Multimodal Control Method for Prosthetic Hands
Author Information
Author(s): Cui Jianwei, Yan Bingyan
Primary Institution: Institute of Instrument Science and Engineering, Southeast University, Nanjing, China
Hypothesis
Can a multimodal perception and control method improve the functionality of prosthetic hands for disabled individuals?
Conclusion
The proposed control method for prosthetic hands achieved a grasping success rate of 91.63%, demonstrating its feasibility and applicability.
Supporting Evidence
- The grasping success rate of the proposed method was 91.63%.
- The system recognized the intention of upper limb movements effectively.
- Participants completed various tasks with high accuracy using the prosthetic hand.
- The multimodal approach improved the control and comfort of the prosthetic hand.
Takeaway
This study created a smart robotic hand that can help people with disabilities by using different sensors to understand how to grab things.
Methodology
The study used a combination of visual and tactile sensors along with arm motion measurements to control a prosthetic hand.
Limitations
The study may be limited by the complexity of environments and the variety of objects that can be recognized.
Participant Demographics
Participants included 10 volunteers with upper limb disabilities.
Digital Object Identifier (DOI)
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