkeepers, 21.4% of forwards, and 20.5% of midfielders experienced at least one adductor strain. The MOI most responsible for these injuries were overuse (30%), change of direction (26.7%), running (13.3%), and kicking (10%). Athletes with previous adductor injury had 167.2 times the odds of adductor injury in a future half-season compared to non-injured athletes. The findings from this study provide further descriptive evidence of player position types and mechanisms related to adductor strain. Insights into the nature of injury within an MLS team and support of previous evidence shows the prevalence of adductor injuries in elite soccer players. Full article

Objective: Our objective was to investigate the biomechanical and neuromuscular adaptations of the lower limbs during the landing phase of running under fatigue conditions. Methods: A controlled fatigue protocol was used to induce running-related fatigue in participants. Data were collected using a three-dimensional motion capture system, force platform analysis, and surface electromyography (sEMG). Kinematic variables, such as hip, knee, and ankle joint angles and range of motion, were analyzed alongside kinetic parameters, including vertical ground reaction forces (vGRFs) and joint moments. sEMG was used to measure the muscle activation levels of the rectus femoris, biceps femoris, tibialis anterior, and gastrocnemius, and to calculate antagonist coactivation ratios. Statistical analyses were performed to assess the differences in pre- and post-fatigue using paired t-tests, with a significance level set at α = 0.05, and FDR correction was applied to control for multiple comparisons. Results: Post-fatigue, hip and knee flexion angles at initial contact decreased by 4.5% and 4.8%, respectively (FDR-adjusted p = 0.023, 0.0157), while their range of motion increased significantly by 10.4% and 11.1% (FDR-adjusted p = 0.0115, 0.0063). The second vGRF peak increased by 2.1% post-fatigue (FDR-adjusted p = 0.0086), with no significant changes in the first vGRF peak (p > 0.05). Muscle activation levels significantly increased in the rectus femoris (10.7%), biceps femoris (8.3%), tibialis anterior (9.1%), and gastrocnemius (10.2%) (FDR-adjusted p < 0.05). The antagonist coactivation ratio significantly decreased in the early and late landing phases (FDR-adjusted p = 0.0033, 0.0057), reflecting neuromuscular adjustments to fatigue. Conclusions: Fatigue-induced adaptations in joint kinematics, muscle activation, and coactivation strategies optimize performance and stability but may increase mechanical stress on lower-limb joints, highlighting a need for targeted interventions to mitigate injury risk. Full article

Background: Variability in running mechanics, termed running variability, reflects the adaptability of the locomotor system to dynamic environments. Due to inconsistent findings in the literature, there is a research gap in understanding its role in injury. Objectives: This scoping review explores running variability’s influence on injury susceptibility, examining studies across various injury types, skill levels, methods, and analysis adhering to the guidelines outlined in the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews checklist (PRISMA-ScR). Eligibility criteria and sources of evidence: Twenty-one studies illustrating the complexity of running variability in relation to running-related injuries were selected from Web of Science, ScienceDirect, Google Scholar, and PubMed databases during December 2022 to June 2024. Results: There are significant differences in running variability between injured and healthy runners, with variability influenced by injury type, stage, and individual differences with varying levels of evidence. Out of 21 studies, 8 (38%) found no group differences, 11 (52%) noted higher running variability in injured participants, and 5 (24%) reported lower variability in injured than healthy subjects. The review was constrained by the diverse subjects, methods, tasks, and outcome variables across the studies. Conclusions: Currently, there is no standard normal range for running variability and abnormal variability is defined relative to control groups, though healthy controls can also show abnormal variability without injury in some study designs. Despite the absence of standardized running variability norms, wearable sensors offer insights into real-world running mechanics, presenting running variability as a potential predictor of running-related injuries. The review highlights the need for standardized protocols and further research to clarify running variability’s role in injury prediction and prevention, emphasizing the necessity of individualized approaches in training and rehabilitation. Future studies should aim to establish a causal relationship between running variability and injury susceptibility, focusing on identifying variability patterns that precede or follow an injury. This review sets the stage for developing evidence-based strategies to optimize running performance and minimize injury risks. Full article

Musculoskeletal injuries induced by high-intensity and repetitive physical activities represent one of the primary health concerns in the fields of public fitness and sports. Musculoskeletal injuries, often resulting from unscientific training practices, are particularly prevalent, with the tibia being especially vulnerable to fatigue-related damage. Current tibial load monitoring methods rely mainly on laboratory equipment and wearable devices, but datasets combining both sources are limited due to experimental complexities and signal synchronization challenges. Moreover, wearable-based algorithms often fail to capture deep signal features, hindering early detection and prevention of tibial fatigue injuries. In this study, we simultaneously collected data from laboratory equipment and wearable insole sensors during in-place running by volunteers, creating a dataset named WearLab-Leg. Based on this dataset, we developed a machine learning model integrating Temporal Convolutional Network (TCN) and Transformer modules to estimate vertical ground reaction force (vGRF) and tibia bone force (TBF) using insole pressure signals. Our model’s architecture effectively combines the advantages of local deep feature extraction and global modeling, and further introduces the Weight-MSELoss function to improve peak prediction performance. As a result, the model achieved a normalized root mean square error (NRMSE) of 7.33% for vGRF prediction and 10.64% for TBF prediction. Our dataset and proposed model offer a convenient solution for biomechanical monitoring in athletes and patients, providing reliable data and technical support for early warnings of fatigue-induced injuries. Full article

Temporal parameters are crucial for understanding running performance, especially in elite sports environments. Traditional measurement methods are often labor-intensive and not suitable for field conditions. This study seeks to provide greater clarity in parameter estimation using a single device by comparing it to the gold standard. Specifically, this study aims to investigate how the temporal parameters and vertical stiffness (K_vert) of running stride exerted by IMU sensors are related to the parameters of the smart insole for outdoor acquisition. Ten healthy male subjects performed four 60-meter high-speed runs. Data were collected using the WIMU PRO™ device and smart insoles. Contact time (CT) and flight time (FT) were identified, and K_vert was calculated using Morin’s method. Statistical analyses assessed data normality, correlations, and reliability. WIMU measured longer CT, with differences ranging from 26.3% to 38.5%, and shorter FT, with differences ranging from 27.3% to 54.5%, compared to smart insoles, across different running speeds. K_vert values were lower with WIMU, with differences ranging from 23.96% to 45.01% depending on the running activity, indicating significant differences (p < 0.001). Using these results, a multiple linear regression model was developed for the correction of WIMU’s K_vert values, improving the accuracy. The improved accuracy of K_vert measurements has significant implications for athletic performance. It provides sports scientists with a more reliable metric to estimate player fatigue, potentially leading to more effective training regimens and injury prevention strategies. This advancement is particularly valuable in team sports settings, where easy-to-use and accurate biomechanical assessments of multiple athletes are essential. Full article

Background:Running is one of the simplest and most popular forms of exercise. Biomechanical evaluation of running is one of the elements of evaluating running technique and, consequently, improving sports performance. Running uphill and downhill is one of the components of daily running but also an element of training used by recreational runners. The aim of this study is to optimize running training and minimize the risk of injury by identifying changes in the spatiotemporal structure of running at different inclinations. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. The protocol has been registered on the international platform INPLASY under the number INPLASY202430094U2. The search was conducted up to 30 March 2024 using the Scopus, PubMed, and Web of Science databases. Results: Spatiotemporal parameters were most frequently analyzed at 2.8–3.35 m/s velocities and inclinations in the range of −11% to 11%. Decreases in stride length (SL) and flight time (FT), and increases in step frequency (SF) were the most frequently reported changes from all parameters analyzed as a function of inclination and velocity. Significant increases or decreases in individual parameters were more often observed for positive inclination values than negative ones. Conclusions: The heterogeneous results of the study limit the possibility of determining the changes that occur in the spatiotemporal structure of the run under the impact of different inclinations. The variation in the results for negative inclination values indicates the different characteristics of running uphill and downhill. However, for uphill running, SF, SL, and FT are closely related to the increase in inclination. Full article

Background/Objectives: Falls and fractures are emerging as a near-pandemic and major global health concern, placing an enormous burden on ageing patients and public health economies. Despite the high risk of polypharmacy in the elderly patients, falls are usually attributed to age-related changes. For the “Individual Pharmacotherapy Management (IPM)” established at the University Hospital Halle, the IPM medication adjustments and their association with in-hospital fall prevention were analysed. Methods: On the basis of the most updated digital overall patient view via his inpatient electronic health record (EHR), IPM adapts each drug’s Summary of Product Characteristics to the patient’s condition. A retrospective pre-post intervention study in geriatric traumatology on ≥70 years old patients compared 200 patients before IPM implementation (CG) with 204 patients from the IPM intervention period (IG) for the entire medication list, organ, cardiovascular and vital functions and fall risk parameters. Results: Statistically similar baseline data allowed a comparison of the average 80-year-old patient with a mean of 11.1 ± 4.9 (CG) versus 10.4 ± 3.6 (IG) medications. The IPM adjusted for drug-drug interactions, drug-disease interactions, overdoses, anticholinergic burden, adverse drug reactions, esp. from opioids inducing increased intrasynaptic serotonin, psychotropic drugs, benzodiazepines, contraindications and missing prescriptions. IPM was associated with a significant reduction in in-hospital falls from 18 (9%) in CG to 3 (1.5%) in IG, a number needed to treat of 14, relative risk reduction 83%, OR 0.17 [95% CI 0.04; 0.76], p = 0.021 in multivariable regression analysis. Factors associated with falls were antipsychotics, digitoxin, corticosteroids, Würzburg pain drip (combination of tramadol, metamizole, metoclopramide), head injury, cognitive impairment and aspects of the Huhn Fall Risk Scale including urinary catheter. Conclusion: The results indicate medication risks constitute a major iatrogenic cause of falls in this population and support the use of EHR-based IPM in standard care for the prevention of falls in the elderly and for patient and drug safety. In terms of global efforts, IPM contributes to the running WHO and United Nations Decade of Healthy Ageing (2021–2030). Full article