Abstract: Methods and apparatus are provided to format a probability index that reflects where an electroencephalogram (EEG) pattern lies within the spectrum of wakefulness to deep sleep, which employs a computer/microprocessor that performs frequency domain analysis of one or more discrete sections of the EEG to determine the EEG power or amplitude at specified frequencies, optionally calculates the total power or amplitude over specified frequency ranges, assigns a rank to the power or amplitude at each frequency, or frequency range, assigns a code that reflects the ranking of the different frequencies or frequency ranges, and determines an index that reflects where the EEG pattern within the section(s) lies within the spectrum of wakefulness to deep sleep by use of a reference source, such as a look-up table or other suitable decoding instrument.

Abstract: Method and software are provided to format a probability index that reflects where an electroencephalogram (EEG) pattern lies within the spectrum of wakefulness to deep sleep, which employs a computer/microprocessor that performs frequency domain analysis of one or more discrete sections (Bins) of the EEG to determine the EEG power at specified frequencies, optionally calculates the total power over specified frequency ranges, assigns a rank to the power at each frequency, or frequency range, assigns a code to the Bin that reflects the ranking of the different frequencies or frequency ranges, and determines an index that reflects where said EEG pattern within said Bin(s) lies within the spectrum of wakefulness to deep sleep by use of a reference source, such as a look-up table or other suitable decoding instrument.

Abstract: A computerized method comprises statistically analyzing, using one or more processors, at least one section of a digitally recorded electroencephalography (EEG) signal that comprises an arousal segment to determine, for the arousal segment, at least one of amplitude and power at different frequencies as a function of time; selecting specified features from the results of the analysis and normalizing the selected features; and assigning, using one or more processors, an intensity scale value to the arousal segment based on the normalized selected features and a reference data set, the reference data set comprising normalized features corresponding to the normalized selected features and being generated based on a plurality of EEG signals comprising arousal segments to which intensity scale values have been assigned based on a visual inspection of the EEG signals.

Abstract: Method and software are provided to format a probability index that reflects where an electroencephalogram (EEG) pattern lies within the spectrum of wakefulness to deep sleep, which employs a computer/microprocessor that performs frequency domain analysis of one or more discrete sections (Bins) of the EEG to determine the EEG power at specified frequencies, optionally calculates the total power over specified frequency ranges, assigns a rank to the power at each frequency, or frequency range, assigns a code to the Bin that reflects the ranking of the different frequencies or frequency ranges, and determines an index that reflects where said EEG pattern within said Bin(s) lies within the spectrum of wakefulness to deep sleep by use of a reference source, such as a look-up table or other suitable decoding instrument.

Abstract: Method and software are provided to format a probability index that reflects where an electroencephalogram (EEG) pattern lies within the spectrum of wakefulness to deep sleep, which employs a computer/microprocessor that performs frequency domain analysis of one or more discrete sections (Bins) of the EEG to determine the EEG power at specified frequencies, optionally calculates the total power over specified frequency ranges, assigns a rank to the power at each frequency, or frequency range, assigns a code to the Bin that reflects the ranking of the different frequencies or frequency ranges, and determines an index that reflects where said EEG pattern within said Bin(s) lies within the spectrum of wakefulness to deep sleep by use of a reference source, such as a look-up table or other suitable decoding instrument.

Abstract: Method and device for diagnosing and/or treating sleep apnea and related sleep disorders, such as snoring and respiratory effort-related arousals, includes an inflatable implement which is applied to the external surface of the chest and/or abdomen (Vest). Pressure is caused to rise to a predetermined positive value. The rate of airflow into and/or out of said Vest is monitored, whereby the Vest Flow is displayed or processed to obtain information about the breathing characteristics of the patient.

Abstract: Method and software are provided to format a probability index that reflects where an electroencephalogram (EEG) pattern lies within the spectrum of wakefulness to deep sleep, which employs a computer/microprocessor that performs frequency domain analysis of one or more discrete sections (Bins) of the EEG to determine the EEG power at specified frequencies, optionally calculates the total power over specified frequency ranges, assigns a rank to the power at each frequency, or frequency range, assigns a code to the Bin that reflects the ranking of the different frequencies or frequency ranges, and determines an index that reflects where said EEG pattern within said Bin(s) lies within the spectrum of wakefulness to deep sleep by use of a reference source, such as a look-up table or other suitable decoding instrument.

Abstract: A computerized method comprises statistically analyzing, using one or more processors, at least one section of a digitally recorded electroencephalography (EEG) signal that comprises an arousal segment to determine, for the arousal segment, at least one of amplitude and power at different frequencies as a function of time; selecting specified features from the results of the analysis and normalizing the selected features; and assigning, using one or more processors, an intensity scale value to the arousal segment based on the normalized selected features and a reference data set, the reference data set comprising normalized features corresponding to the normalized selected features and being generated based on a plurality of EEG signals comprising arousal segments to which intensity scale values have been assigned based on a visual inspection of the EEG signals.

Abstract: A method and device for generating a signal that mirrors changes in the level of effort exerted by respiratory muscles of patients on mechanical ventilatory support comprising: monitoring and storing airway pressure (Paw), rate of gas flow (F), and volume of gas flow (V), and generating a composite pressure signal using resistive pressure units (KF) determined from elapsed data and selected to minimize step changes in the calculated signal and elastic pressure units (Kv) determined from elapsed data by steps comprising: —scanning stored F or Paw during exhalation and identifying where their trajectory transiently reverses direction to detect transients; —selecting points within the exhalation that are at preselected distances away from the transients; —calculating the value of Kv required to force the values of the calculated signal at said selected points in elapsed breaths to be substantially equal when the selected value of KF is used as the flow coefficient.

Abstract: Gas leakage from a ventilator circuit and patient interface is estimated by a method that relies on breath-by-breath or time-to-time variability in the pattern of pressure delivery by the ventilator, comprising generating signals that correspond to pressure (PCIRCUIT) and flow rate (Flow) in the ventilator circuit, integrating flow (Integrated Flow), measuring the change in Integrated Flow (?V) over an INTERVAL extending from a selected point in the expiratory phase of a ventilator cycle to a selected point during the expiratory phase of a nearby ventilator cycle, repeating the measurement of ?V for at least two said INTERVALs, processing PCIRCUIT to produce an index or indices that reflect(s) the pattern of pressure delivery by the ventilator during each of said INTERVALs, applying statistical methods to determine the relation between the differences in ?V among 1NTERVALs and the corresponding differences in said index or indices of PCIRCUIT, and establishing from said relation the leak rate at specified PCI

Abstract: Method and device for diagnosing and/or treating sleep apnea and related sleep disorders, such as snoring and respiratory effort-related arousals, includes an inflatable implement which is applied to the external surface of the chest and/or abdomen (Vest). Pressure is caused to rise to a predetermined positive value. The rate of airflow into and/or out of said Vest is monitored, whereby the Vest Flow is displayed or processed to obtain information about the breathing characteristics of the patient.

Abstract: Gas leakage from a ventilator circuit and patient interface is estimated by a method that relies on breath-by-breath or time-to-time variability in the pattern of pressure delivery by the ventilator, comprising generating signals that correspond to pressure (PCIRCUIT) and flow rate (Flow) in the ventilator circuit, integrating flow (Integrated Flow), measuring the change in Integrated Flow (?V) over an INTERVAL extending from a selected point in the expiratory phase of a ventilator cycle to a selected point during the expiratory phase of a nearby ventilator cycle, repeating the measurement of ?V for at least two said INTERVALS, processing PCIRCUIT to produce an index or indices that reflect(s) the pattern of pressure delivery by the ventilator during each of said INTERVALS, applying statistical methods to determine the relation between the differences in ?V among INTERVALS and the corresponding differences in said index or indices of PCIRCUIT, and establishing from said relation the leak rate at specified PCI

Abstract: Automatic ongoing adjustment of the cycling-off time of ventilator inflation phase during assisted ventilation in accordance with true respiratory rate of a patient. Electrical signals are generated corresponding to the gas flow exchanged between patient and ventilator (flow) and/or to airway pressure (Paw) and the true respiratory rate of the patient (patient RR) is determined on an ongoing basis from the flow and/or Paw. The current average cycle duration of patient respiratory efforts (current patient TTOT) is estimated from patient RR. A current desirable duration of the inhalation phase (desirable TI) is calculated from the product of current patient TTOT a TI/TTOT ratio chosen to be in the physiological range, usually 0.25 to 0.50. The ventilator phase is caused to terminate in accordance with the desirable TI.

Abstract: A method and device for generating a signal that mirrors changes in the level of effort exerted by respiratory muscles of patients on mechanical ventilatory support comprising: monitoring and storing airway pressure (Paw), rate of gas flow (F), and volume of gas flow (V), and generating a composite pressure signal using resistive pressure units (KF) determined from elapsed data and selected to minimize step changes in the calculated signal and elastic pressure units (Kv) determined from elapsed data by steps comprising: scanning stored F or Paw during exhalation and identifying where their trajectory transiently reverses direction to detect transients; selecting points within the exhalation that are at preselected distances away from the transients; calculating the value of Kv required to force the values of the calculated signal at said selected points in elapsed breaths to be substantially equal when the selected value of KF is used as the flow coefficient.

Abstract: Method and apparatus for non-invasively determining the time onset (Tonset) and end (Tend) of patient inspiratory efforts. A composite pressure signal is generated comprising the sum of an airway pressure signal, a gas flow pressure signal obtained by applying a gain factor (Kf) to a signal representing gas flow rate and a gas volume pressure signal obtained by applying a gain factor (Kv) to a signal representing volume of gas flow. Kf and Kv values are adjusted to result in a desired linear trajectory of composite pressure signal baseline in the latter part of the exhalation phase. The current composite pressure signal is compared with (i) selected earlier composite pressure signal values and/or (ii) value expected at current time based on extrapolation of composite pressure signal trajectory at specified earlier times and/or (iii) the current rate of change in the composite pressure signal with a selected earlier rates of change.

Abstract: Method and apparatus for non-invasively determining the time onset (Tonset) and end (Tend) of patient inspiratory efforts. A composite pressure signal is generated comprising the sum of an airway pressure signal, a gas flow pressure signal obtained by applying a gain factor (Kf) to a signal representing gas flow rate and a gas volume pressure signal obtained by applying a gain factor (Kv) to a signal representing volume of gas flow. Kf and Kv values are adjusted to result in a desired linear trajectory of composite pressure signal baseline in the latter part of the exhalation phase. The current composite pressure signal is compared with (i) selected earlier composite pressure signal values and/or (ii) value expected at current time based on extrapolation of composite pressure signal trajectory at specified earlier times and/or (iii) the current rate of change in the composite pressure signal with a selected earlier rates of change.

Abstract: Automatic ongoing adjustment of the cycling-off time of ventilator inflation phase during assisted ventilation in accordance with true respiratory rate of a patient. Electrical signals are generated corresponding to the gas flow exchanged between patient and ventilator (flow) and/or to airway pressure (Paw) and the true respiratory rate of the patient (patient RR) is determined on an ongoing basis from the flow and/or Paw. The current average cycle duration of patient respiratory efforts (current patient TTOT) is estimated from patient RR. A current desirable duration of the inhalation phase (desirable TI) is calculated from the product of current patient TTOT a TI/TTOT ratio chosen to be in the physiological range, usually 0.25 to 0.50. The ventilator phase is caused to terminate in accordance with the desirable TI.

Abstract: Method and apparatus for non-invasively determining the time onset (Tonset) and end (Tend) of patient inspiratory efforts. A composite pressure signal is generated comprising the sum of an airway pressure signal, a gas flow pressure signal obtained by applying a gain factor (Kf) to a signal representing gas flow rate and a gas volume pressure signal obtained by applying a gain factor (Kv) to a signal representing volume of gas flow. Kf and Kv values are adjusted to result in a desired linear trajectory of composite pressure signal baseline in the latter part of the exhalation phase. The current composite pressure signal is compared with (i) selected earlier composite pressure signal values and/or (ii) value expected at current time based on extrapolation of composite pressure signal trajectory at specified earlier times and/or (iii) the current rate of change in the composite pressure signal with a selected earlier rates of change.

Abstract: Obstructive sleep apnea and snoring are treated by administering a sedative or hypnotic drug, including barbiturates and antihistamines.

Abstract: Method and apparatus are described for determining respiratory system resistance (R) in a patient receiving gas from a ventilator. A negative pulse in the pressure and/or flow output of the ventilator during selected inflation cycles is generated and Paw, {dot over (V)} and V are measured at a point (To) near the beginning of the pulse, at a point (T1) near the trough of the negative pulse and at a point (T?1) preceding To. The value of R is calculated from the difference between Paw, {dot over (V)} and V at To and at T1 and where the change in patient generated pressure (Pmus) in the interval To?T1 is estimated by extrapolation from the different between Paw, {dot over (V)} and V and To and at T?1, in accordance with Equation 8.