The University of Texas System

Other

Respironics, Inc.

John R Burk

Edgar A Lucas

Khosrow Behbehani

Fu-Chung Yen

John R Axe

Khosrow Bebehani

Sridhar Vijendra

Francisco J Lopez

Edgar R Lucas

A system to form and store an electrocardiogram (ECG) signal derived from a cardiac electrical signal that includes an apparatus having a pair of the electrodes to connect to a patient to detect the cardiac electrical signal. A signal sampler samples the cardiac electrical signal to form the ECG signal. A data storage device stores the ECG signal. A computer communicates with the data storage device to retrieve the ECG signal for analysis by software stored in the memory of the computer. The software analyzes a morphology of the amplitude of a plurality of R-wave peaks contained within the ECG signal and/or analyzes a morphology of the area of a plurality of QRS complex pulses contained within the ECG signal.

System, software, and method for detection of sleep-disordered breathing using an electrocardiogram

Respiratory rhythms of a subject are derived from measured ECG signals utilizing leads placed for significant influence of chest movement on the ECG signals. The QRS pulses within ECG signals measured in two substantially orthogonal planes are located by applying a sequence of filters. The knot and period of the QRS pulses are then determined, with adjustments made during a learning phase of data sampling. The QRS pulse areas in both planes is then calculated. These pulse areas are employed to determine the angle of orientation of the depolarization wave's mean electrical axis (MEA) at the QRS pulse locations. Cubic spline interpolation of the data points for the MEA angle provides a smooth breathing curve, which may be scored for sleep disordered breathing events. The ECG-derived respiratory (EDR) signal may be employed in lieu of airflow measurements where such measurements are not available, or may be employed in conjunction with airflow measurements and/or measured cardiac activity data to discriminate between arrhythmias associated with disordered breathing versus those associated with cardiac malfunction, reducing misdiagnosis. The additional processing of ECG data required for derivation of respiratory rhythms may be easily automated and implemented at nominal incremental cost per unit.

ECG derived respiratory rhythms for improved diagnosis of sleep apnea

A pressurized breathable gas, preferably air, is supplied to the patient's airways with an interface including a mask and a flexible hose. A selected oscillation component or forced probing signal is applied or superposed on the pressurized breathable gas, preferably with a loudspeaker coupled to a frequency generator. Pressure and flow of the breathable gas in the interface are measured or sampled, preferably using pressure transducers and a pneumotachometer coupled to a personal computer, to obtain pressure and flow data characteristic of the patient's airway. The pressure and flow data are converted to the frequency domain using Fourier transform or cross-power spectrum techniques in the personal computer. A function of the processed pressure and flow data is obtained to determine an index of airway impedance or degree of airway obstruction.

Method and apparatus for detection and diagnosis of airway obstruction

A method and device for controlling sleep disorder breathing utilizes variable multiple level pressures. A pressure source supplies compressed breathable gas at a relatively low pressure to the user's airway. Pressure transducers monitor pressures and convert them into electrical signals. The electrical signals are filtered and processed to extract specific features such as duration and energy levels. If these features exceed selected threshold values for duration and energy level over a minimum period of time, then the microprocessor declares the presence of sleep disorder breathing. If a selected number of these events occur within a selected time period, then the microprocessor adjusts the pressure delivered by the pressure source. If sleep disorder breathing is not detected within a certain time period, then the microprocessor lowers the pressure level gradually. The device and method disclosed in this patent is capable of detecting apnea, hypopnea, and pharyngeal wall vibration. Further, it is able to distinguish between obstructive, central and mixed apnea and hypopnea.

Method and apparatus for controlling sleep disorder breathing

A method and apparatus for treating sleep disorder breathing is disclosed having improved ability to accurately detect pharyngeal wall vibration or other apneic events. An interface or mask is placed over a patient's airway. The interface is coupled to a source of pressurized gas. A respiration-related variable, namely the total pressure in the interface, is measured or sampled. The respiration-related variable is input into an artificial neural network trained to recognize patterns characterizing sleep disorder breathing. Responsive to recognition by the artificial neural network of sleep disorder breathing, pressurized gas is supplied to the patient's airways through the interface.

Method and apparatus for treatment of sleep disorder breathing employing

A method and device for controlling sleep disorder breathing utilizes variable pressure. The compressor supplies air at a relatively low pressure to the user's air passages while the user is asleep. A pressure transducer will monitor the pressure and convert the pressure into an electrical signal. The electrical signal is filtered and processed to compare it to the characteristics of waveforms that exists during snoring. If the envelope of the waveform exceeds an average threshold value in duration and in area, then the microprocessor will consider the envelope possibly associated with a snore. If a selected number of envelopes of this nature occur within a selected time period, then the microprocessor considers snoring to exist and increases the pressure of the compressor. If snoring is not detected within a certain time period, then the microprocessor lowers the level gradually.

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Aledo, TX, United States of America

John R Burk