We present a method of electromyographic(EMG) pattern recognition to identify motion commands for the control of a prosthetic arm by evidence accumulation with multiple parameters. Integral absolute value, variance, autoregressive(AR) model coefficients, linear cepstrum coefficients, and adaptive cepstrum vector are extracted as feature parameters from several time segments of the EMG signals. Pattern recognition is carried out through the evidence accumulation procedure using the distances measured with reference parameters. A fuzzy mapping function is designed to transform the distances for the application of the evidence accumulation method. Results are presented to support the feasibility of the suggested approach for EMG pattern recognition.