A medical method of automatically improving signals received from a patient's physiological system, the method comprising: - delivering stimulation signals to a nerve pathway of a patient with electrical pulses via electrodes placed over the nerve pathway to generate a plurality of resultant electrical waveforms (EPs) based on a plurality of electrophysiological responses (ERs); - recording the plurality of resultant electrical waveforms (EPs); - generating an ensemble average waveform, the generating comprising averaging a subset of the plurality of electrophysiological responses (ERs); - denoising the ensemble average waveform, - comparing the denoised ensemble average waveform to a previously denoised ensemble average waveform; - determining whether a change has occurred in the denoised ensemble average waveform relative to the previously denoised ensemble average waveform; and, - generating an alert, based on said determination that the change has occurred, characterized in the denoising comprising: decomposing the ensemble average waveform in a hierarchical fashion using a series of filter banks, wherein filter coefficients of the filter banks are derived from a mother wavelet and wherein the hierarchical decomposition of the ensemble average waveform comprises applying a wavelet transform to the ensemble average waveform; applying the filter banks to the hierarchical decomposition of the ensemble average waveform in at least one iteration;applying a threshold to the filter coefficients to remove high-frequency noise from the ensemble average waveform, said threshold being determined with each ensemble average waveform; and, applying an inverse wavelet transform to the ensemble average waveform. - delivering stimulation signals to a nerve pathway of a patient with electrical pulses via electrodes placed over the nerve pathway to generate a plurality of resultant electrical waveforms (EPs) based on a plurality of electrophysiological responses (ERs); - recording the plurality of resultant electrical waveforms (EPs); - generating an ensemble average waveform, the generating comprising averaging a subset of the plurality of electrophysiological responses (ERs); - denoising the ensemble average waveform, - comparing the denoised ensemble average waveform to a previously denoised ensemble average waveform; - determining whether a change has occurred in the denoised ensemble average waveform relative to the previously denoised ensemble average waveform; and, - generating an alert, based on said determination that the change has occurred, characterized in the denoising comprising: decomposing the ensemble average waveform in a hierarchical fashion using a series of filter banks, wherein filter coefficients of the filter banks are derived from a mother wavelet and wherein the hierarchical decomposition of the ensemble average waveform comprises applying a wavelet transform to the ensemble average waveform; applying the filter banks to the hierarchical decomposition of the ensemble average waveform in at least one iteration;applying a threshold to the filter coefficients to remove high-frequency noise from the ensemble average waveform, said threshold being determined with each ensemble average waveform; and, applying an inverse wavelet transform to the ensemble average waveform. decomposing the ensemble average waveform in a hierarchical fashion using a series of filter banks, wherein filter coefficients of the filter banks are derived from a mother wavelet and wherein the hierarchical decomposition of the ensemble average waveform comprises applying a wavelet transform to the ensemble average waveform; applying the filter banks to the hierarchical decomposition of the ensemble average waveform in at least one iteration;applying a threshold to the filter coefficients to remove high-frequency noise from the ensemble average waveform, said threshold being determined with each ensemble average waveform; and, applying an inverse wavelet transform to the ensemble average waveform.