Abstract: A method of predicting continuous positive airway pressure (“CPAP”) is disclosed. In one such method, an artificial neural network (“ANN”) is created that produces a predicted CPAP. The ANN may be used to produce a CPAP that in turn may be useful in diagnosing and treating a patient with obstructive sleep apnea. Also disclosed are methods of evaluating ANNs for predicting a CPAP based on neck circumference, a body mass index, an apnea-hypopnea index, and an actual effective pressure.

Abstract: The present invention provides a diagnostic tool for detection of Cheyne-Stokes Respiration (CSR). This invention also provides a method for development of the diagnostic tool. The method comprises the steps of performing overnight oximetry recordings in patients suspected of sleep disordered breathing. Spectral analysis is performed on the oximetry recordings to obtain a set of parameters which can be used in the construction of a classification tree and a trained neural network. The diagnostic tools of the present invention can be used for classification of a patient as having CSR or obstructive sleep apnea.

Abstract: The present invention discloses a method for developing a diagnostic method for CSR. The method comprises the steps of performing overnight oximetry recordings in patients suspected of OSA who have been identified as having or not having CSR by clinical studies. Spectral analysis is performed on the oximetry recordings from which a classification tree is generated. The present invention also discloses a method for the identification of Cheyne-Stokes respiration in an individual. The method comprises the steps of performing spectral analysis of overnight oximetry recordings. The key features are then input into a classification tree to determine the presence or absence of CSR.

Abstract: A method for predicting respiratory disturbances, and a method for developing such an artificial neural network. The inputs to the method and to the artificial neural network of the present invention are the answers given by a person to a series of questions. The output of the artificial neural network is a predicted respiratory disturbance index.