| Proj No. | B3094-251 |
| Title | Development and Validation of Hybrid EMG-Assisted Optimization for Accurate Human Muscle Strength Modeling |
| Summary | Accurately modeling human muscle strength and activation is critical for applications in biomechanics, rehabilitation, sports science, and human–machine interaction. While musculoskeletal modeling tools such as OpenSim have advanced our ability to estimate internal forces from observed motion, traditional methods like Static Optimization (SO) and Computed Muscle Control (CMC) have inherent limitations. Hybrid EMG-assisted optimization provides a way to overcome these limitations. By incorporating experimental EMG signals into the optimization framework, we can constrain or guide muscle force estimation toward physiologically plausible patterns. This project aims to design and validate a hybrid EMG-assisted optimization framework to improve musculoskeletal modeling and muscle strength estimation. |
| Supervisor | A/P Lin Zhiping (Loc:S2 > S2 B2A > S2 B2A 14, Ext: +65 67906857) |
| Co-Supervisor | - |
| RI Co-Supervisor | Dr ZHANG Haihong (RI) |
| Lab | |
| Single/Group: | Single |
| Area: | Intelligent Systems and Control Engineering |
| ISP/RI/SMP/SCP?: | RI: Institute for Infocomm Research (I2R) Dr ZHANG Haihong Principal Scientist II Email: HHZHANG@I2R.A-STAR.EDU.SG Tel: 68748226; Fax: |
| Available for Phase 2 selection? (for RI projects only) |
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