Technol Health Care. 2022 Aug 5. doi: 10.3233/THC-220190. Online ahead of print.
ABSTRACT
BACKGROUND: Human gait involves activities in nervous and musculoskeletal dynamics to modulate joint torques with time continuously for adapting to varieties of walking conditions.
OBJECTIVE: The goal of this paper is to estimate the joint torques of lower limbs in human gait based on Gaussian process.
METHOD: The potential uses of this study include optimization of exoskeleton assistance, control of the active prostheses, and modulating the joint torque for human-like robots. To achieve this, Gaussian process (GP) based data fusion algorithm is established with joint angles as the inputs.
RESULTS: The statistic nature of the proposed model can explore the correlations between joint angles and joint torques, and enable accurate joint-torque estimations. Experiments were conducted for 5 subjects at three walking speed (0.8 m/s, 1.2 m/s, 1.6 m/s).
CONCLUSION: The results show that it is possible to estimate the joint torques at different scenarios.
PMID:35964218 | DOI:10.3233/THC-220190
