Most of the assistive devices are of user contact based control like body-powered prosthetic hand, joystick control of wheelchair, sip-and-puff, etc. and have a limited number of control movements. The performance of these assistive devices improves using bio-signals/gesture based control embedded in the processor. Gesture based control is widely used in wheelchair navigation control, communication with external world for neuromuscular impaired subjects. On the other hand, bio-signals are used widely in prosthetic devices, wheelchair control, orthotic devices, etc. with pattern recognition based control strategy. The choice and number of features used in pattern recognition for accurate control of assistive device is crucial. Further, these features performance also varies with the classifier. The appropriate selection of combination of pattern recognition will enhance the accuracy. This chapter focuses on bio-inspired techniques in selection of features and classification for the pattern recognition based assistive device control.