Electromyographic (EMG) signals are pulse-based signals with the high-energy components located in the pulses, also called envelopes. These pulses contain information that is vital for EMG signal analysis. In a person with a spinal cord injury, the envelopes are cluttered with noise and are difficult to detect. In this paper, we will show that the simultaneous use of a pico filter (FatBear) and wavelets is a robust method for the detection of the signal in a cluttered environment. The FatBear, a nonarithmetic, piecewise continuous filter, can be used as a filter for pulse-width filtering, impulse rejection, and edge enhancement. The FatBear will be used as a preliminary step to eliminate the impulsive noise present in the signal. Wavelet techniques will then be applied to process the signal. As a result, we will obtain the information in the pulse interval without the noise.