Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2022
|
| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2212.12760 |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866910354178572288 |
|---|---|
| author | Saadati, Sina Razzazi, Mohammadreza |
| author_facet | Saadati, Sina Razzazi, Mohammadreza |
| contents | Despite the fact that only a small portion of muscles are affected in motion disease and disorders, medical therapies do not distinguish between healthy and unhealthy muscles. In this paper, a method is devised in order to calculate the neural stimuli of the lower body during gait cycle and check if any group of muscles are not acting properly. For this reason, an agent-based model of human muscle is proposed. The agent is able to convert neural stimuli to force generated by the muscle and vice versa. It can be used in many researches including medical education and research and prosthesis development. Then, Boots algorithm is designed based on a biomechanical model of human lower body to do a reverse dynamics of human motion by computing the forces generated by each muscle group. Using the agent-driven model of human muscle and boots algorithm, a user-friendly application is developed which can calculate the number of neural stimuli received by each muscle during gait cycle. The application can be used by clinical experts to distinguish between healthy and unhealthy muscles. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2212_12760 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Agent-based Modeling and Simulation of Human Muscle For Development of Human Gait Analyzer Application Saadati, Sina Razzazi, Mohammadreza Artificial Intelligence Multiagent Systems Despite the fact that only a small portion of muscles are affected in motion disease and disorders, medical therapies do not distinguish between healthy and unhealthy muscles. In this paper, a method is devised in order to calculate the neural stimuli of the lower body during gait cycle and check if any group of muscles are not acting properly. For this reason, an agent-based model of human muscle is proposed. The agent is able to convert neural stimuli to force generated by the muscle and vice versa. It can be used in many researches including medical education and research and prosthesis development. Then, Boots algorithm is designed based on a biomechanical model of human lower body to do a reverse dynamics of human motion by computing the forces generated by each muscle group. Using the agent-driven model of human muscle and boots algorithm, a user-friendly application is developed which can calculate the number of neural stimuli received by each muscle during gait cycle. The application can be used by clinical experts to distinguish between healthy and unhealthy muscles. |
| title | Agent-based Modeling and Simulation of Human Muscle For Development of Human Gait Analyzer Application |
| topic | Artificial Intelligence Multiagent Systems |
| url | https://arxiv.org/abs/2212.12760 |