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Hand Tremor Prediction and Classification Using Electromyogram Signals to Control Neuro-Motor Instability
Abstract
This chapter provides a prototype design of a hand tremor compensator/controller to reduce the effect of the tremor to an external device/ apparatus, such as a magnetic pen for the patients suffering from Parkinson and similar diseases. It would also be effective for busy surgeons suffering from hand tremor due to muscle fatigue. Main emphasis in this chapter is given on the prediction of the tremor signal from the discrete samples of electromyogram data and tremor. The predicted signal is inverted in sign and added to the main tremor signal through a specially designed magnetic actuator carrying the external device, such as a magnetically driven pen or surgical instrument. Two different prediction algorithms, one based on neural nets and the other based on Kalman Filter have been designed, tested, and validated for the proposed application. A prototype model of the complete system was developed on an embedded platform. Further development on the basic model would be appropriate for field applications in controlling tremors of the subjects suffering from Parkinson and the like diseases.
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