Abstract: A method for the detection and treatment of disordered breathing during sleep employs an artificial neural network (ANN) in which data related to breathing gas flow are analyzed. A respiratory circuit is established by connecting the patient to a continuous positive airway pressure (CPAP) system with pressurized breathing gas supply, the gas flow in the circuit is periodically sampled, one or several cepstrum parameters distinctive of various breathing patterns are periodically calculated; the parameter values are periodically fed to an ANN trained to recognize breathing patterns characteristic of sleep disordered breathing and are analyzed in the network, the CPAP pressurized breathing gas supply is controlled in response to the ANN output. Also disclosed is a corresponding apparatus.

Abstract: A decoding method and apparatus for speech coding systems which takes into account the fact that the human auditory system is sensitive to changes in signal characteristics. For example, a sustained distortion of the spectral characteristic of reconstructed speech is usually less perceptible than an objectively smaller distortion which changes as a function of time. This property of the auditory system is advantageously exploited in the design of a speech coding system receiver in accordance with the present invention, by selecting the sequence of decoded speech parameter values on a perceptual basis. Illustratively, the sequence of decoded speech parameter values is selected so as to describe a smooth path through the sequence of Voronoi regions. The distance between successive parameter values is advantageously minimized, under the constraint that the resultant parameter values fall within, or nearly within, the appropriate Voronoi regions.