651 Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 32 DOI: 10.4018/978-1-61350-429-1.ch032 Koushik Bakshi Jadavpur University, India Sourav Chandra Jadavpur University, India Amit Konar Jadavpur University, India. D.N. Tibarewala Jadavpur University, India Hand Tremor Prediction and Classifcation 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 embed- ded platform. Further development on the basic model would be appropriate for feld applications in controlling tremors of the subjects suffering from Parkinson and the like diseases.