1. A Real-time Control System of Upper-limb Human Musculoskeletal Model with Environmental Integration
- Author
-
Azhar Aulia Saputra, Tadamitsu Matsuda, and Naoyuki Kubota
- Abstract
Human musculoskeletal modelling involves extensive mathematical calculations to replicate physical and biological dynamics faithfully, making it difficult to arrive at an estimate of muscle activity. Real-time processes affect the real monitoring application and advanced analy- sis. This model aimed to achieve real-time muscle activity estimation using human musculoskeletal simulation with environmental integration. We focused on the upper ex- tremity of the human musculoskeletal model with 50 Hill- type muscles. We built the model in MuJoCo and included surrounding environments. The data input on human pos- ture was acquired from single RGBD sensors located at 32 three-dimensional node positions. We provided inverse kinematics calculations to convert this data to the joint angle level of the simulation model. We controlled the stretch reflex of each muscle to move the target joints. The target muscle stretch length was calculated from the mechanical integration between the bone and the muscle- tendon actuator anchored to it. In the model, an artificial force could be applied to represent an external load. To validate our model, we conducted the basic movement of the upper extremity and measured the resulting muscle activity with EMG sensors. We concluded that the proposed model can accurately estimate muscle activation, including the force exerted by each muscle. Further experiments showed that the proposed model can be integrated with dynamic environmental conditions for a seamless human physical monitoring system.
- Published
- 2023