FIELD OF THE TECHNOLOGY

The present technology relates to methods and apparatus for the detection of respiratory treatment related conditions or events such as the conditions indicative of asynchrony.

BACKGROUND OF THE TECHNOLOGY

Ensuring quality interaction between a patient and their respiratory treatment apparatus can be significant. For example, quality interaction between a patient and their ventilator is critical to minimize the work of breathing of the patient. Increased work of breathing caused by patient-ventilator asynchrony is associated with negative patient outcomes and has been shown to be highly prevalent; studies have shown up to 47% of ventilator delivered breaths may be asynchronous.

With proper supervision and adjustment of ventilator settings, asynchrony may be manually mitigated by the clinician. However, monitoring asynchrony is a challenge. Knowledge of its existence may require high resolution and real-time display of airway pressure delivered by the ventilator, the patient's airflow and a measure of inspiratory activity, such as diaphragmatic EMG or esophageal pressure measured invasively via a balloon catheter. Furthermore, expert visual interpretation of these signals can be critical to diagnose the quality of patient-ventilator interaction.

It may be desirable to develop further methods and devices for automating detection of asynchrony that may improve respiratory treatment apparatus.

SUMMARY OF THE TECHNOLOGY

Aspects of the present technology involve methods and apparatus for a detection of asynchrony.

Still further aspects of the technology involve methods and apparatus for development of devices for detection of asynchrony.

In one such example embodiment, an automated processing method is provided for detection of asynchrony of a respiratory treatment apparatus that controls a delivery of a synchronized respiratory treatment. The method may include determining detection values of a feature set with data derived from signals of at least one sensor coupled with the respiratory treatment apparatus. The method may further include comparing with a processor the feature set of detection values with a set of stored data thresholds. The method may also include determining with the processor an occurrence of an asynchrony event between the respiratory treatment apparatus and a patient respiratory cycle based on the comparison.

In another embodiment, an apparatus for detection of asynchrony between a synchronized respiratory treatment and a respiratory cycle is provided. The apparatus may include a memory containing data representing a feature set of detection values derived from signals of at least one sensor coupled with the respiratory treatment apparatus. The apparatus may also include a processor to access the data. The processor may be configured to control a comparison of the data of the feature set of detection values with a set of stored data thresholds of the memory. It may also be configured to control a determination of an occurrence of an asynchrony event between the respiratory treatment apparatus and a patient respiratory cycle based on the comparison. In addition, it may be configured to control a generation of an output representing the occurrence of the asynchrony event.

In some embodiments, the feature set of detection values may include any one or more of a respiratory rate based feature, a respiratory volume based feature, a respiratory mechanics based feature, an expiratory flow morphology based feature.

In some embodiments, the apparatus or method may also determine or identify a plurality of distinct asynchrony events based on the comparison. The asynchrony events may be any one or more of an expiratory ineffective effort event, a post-triggering effort event, a double triggering event, an autotriggering event, a late triggering event, an early cycling event, a late cycling event, and/or an inspiratory ineffective effort event.

In an example embodiment, the feature set of detection values for detecting an inspiratory ineffective effort event may include (a) power of a piecewise bilinear approximation of a remainder of expiration after a location of a maximum expiratory flow, (b) a distance between a maximum and minimum values of a moving average expiratory flow, (c) an integral of a rectified and de-trended moving average of expiratory flow, (d) an inspiratory time constant (e) and a fraction of said distance and a peak expiratory flow.

In some embodiments, the processor may be or be part of a controller of the respiratory treatment apparatus, which may be a ventilator, and the sensor may be a flow sensor. The controller may then be configured to detect a respiratory cycle with the signal of the flow sensor and to generate flow generator control signals for producing the respiratory treatment.

In some embodiments of the method or apparatus, the feature set are selected by a selecting process such that the feature set comprises a subset of a superset of features. Such a selecting process may include evaluating, with a processor, values of the superset for known asynchronous events occurring in data of a plurality of breaths established with a plurality of respiratory treatment apparatus. The evaluating process may involve calculating posterior-probabilities with values of the superset by Parzen-window estimation, wherein groups of values of the superset are selected by iteratively including and removing values. The evaluation may also include detecting asynchrony events with the selected subset of features and comparing the events detected with known events data to test or assess the performance of the subset.

In some embodiments, the apparatus may include a patient interface to carry a flow of breathable gas to a patient. It may also include a flow generator coupled with the patient interface to generate a flow of the breathable gas through the patient interface. The apparatus may also include a transducer, such as a pressure transducer or differential pressure transducer. The transducer may provide a signal indicative of patient flow through the patient interface. The processor may serve as a controller of the flow generator so that the controller is configured to detect a respiratory cycle with the signal of the flow sensor and to generate flow generator control signals for producing the respiratory treatment.

In some embodiments, a system is provided for detection of asynchrony between a synchronized respiratory treatment and a respiratory cycle. The system may include a processing means for processing data derived from one or more pressure transducer signals from use of respiratory treatment apparatus. The processing means may be configured for (a) comparing a feature set of detection values calculated from the data with a set of stored data thresholds, and (b) determining an occurrence of an asynchrony event between the respiratory treatment apparatus and a patient respiratory cycle based on the comparison. The system may also include classification means for selecting the feature set such that the feature set comprises a subset of a superset of features, wherein the selecting comprises evaluating values of the superset for known asynchronous events occurring in data of a plurality of breaths established with a plurality of respiratory treatment apparatus. The processing means of the system may also be configured for calculating the detection values of the feature set with the data derived from signals of at least one sensor.

In some embodiments of such a system, the feature set of detection values may be two or more of features of a group of features consisting of (a) a respiratory rate based feature; (b) a respiratory volume based feature; (b) a respiratory mechanics based feature; (d) an expiratory flow morphology based feature.

In further embodiments of such a system, the occurrence of the asynchrony event may be an asynchrony event of a group of asynchrony events consisting of (a) an expiratory ineffective effort event, (b) a post-triggering effort event, (c) a double triggering event, (d) an autotriggering event (e) a late triggering event, (f) an early cycling event, and (g) a late cycling event.

The system may also include an interface means to carry a flow of breathable gas, a flow generation means, coupled with the interface means, for generating the breathable gas, and a flow sensor for generating the pressure transducer signals. In such a system, the processing means may be further configured for controlling the flow generation means to provide a synchronized respiratory treatment, such as respiratory support ventilation.

In some embodiments, the methodologies may be contained on information bearing medium such as a memory. For example, an information-bearing medium may have processor-readable information thereon. The processor-readable information may control an apparatus for detection of asynchrony between a synchronized respiratory treatment and a respiratory cycle. The processor-readable information may then include control instructions to access detection values of a feature set with data derived from signals of at least one sensor coupled with the respiratory treatment apparatus, to compare the feature set of detection values with a set of stored data thresholds, and to determine an occurrence of an asynchrony event between the respiratory treatment apparatus and a patient respiratory cycle based on the comparison.

In some embodiments of the present technology, a respiratory treatment apparatus estimates respiratory resistance and compliance based on measures of flow and pressure. The apparatus may include one or more sensors to generate signals representative of flow and pressure. The apparatus may also include a processor, coupled with the one or more sensors. The processor may be configured to control detecting a portion of expiration of a breathing cycle from data of the flow signal. It may also be configured to control calculating a resistance value and compliance value with flow, pressure and volume measures that correspond to the detected portion of expiration.

In some embodiments, the detected portion of expiration may a portion that begins at an expiration cycle and ends when an expired tidal volume for the expiration cycle exceeds a limit in a range of about 85 to 90 percent. The compliance and resistance values may optionally be calculated by a multiple linear regression process with data representing the flow, pressure and volume measures. Moreover, this may be calculated in a breath by breath process. The processor may be further configured to control an assessment of accuracy of the determined resistance and compliance values. The assessment of accuracy may involve calculating a coefficient of determination and comparing it to a threshold.

In some embodiment, the processor of the respiratory treatment apparatus may be further configured to control determining a PEEP control parameter based on a plurality of compliance values determined by the processor. In such a process, the processor may control a repeated change, such as a step reduction, to a preset PEEP control parameter during which a plurality of pressure and flow measures are determined. The plurality of compliance values may then be determined based on the plurality of pressure and flow measures. This determination may involve detecting an inflection point from data representing the plurality of compliance values.

In some embodiments, the processor of the respiratory treatment apparatus may also be configured to control determining a maximum pressure support limit based on a plurality of determined compliance values. In such a process, the processor may controls a repeated change, such as a stepped reduction, to a preset PEEP control parameter during which a plurality of pressure and flow measures are determined. The processor then may determine the plurality of compliance values based on the plurality of pressure and flow measures. Optionally, the determining of the maximum pressure support limit may involve detecting an inflection point from data representing the plurality of compliance values. In some such embodiments, the respiratory treatment apparatus may also include a flow generator, coupled with the processor, to generate a flow of breathable gas at pressures above atmospheric to a patient interface based on control signals from the processor.

Further embodiments and features of the technology will be apparent from the following detailed disclosure, claims and drawings.

