ABSTRACT
Objective To analyze the difference in ground reaction force (GRF) between male and female runners and between left and right limbs using the one-dimensional statistical parametric mapping (SPM). Methods Thirty male and female runners participated the running test on force treadmill at the speed of 12 km/h. GRF of consecutive five steps were recorded. The independent-sample t test and paired-sample t test in the SPM package were used to check the male vs female and right limb vs left limb differences. Results Male and female runners showed inter-limb asymmetry in vertical average loading rate (VALR), and the VALR of male runners was significantly higher than that of female runners in the left limb, while no significant differences were found in the right limb. Male and female runners showed significant differences in the right vertical GRF during push-off and medial-lateral GRF during landing, while left medial-lateral GRF presented significant differences during landing and mid stance. Male runners showed right limb vs left limb significance in the anterior-posterior GRF during push-off, vertical GRF during landing and push-off and medial-lateral GRF during landing, while female runners exhibited right limb vs left limb significance in vertical GRF during landing and push-off. Conclusions This study introduced the application of SPM in statistical analysis of GRF, elaborated the procedures and theory, compared the test of time-series data in SPM and discrete value with traditional statistics, and discussed the difference and features in SPM and SnPM, thus providing references for the application in data analysis of sports biomechanics. Comparison in the male vs female and right limb vs left limb revealed the genders and inter-limb symmetrical differences in the landing, mid-stance and push-off phases during stance. The research findings laid the foundation for future investigation of mechanism in running related injuries and strategy of prevention and treatment.
ABSTRACT
Objective To establish the three-dimensional (3D) statistical shape model (SSM) of the foot, so as to reveal the 3D foot shape variations. Methods Foot data from 50 normal Chinese young males were used for 3D statistical shape modelling. Steps, including mesh registration of foot surface, axis alignment and principal component (PC) analysis (dimension reduction), were performed to obtain the parameterized foot shape (mean shape and standard deviation of PC). Results Through the principal component analysis (PCA), the 3D foot shape varied in the length and width (PC1, 48.01%), arch and dorsal height (PC2, 11.38%), and hallux abduction-adduction position (PC3, 7.48%). Conclusions Based on the parameterised 3D foot SSM, these datasets can be applied into the population-based shoe last manufacture, orthotics customization and quick diagnosis of foot disorders in clinic.
ABSTRACT
OpenSim musculoskeletal modelling has developed rapidly and been widely utilized due to its open-source. Apart from calculation of the basic kinematic and kinetic data, subject-specific OpenSim model could reveal information of neuromuscular control, muscle forces and geometry, and contact forces. Image-based model-ling of the neuromuscular control in pathological gait and ergonomic evaluation of the prostheses confirmed the reliability and feasibility, but limitations in time-consumption and foot-ankle modelling also existed. The subject-specific modelling of pathological gait could improve the accuracy and diversity of clinical biomechanics and medical engineering research. It could also reveal the pathological features, and provide scientific evidence to design specific and accurate protocols of motor function diagnosis and rehabilitation, health monitoring and evaluation, and ergonomic customization and assessment of devices, as well as future directions and implications in the research field.