SOURCE-LINKED INTELLIGENCE
Synergistic Control Technology: Muscle Activation-Based Intention Estimation and Vision-aid Assistance in Upper Limb Prosthetics
posed and it will offer highly accurate, robust, and object interactive advantages. SSPC will overcome LMs by 1) Design a signal processing algorithm for the acquisition of muscle unit activation and Machine learning (ML)-based intention estimation model by spatial and temporal signal consideration, 2) Vision-aid real-time grasping assistance algorithm, and 3) Design SSPC framework. (a) Offline simulation analysis and (b) Real-time clinical trials will be conducted as solid support of Synergistic Control Technology: Muscle Activation-Based Intention Estimation and Vision-aid Assistance in Upper Limb Prosthetics (SynConT). It will contribute to prosthetics technology beyond the state of the art and bring it to daily life. prosthetics, assistance grasping, intention estimation, signal processing, biomedical engineering, neurorehabilitation technology
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 260347.92
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T03:21:21.440Z. This is not the publication date.