A computer-implemented method of characterizing a patient's disordered breathing during a sleeping period, comprising: receiving at least a first signal that is representative of the sounds occurring during at least a portion of the sleeping period in the vicinity of the patient; identifying in the at least first signal a plurality of segments; characterizing at least some of the segments of the plurality of segments as each being in one of a plurality of pre-established clusters, the plurality of pre-established clusters each having a plurality of properties, a property from among the plurality of properties being a phase from among a group of phases that comprises an inhalation phase of a breathing cycle, an exhalation phase of a breathing cycle, a rest phase of a breathing cycle, and an unknown event, another property from among the plurality of properties being representative of an energy value; applying to each segment of the at least some of the segments a spectral characterization of the segment; for at least one segment characterized as being in a cluster having as its phase an unknown event, re-characterizing the at least one segment into being characterized as in another cluster having as its phase one of an inhalation phase of a breathing cycle, an exhalation phase of a breathing cycle, and a rest phase of a breathing cycle based at least in part upon a correspondence between the spectral characterization of the at least one segment and a spectral characterization that pertains to the another cluster to form a time axis that corresponds with the at least first signal and whose segments are each categorized as being one of an inhalation phase of a breathing cycle, an exhalation phase of a breathing cycle, and a rest phase of a breathing cycle; and generating an output that comprises information that is based at least in part upon the time axis. receiving at least a first signal that is representative of the sounds occurring during at least a portion of the sleeping period in the vicinity of the patient; identifying in the at least first signal a plurality of segments; characterizing at least some of the segments of the plurality of segments as each being in one of a plurality of pre-established clusters, the plurality of pre-established clusters each having a plurality of properties, a property from among the plurality of properties being a phase from among a group of phases that comprises an inhalation phase of a breathing cycle, an exhalation phase of a breathing cycle, a rest phase of a breathing cycle, and an unknown event, another property from among the plurality of properties being representative of an energy value; applying to each segment of the at least some of the segments a spectral characterization of the segment; for at least one segment characterized as being in a cluster having as its phase an unknown event, re-characterizing the at least one segment into being characterized as in another cluster having as its phase one of an inhalation phase of a breathing cycle, an exhalation phase of a breathing cycle, and a rest phase of a breathing cycle based at least in part upon a correspondence between the spectral characterization of the at least one segment and a spectral characterization that pertains to the another cluster to form a time axis that corresponds with the at least first signal and whose segments are each categorized as being one of an inhalation phase of a breathing cycle, an exhalation phase of a breathing cycle, and a rest phase of a breathing cycle; and generating an output that comprises information that is based at least in part upon the time axis.