A novel muscle force model based on the fuzzy theory

作者：Wei, Gaofeng; Sun, Qiuming; Tang, Gang; Xie, Xinwu; Ni, Aijuan; Tian, Feng

DOI：10.1109/FSKD.2010.5569155

• Electromyography signals
• Fuzzy
• Fuzzy algorithms
• Human muscles
• Muscle activation
• Muscle activities
• Muscle force
• Virtual Markers

A new method is reported for human muscle force modeling based on the fuzzy theory. First, a Hill-based muscle force model was built. The muscle activation parameters were ascertained by fuzzy inferential algorithm as the input of the Hill-based muscle force. Then, a weightlifting motor task was implemented. Four channels of electromyography signals and twelve virtual markers motion data were collected when subject did a standard weightlifting experiment. The fuzzy algorithm was used to process raw electromyography signals and extract muscle activity features. Several muscle forces were estimated by the proposed muscle force model. The results demonstrated that the proposed method could improve the estimation accuracy of muscle forces. The proposed fuzzy algorithm could efficiently extract muscle activity features from electromyography signals. The reported method may be potentially used for the human biodynamic research and clinical biomechanics. Possible further improvements for this method were also discussed.

• 出版日期2010
• 单位上海交通大学