Abstract: A method is provided for identifying a disease of a patient. The method includes collecting data of at least one cardio-respiratory function of the patient over time, eliminating artifacts from the collected data to create a new data record, constructing a phase-space from the new data record, and constructing a hypercube covering the phase-space. The method further includes calculating threshold criteria for quantifying dispersion characteristics of an attractor of the phase-space and determining the patient's tendency towards the disease based on the threshold criteria.

Abstract: A method is provided for identifying a disease of a patient. The method includes collecting data of at least one cardio-respiratory function of the patient over time, eliminating artifacts from the collected data to create a new data record, constructing a phase-space from the new data record, and constructing a hypercube covering the phase-space. The method further includes calculating threshold criteria for quantifying dispersion characteristics of an attractor of the phase-space and determining the patient's tendency towards the disease based on the threshold criteria.

Abstract: An apparatus and method for identifying sleep disordered breathing while the patient is awake. The device includes collection of raw data which is normalized, then conditioned and transformed for comparison against a threshold, enabling identification of the presence of and severity of sleep disordered breathing. Step 1 is the collection of raw data and normalization. Step 2 is the conditioning of the data (using Empirical Mode Decomposition or similar technique). Step 3 is the selection of several components in the conditioned data. Step 4 is the performing of a Hilbert transform on the conditioned data. Step 5 is selecting a constant frequency. Step 6 is charting output against a threshold. Step 7 is identifying the patient's condition based on an array of amplitudes and the threshold.

Abstract: An apparatus and method for identifying sleep disordered breathing while the patient is awake. The device includes collection of raw data which is normalized, then conditioned and transformed for comparison against a threshold, enabling identification of the presence of and severity of sleep disordered breathing. Step 1 is the collection of raw data and normalization. Step 2 is the conditioning of the data (using Empirical Mode Decomposition or similar technique). Step 3 is the selection of several components in the conditioned data. Step 4 is the performing of a Hilbert transform on the conditioned data. Step 5 is selecting a constant frequency. Step 6 is charting output against a threshold. Step 7 is identifying the patient's condition based on an array of amplitudes and the threshold.