To improve performance of human hand movement pattern recognition

a new pattern recognition method based on locally linear embedding（ LLE） algorithm and support vector machine（ SVM） is proposed aiming at problem caused by high dimensional feature data. Two path surface electromyography（ s EMG） are acquired from the brachioradialis muscle and flexor carpi ulnaris

by means of time domain analysis and wavelet analysis

feature of original signal is extracted

and feature vector is constructed. To find low dimensional feature which is more able to express intrinsic law of the characteristics

reduce the dimension by using the LLE algorithm. Feature data after reducing dimension is input into SVM classifier for pattern recognition of four kinds of hand movements. Experiments show that the method can effectively and accurately classify human hand movements.