Grasping Recognition Based on Electromyographic Signals Using a Wearable Device
Human grasping recognition based on superficial electromyographic signals is a research field that has grown in recent years due to the fact that it is possible to control i.) prosthesis hand, and ii.) general device. Recently, there is an innovative technology called wearable device; an example is MyoarmbandTM, which is able to capture superficial electromyographic signals. Using this device, a new mathematical model that allows automatic grasping movements detection, in real-time recognition, has been introduced. The model involves three steps: i.) identifying movement inception, ii.) extracting features from superficial electromyographic signals, and iii.) recognizing patterns. In order to evaluate hand grasping recognition accuracy, an experimental procedure is presented, using MyoarmbandTM bracelet. Moreover, a potential application of the presented model focuses on the control of the ProMain soft robotic hand prosthesis.
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