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Classification of Electromyogram Signal for Control of Robotic Gripper

Excerpt

This paper will look into the utilization of electromyogram (EMG) signal for control of a robotic gripper. EMG signal is acquired from flexor carpi ulnaris and flexor carpi radialis of the forearm. These are the muscles that responsible for wrist flexion and extension that brought to opening and closing of the hand. To link this with the control of robotic gripper, the EMG signal from the muscles will first be classified into two distinct groups which represents ‘hand open’ and ‘hand close’ gesture. In this study, EMG data corresponds to hand opening and closing was recorded from five subjects. Feature of EMG signal were extracted using mean absolute value (MAV) method. The feature vector is then classified into the two distinct movement using Support Vector Machine (SVM).

  • Abstract
  • Key Words
  • 1. Introduction
  • 2. Method
  • 3. Feature Extraction
  • 4. Classification Using SVM
  • 5. Results
  • 6. Conclusion
  • 7. Summary & Future Development
  • References

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