The collision accident in collegiate football game was simulated based on the game video and the concussive impact on the head was analyzed. First, the collision motion of players was reproduced based on the video by using motion analysis, and the translational and rotational velocities, relative position and contact location of the struck and the striking players’ heads just before the collision were calculated. Then the data obtained were input to two helmeted finite element (FE) human head models as the initial condition, and the brain injury risk was evaluated by using the impact analysis. The FE helmet model was validated by a drop test of the helmet in which the head impactor was embedded. In the present study, two concussion suspected accident cases were analyzed; then the concussion was evaluated by ten mechanical parameters generated inside the skull caused by the collision. The injury risk evaluated by multi parameters belonged to the dangerous range that may cause concussion and was consistent with the diagnosis of the medical team doctor. The brain injury risk can be successfully estimated by the reconstructed simulation of the game video and FE analysis. To our knowledge, this study is the first attempt in Japan to estimate the brain injury risk systematically by a combination of game video analysis which is originally introduced for the players’ health care and FE analysis by helmeted human head model. In the future, brain injury risk caused by an accident can be evaluated with higher accuracy by analyzing more accident cases.
In this study, as a fundamental approach to realize orthotic device for patients with osteoarthritis of the knee considering screw home movement, bending and extension movements of lower thigh of able-bodied persons are analyzed and inherent screw home movement is examined. The analyzed extension movement of lower thigh with screw home movement is mathematically modeled and the structure of an orthotic device is proposed based on the model. It is confirmed by the simulation based on FEM analysis that the force acting on the leg when using the proposed orthotic device is helpful to realize normal screw home movement and valgus rotation, which is expected to be useful for patients with osteoarthritis of the knee.
The objective of this study was to develop a method to estimate thigh-calf contact force during heel-rise squatting posture, which is important for analyzing the kinetics of the lower limb during deep knee flexion; however, the measured forces varied widely among test subjects. We also considered joint angles, rather than only individual anthropometric, such as height, body weight (BW), or body mass index (BMI). We created estimation equations by a linear combination of both physical and posture parameters, and then performed the measurement experiment with 10 healthy males. Test subjects were asked to take a squatting posture, and to bend their upper bodies forward and backward. We measured thigh-calf contact force by placing a pressure distribution sensor sheet between the thigh and calf. At the same time, the joint angles were measured as estimation parameters. Coefficients of the estimating equations were determined to minimize the root mean square error of the estimated and measured values. We compared four estimation equations, using physical and posture parameters, as well as those selected from all parameters, which are easily measurable. As a result, the estimation accuracy improved by using both physical and posture parameters. The average magnitude of the thigh-calf contact force was 0.92±0.24BW, and the average error of estimation was 0.06BW. The error was 0.11BW by using only physical parameters, and was 0.15BW by using only posture parameters. Despite this, even the estimation error using selected parameters was 0.07BW, while the maximum error was 0.25BW. We confirmed that there was little posture change adversely affecting thigh-calf contact force. Individual anthropometric parameters were important for estimation, although we used similar subjects for gender, age, and physical size. In the future, we will be recruiting more test subjects and discussing the effect of physical parameters, not only anthropometric values.
Dissection and removal of lesion areas are fundamental operations in brain surgeries. Therefore, damage and fracture models are needed to simulate dissection and removal operations. Generally, brain tissues show strong ductility; however, conventional fracture or damage models cannot reproduce ductile fractures well. In this paper, a simple damage and fracture model of brain parenchyma is proposed for real-time haptic surgery simulations. Although the proposed model does not require iterative calculation, it can reproduce ductile fracture while maintaining sufficient accuracy. The finite element method (FEM) is used to perform numerical simulations. In the proposed damage model, it is assumed that micro-damage begins when von Mises stress exceeds a certain threshold in an element, and the micro-damage grows with increased von Mises stress. The stiffness decreases as the micro-damage grows. When the integrity of an element becomes smaller than a certain threshold, the element is removed to express the occurrence of a fracture. These steps were formulated algorithmically. In order to verify the proposed damage and fracture model, tensile tests were conducted using porcine brain parenchyma. Parameters for the proposed damage model were identified using the results of the tensile tests. Tensile test simulations were performed using the identified parameters. The simulations effectively reproduced the stress-strain curves obtained in the tensile tests using porcine brain tissues.