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Inference of Upcoming Human Grasp Using EMG During Reach-to-Grasp Movement
We collected and utilized data from large gesture vocabularies with multiple dynamic actions to encode the transitions from one grasp intent to another based on common sequences of the grasp movements.
Multimodal Fusion of EMG and Vision for Human Grasp Intent Inference in Prosthetic Hand Control
Conclusion: Our experimental data analyses demonstrate that EMG and visual evidence show complementary strengths, and as a consequence, fusion of multimodal evidence can outperform each individual evidence modality at any given time.
NetCut: Real-Time DNN Inference Using Layer Removal
Deep Learning plays a significant role in assisting humans in many aspects of their lives.
Towards Creating a Deployable Grasp Type Probability Estimator for a Prosthetic Hand
For lower arm amputees, prosthetic hands promise to restore most of physical interaction capabilities.
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