The Influence of External Additional Loading on the Muscle Activity and Ground Reaction Forces during Gait.
Ontology highlight
ABSTRACT:
SUBMITTER: Zagrodny B
PROVIDER: S-EPMC8342170 | biostudies-literature | 2021
REPOSITORIES: biostudies-literature
Publications
The Influence of External Additional Loading on the Muscle Activity and Ground Reaction Forces during Gait.
Zagrodny Bartłomiej B Ludwicki Michał M Wojnicz Wiktoria W
Applied bionics and biomechanics 20210729
Asymmetrical external loading acting on the musculoskeletal system is generally considered unhealthy. Despite this knowledge, carrying loads in an asymmetrical manner like carrying on one shoulder, with one hand, or on the strap across the torso is a common practice. This study is aimed at presenting the effects of the mentioned load carrying methods on muscle activity assessed by using thermal field and ground reaction forces. Infrared thermography and pedobarographic force platform (ground rea ...[more]
Similar Datasets
Project description:Though gait asymmetry is used as a metric of functional recovery in clinical rehabilitation, there is no consensus on an ideal method for its evaluation. Various methods have been proposed to analyze single bilateral signals but are limited in scope, as they can often use only positive signals or discrete values extracted from time-scale data as input. By defining five symmetry axioms, a framework for benchmarking existing methods was established and a new method was described here for the first time: the weighted universal symmetry index (wUSI), which overcomes limitations of other methods. Both existing methods and the wUSI were mathematically compared to each other and in respect to their ability to fulfill the proposed symmetry axioms. Eligible methods that fulfilled these axioms were then applied using both discrete and continuous approaches to ground reaction force (GRF) data collected from healthy gait, both with and without artificially induced asymmetry using a single instrumented elbow crutch. The wUSI with a continuous approach was the only symmetry method capable of identifying GRF asymmetry differences in different walking conditions in all three planes of motion. When used with a continuous approach, the wUSI method was able to detect asymmetries while avoiding artificial inflation, a common problem reported in other methods. In conclusion, the wUSI is proposed as a universal method to quantify three-dimensional GRF asymmetries, which may also be expanded to other biomechanical signals.
| S-EPMC7644861 | biostudies-literature
Project description:BACKGROUND:Sand is an easy-to-access, cost-free resource that can be used to treat pronated feet (PF). Therefore, the aims of this study were to contrast the effects of walking on stable ground versus walking on sand on ground reaction forces (GRFs) and electromyographic (EMG) activity of selected lower limb muscles in PF individuals compared with healthy controls. METHODS:Twenty-nine controls aged 22.2±2.5 years and 30 PF individuals aged 22.2±1.9 years were enrolled in this study. Participants walked at preferred speed and in randomized order over level ground and sand. A force plate was included in the walkway to collect GRFs. Muscle activities were recorded using EMG system. RESULTS:No statistically significant between-group differences were found in preferred walking speed when walking on stable ground (PF: 1.33±0.12 m/s; controls: 1.35±0.14 m/s; p = 0.575; d = 0.15) and sand (PF: 1.19±0.11 m/s; controls: 1.23±0.18 m/s; p = 0.416; d = 0.27). Irrespective of the group, walking on sand (1.21±0.15 m/s) resulted in significantly lower gait speed compared with stable ground walking (1.34±0.13 m/s) (p<0.001; d = 0.93). Significant main effects of "surface" were found for peak posterior GRFs at heel contact, time to peak for peak lateral GRFs at heel contact, and peak anterior GRFs during push-off (p<0.044; d = 0.27-0.94). Pair-wise comparisons revealed significantly smaller peak posterior GRFs at heel contact (p = 0.005; d = 1.17), smaller peak anterior GRFs during push-off (p = 0.001; d = 1.14), and time to peak for peak lateral GRFs (p = 0.044; d = 0.28) when walking on sand. No significant main effects of "group" were observed for peak GRFs and their time to peak (p>0.05; d = 0.06-1.60). We could not find any significant group by surface interactions for peak GRFs and their time to peak. Significant main effects of "surface" were detected for anterior-posterior impulse and peak positive free moment amplitude (p<0.048; d = 0.54-0.71). Pair-wise comparisons revealed a significantly larger peak positive free moment amplitude (p = 0.010; d = 0.71) and a lower anterior-posterior impulse (p = 0.048; d = 0.38) when walking on sand. We observed significant main effects of "group" for the variable loading rate (p<0.030; d = 0.59). Pair-wise comparisons revealed significantly lower loading rates in PF compared with controls (p = 0.030; d = 0.61). Significant group by surface interactions were observed for the parameter peak positive free moment amplitude (p<0.030; d = 0.59). PF individuals exhibited a significantly lower peak positive free moment amplitude (p = 0.030, d = 0.41) when walking on sand. With regards to EMG, no significant main effects of "surface", main effects of "group", and group by surface interactions were observed for the recorded muscles during the loading and push-off phases (p>0.05; d = 0.00-0.53). CONCLUSIONS:The observed lower velocities during walking on sand compared with stable ground were accompanied by lower peak positive free moments during the push-off phase and loading rates during the loading phase. Our findings of similar lower limb muscle activities during walking on sand compared with stable ground in PF together with lower free moment amplitudes, vertical loading rates, and lower walking velocities on sand may indicate more relative muscle activity on sand compared with stable ground. This needs to be verified in future studies.
| S-EPMC6762175 | biostudies-literature
Project description:Accelerometers are low-cost measurement devices that can readily be used outside the lab. However, determining isolated gait events from accelerometer signals, especially foot-off events during running, is an open problem. We outline a two-step approach where machine learning serves to predict vertical ground reaction forces from accelerometer signals, followed by force-based event detection. We collected shank accelerometer signals and ground reaction forces from 21 adults during comfortable walking and running on an instrumented treadmill. We trained one common reservoir computer using segmented data using both walking and running data. Despite being trained on just a small number of strides, this reservoir computer predicted vertical ground reaction forces in continuous gait with high quality. The subsequent foot contact and foot off event detection proved highly accurate when compared to the gold standard based on co-registered ground reaction forces. Our proof-of-concept illustrates the capacity of combining accelerometry with machine learning for detecting isolated gait events irrespective of mode of locomotion.
| S-EPMC9644164 | biostudies-literature
Project description:One of the most important forces generated during gait is the vertical ground reaction force (vGRF). This force can be measured using force plates, but these can limit the scope of gait analysis. This paper presents a method to estimate the vGRF using inertial measurement units (IMU) and machine learning techniques. Four wearable IMUs were used to obtain flexion/extension angles of the hip, knee, and ankle joints, and an IMU placed over the C7 vertebra to measure vertical acceleration. We trained and compared the performance of two machine learning algorithms: feedforward neural networks (FNN) and random forest (RF). We investigated the importance of the inputs introduced into the models and analyzed in detail the contribution of lower limb kinematics and vertical acceleration to model performance. The results suggest that the inclusion of vertical acceleration increases the root mean square error in the FNN, while the RF appears to decrease it. We also analyzed the ability of the models to construct the force signal, with particular emphasis on the magnitude and timing of the vGRF peaks. Using the proposed method, we concluded that FNN and RF models can estimate the vGRF with high accuracy.
| S-EPMC10570513 | biostudies-literature
Project description:Diabetic neuropathy (DN) is one of the prevalent forms of neuropathy that involves alterations in biomechanical changes in the human gait. Diabetic foot ulceration (DFU) is one of the pervasive types of complications that arise due to DN. In the literature, for the last 50 years, researchers have been trying to observe the biomechanical changes due to DN and DFU by studying muscle electromyography (EMG) and ground reaction forces (GRF). However, the literature is contradictory. In such a scenario, we propose using Machine learning techniques to identify DN and DFU patients by using EMG and GRF data. We collected a dataset from the literature which involves three patient groups: Control (n = 6), DN (n = 6), and previous history of DFU (n = 9) and collected three lower limb muscles EMG (tibialis anterior (TA), vastus lateralis (VL), gastrocnemius lateralis (GL)), and three GRF components (GRFx, GRFy, and GRFz). Raw EMG and GRF signals were preprocessed, and different feature extraction techniques were applied to extract the best features from the signals. The extracted feature list was ranked using four different feature ranking techniques, and highly correlated features were removed. In this study, we considered different combinations of muscles and GRF components to find the best performing feature list for the identification of DN and DFU. We trained eight different conventional ML models: Discriminant analysis classifier (DAC), Ensemble classification model (ECM), Kernel classification model (KCM), k-nearest neighbor model (KNN), Linear classification model (LCM), Naive Bayes classifier (NBC), Support vector machine classifier (SVM), and Binary decision classification tree (BDC), to find the best-performing algorithm and optimized that model. We trained the optimized the ML algorithm for different combinations of muscles and GRF component features, and the performance matrix was evaluated. Our study found the KNN algorithm performed well in identifying DN and DFU, and we optimized it before training. We found the best accuracy of 96.18% for EMG analysis using the top 22 features from the chi-square feature ranking technique for features from GL and VL muscles combined. In the GRF analysis, the model showed 98.68% accuracy using the top 7 features from the Feature selection using neighborhood component analysis for the feature combinations from the GRFx-GRFz signal. In conclusion, our study has shown a potential solution for ML application in DN and DFU patient identification using EMG and GRF parameters. With careful signal preprocessing with strategic feature extraction from the biomechanical parameters, optimization of the ML model can provide a potential solution in the diagnosis and stratification of DN and DFU patients from the EMG and GRF signals.
| S-EPMC9100406 | biostudies-literature
Project description:Underwater walking was a crucial step in the evolutionary transition from water to land. Underwater walkers use fins and/or limbs to interact with the benthic substrate and produce propulsive forces. The dynamics of underwater walking remain poorly understood due to the lack of a sufficiently sensitive and waterproof system to measure substrate reaction forces (SRFs). Using an underwater force plate (described in our companion paper), we quantify SRFs during underwater walking in axolotls (Ambystoma mexicanum) and Spot prawn (Pandalus platyceros), synchronized with videography. The horizontal propulsive forces were greater than the braking forces in both species to overcome hydrodynamic drag. In axolotls, potential energy (PE) fluctuations were far smaller than kinetic energy (KE) fluctuations due to high buoyant support (97%), whereas the magnitudes were similar in the prawn due to lower buoyant support (93%). However, both species show minimal evidence of exchange between KE and PE, which, along with the effects of hydrodynamic drag, is incompatible with inverted pendulum dynamics. Our results show that, despite their evolutionary links, underwater walking has fundamentally different dynamics compared with terrestrial walking and emphasize the substantial consequences of differences in body plan in underwater walking.
| S-EPMC11191838 | biostudies-literature
Project description:Despite being a key concept in rehabilitation, controlling weight-bearing load while walking, following lower limb injury is very hard to achieve. Walking in water provides an opportunity to prescribe load for people who have pain, weakness or weight bearing restrictions related to stages of healing. The aim of this experimental study was to evaluate and validate regression models for predicting ground reaction forces while walking in water. One hundred and thirty seven individuals (24±5 years, 1.71±0.08 m and 68.7±12.5 kg) were randomly assigned to a regression group (n = 113) and a validation group (n = 24). Trials were performed at a randomly assigned water depth (0.75 to 1.35 m), and at a self-selected speed. Independent variables were: immersion ratio, velocity, body mass, and waist, thigh and leg circumferences. Stepwise regression was used for the prediction of ground reaction forces and validation included agreement and consistency statistical analyses. Data from a force plate were compared with predicted data from the created model in the validation group. Body mass, immersion ratio, and velocity independently predicted 95% of the vertical and resultant ground reaction force variability, while, together, velocity and thigh circumference explained 81% of antero-posterior ground reaction force variability. When tested against the data measured in validation samples, the models output resulted in statistically similar values, intraclass correlation coefficients ranging from 0.88 to 0.90 and standard errors of measurement, 11.8 to 42.3 N. The models introduced in this study showed good predictive performance in our evaluation procedures and may be considered valid in the prediction of vertical, antero-posterior and resultant ground reaction forces while walking in water. All predictive variables can be easily determined in clinical practice. Future studies should focus on the validation of these models in specific populations.
| S-EPMC6638929 | biostudies-literature
Project description:Background:Court shoe designs predominantly focus on reducing excessive vertical ground reaction force, but shear force cushioning has received little attention in the basketball population. We aimed to examine the effect of a novel shoe-cushioning design on both resultant horizontal ground reaction forces and comfort perception during two basketball-specific cutting movements. Methods:Fifteen university team basketball players performed lateral shuffling and 45-degree sidestep cutting at maximum effort in basketball shoes with and without the shear-cushioning system (SCS). Paired t-tests were used to examine the differences in kinetics and comfort perception between two shoes. Results:SCS shoe allowed for larger rotational material deformation compared with control shoes, but no significant shoe differences were found in braking phase kinetics during both cutting movements (P = 0.35). Interestingly, a greater horizontal propulsion impulse was found with the SCS during 45-degree cutting (P < 0.05), when compared with the control. In addition, players wearing SCS shoes perceived better forefoot comfort (P = 0.012). During lateral shuffling, there were no significant differences in horizontal GRF and comfort perception between shoe conditions (P > 0.05). Discussion:The application of a rotational shear-cushioning structure allowed for better forefoot comfort and enhanced propulsion performance in cutting, but did not influence the shear impact. Understanding horizontal ground reaction force information may be useful in designing footwear to prevent shear-related injuries in sport populations.
| S-EPMC5702506 | biostudies-literature
Project description:Femoral deformities, e.g. increased or decreased femoral anteversion (AVA) and neck-shaft angle (NSA), can lead to pathological gait patterns, altered joint loads, and degenerative joint diseases. The mechanism how femoral geometry influences muscle forces and joint load during walking is still not fully understood. The objective of our study was to investigate the influence of femoral AVA and NSA on muscle forces and joint loads during walking. We conducted a comprehensive musculoskeletal modelling study based on three-dimensional motion capture data of a healthy person with a typical gait pattern. We created 25 musculoskeletal models with a variety of NSA (93°-153°) and AVA (-12°-48°). For each model we calculated moment arms, muscle forces, muscle moments, co-contraction indices and joint loads using OpenSim. Multiple regression analyses were used to predict muscle activations, muscle moments, co-contraction indices, and joint contact forces based on the femoral geometry. We found a significant increase in co-contraction of hip and knee joint spanning muscles in models with increasing AVA and NSA, which led to a substantial increase in hip and knee joint contact forces. Decreased AVA and NSA had a minor impact on muscle and joint contact forces. Large AVA lead to increases in both knee and hip contact forces. Large NSA (153°) combined with large AVA (48°) led to increases in hip joint contact forces by five times body weight. Low NSA (108° and 93°) combined with large AVA (48°) led to two-fold increases in the second peak of the knee contact forces. Increased joint contact forces in models with increased AVA and NSA were linked to changes in hip muscle moment arms and compensatory increases in hip and knee muscle forces. Knowing the influence of femoral geometry on muscle forces and joint loads can help clinicians to improve treatment strategies in patients with femoral deformities.
| S-EPMC10569567 | biostudies-literature
Project description:ObjectivesThe aim of this study was to evaluate ground reaction forces (GRFs) in cats after unilateral total hip replacement (THR) and compare them with cats after femoral head and neck ostectomy (FHO).MethodsThe databases of the Small Animal Clinic of the Veterinary University in Vienna and three referral clinics were searched for cats that had undergone unilateral THR with the BioMedtrix Micro total hip system or FHO more than 6 months previously. Owners were invited to complete a survey and bring their cats for re-examination, inlcuding clinical and orthopaedic examinations, hip radiography and a gait analysis using a pressure-sensitive plate.ResultsNine cats were included in each group. Cats after THR showed larger GRF values (peak vertical force [PFz] and vertical impulse [IFz] normalised to total force [%TF]) on the operated limb. The resulting symmetry indices (SIs) were lower in terms of vertical force in 7/9 (78%) cats and vertical impulse in 6/9 (67%) cats between the hindlimbs in cats after THR compared with FHO - SI (PFz) = 3.31% ± 2.19% (THR) vs 4.84% ± 2.99% (FHO) and SI (IFz) = 5.17% ± 3.66% (THR) vs 8.27% ± 3.12% (FHO). Cats after FHO showed significantly lower muscle circumference and range of motion (ROM) at the operated hindlimb compared with the contralateral side, whereas cats after THR showed no statistically significant differences between their hindlimbs. Owner surveys revealed significant differences in their subjective assessment of activity and change in gait between the two groups, with better values for cats after THR.Conclusions and relevanceThis was the first study that measured GRFs in cats after THR. PFz (%TF) and IFz (%TF) values were higher in the operated limb of the THR group than in those of the FHO group, resulting in lower symmetry indices (indicating better symmetry) and better loading of the corresponding hindlimb. This finding is clinically relevant and can help in making decisions regarding the treatment of hip joint pathologies in cats.
| S-EPMC11662329 | biostudies-literature