# Development of a Simplified Human Body Model for Movement Simulations
## 4 Discussion
Furthermore, the performance and accuracy of existing models can only be generally evaluated since detailed data concerning these parameters are difficult to obtain and even more challenging to interpret and compare, as models present various accuracies regarding numerous features. For instance, it is reported that the Hanavan model provides data about the center of gravity within 0.7 inches from expectations, and the moments of inertia are anticipated within 10% of the experimental results [16]. Meanwhile, the Yeadon model reported around 2% error in specifying the inertia parameters [18]. Even for the Hatze model, which is considered one of the most accurate, the numerical data are quite general, reporting that the overall accuracy of the model is better than 3% [17]. Therefore, the presented comparison of models involves design features, while the evaluation and comparison of performance and accuracy should be performed in the future. The main model's limitations and trade-offs of simplifications are as follows:  
* parameterization using only two parameters may not accurately capture the anatomical variations of individuals;
* application of single rigid solids may limit the accuracy of results for kinematics since the elasticity of human tissue, and articulations is not included;
* uniform density of segments may lower the accuracy of the results for dynamics. The model is to some extent universal, but its current scope of applicability and limitations concern the fact that the model refers to people of Caucasian race, adults aged 20-60 years; the model is for men. Its modification to make it adequately useful for women may be the subject of further research and should not be problematic, as the parameterization formulas are mostly based on gender-independent anthropometric data [22; 32]. Moreover, the correctness and universality of the additional parametric relationships derived from data for a man in the 50 th percentile [23] (Table A1) still need to be verified. In the case of using a larger number of precise body measurements, the model's accuracy of simulations and calculations would increase, but this would make its application more difficult (measuring many parameters). Moreover, introducing additional parameters would allow for greater individualization of the model with regard to specific types of body structure, e.g., taking into account, the dependence on different values of the centile (not only the 50 th) or the calculated BMI coefficient in anthropometric formulas. However, a very detailed reproduction of the individual human body was not the aim of this study, which instead tried to limit the number of values necessary for model parameterizationin order to obtain a simple model that is quick to use as a reference for assumed typical body measurements and which allows results to be obtained with satisfactory accuracy (depending on the application, the acceptable level should be determined). Therefore, the model may not fit precisely for individuals with atypical parameters (not typical BMI), being overweight, etc. The correctness of the model's operation and its suitability for reproducing measured movements should also be further investigated, e.g., by simulating other activities and using other sensors or sources of data for the simulated movements. In this way, it may also be possible to improve the accuracy of the obtained results. In the future, one of the key steps for research continuation will be to include the anatomical position of each segment's COM in the model and then parameterize it again in relation to the smallest possible number of human body measurements (preferably only height and weight). It will also be necessary to compare the results of the dynamic analysis of such a model with the current solution. More importantly, the application of the formulas presented in this work will allow the development of a fully mathematical model of the human body in the future.