UA90651C2 - Method and apparatus for maintaining and monitoring sleep quality during therapeutic treatments - Google Patents

Abstract

The present invention monitors and interprets physiological signals and spontaneous breathing events to detect the onset of arousal. Once the onset of arousal is determined, the present invention determines adjustments that are needed in the operation of a therapeutic device to avoid or minimize arousals. In one embodiment, the present invention includes one or more sensors (10) which detect a patient's physiological parameters, a controller (12) which monitors and determines the onset of arousal based on the physiological variables received from the sensor (10), and a therapeutic treatment device which is controlled by the controller. The sensor can be a combination of one or more devices, which are able to monitor a physiological parameter that is used by the present invention to determine the onset of arousal or the onset of a sleep disorder. The sensors can be integrated into one unit or may operate independent of the others.

Description

In general, the invention relates to therapeutic procedures. More specifically, the invention relates to a method and a device for providing therapeutic procedures without harmful effects on patients' sleep.

Many of the therapeutic procedures are performed while patients are asleep or trying to fall asleep. | although such procedures may achieve their direct result, they often also significantly affect the patient's sleep quality during the course of these procedures. These procedures often interrupt the patient's normal sleep pattern, causing brief awakenings. Although such awakenings do not result in the patient waking up, they often take patients out of deeper stages or states of higher quality sleep. Patients often do not return to these deeper stages of sleep for a relatively long period of time.

In some cases, therapeutic procedures can cause multiple awakenings. This fragments the patient's sleep and prevents the patient from reaching deeper stages of sleep. Studies have shown that fragmented sleep leads to excessive daytime sleepiness, which in turn is a direct cause of many accidents, a general feeling of apathy, cognitive impairment, and/or daytime sleepiness of patients.

One example of therapeutic procedures causing sleep fragmentation occurs among procedures related to the treatment of sleep disorders. Continuous positive airway pressure therapy (CPAP) is one of the mainstays of treatment for many sleep disorders, such as sleep apnea, hypopnea, and snoring. CPAP therapy consists of delivering a constant flow of positive-pressure air into the patient's airways during sleep to prevent the patient's airway from collapsing. Known CPAP devices, often referred to as auto-titrating PAP (APAP) devices, automatically adjust the pressure of the delivered air to adapt the patient's breathing pattern to the rapid changes in patient airway pressure caused by the APAP devices.

Another disadvantage of currently known ARAP devices is that they are prone to false-positive results (for example, when LVDS and/or natural irregular breathing events do not appear or do not occur due to false detection of such and corresponding changes in the management of the procedure), as well as to false negatives (for example, when true resistance of the upper respiratory tract (irreg aigmau geziziapse - OAV, hereinafter OVDSH) and/or related events are manifested or occur, but are not detected or remain without reaction through controlled changes in the course of the procedure). This is partly due to the dependence of these devices on the correct interpretation of the curves of breathing parameters and inaccuracies that depend on the interpretation of the initial curve by the ARAP device. It may also be due to the inability of currently known gas delivery systems (or other procedural controls, such as cardiac pacemakers) to provide suitable algorithms, detect and sufficiently adapt their computational capabilities to prevent or predict the possibility or likelihood of surface breathing, OVDSH , awakenings and/or corresponding sleep fragmentation or deterioration of sleep quality.

The curve of breathing parameters changes periodically for reasons that are not always related to the resistance of the upper respiratory tract. The use of respiratory parameters curves as the primary or only means of detecting events associated with LVDS may lead to corrective auto-titration measures when they are not needed. This is especially obvious when the methods of analysis of the curves of breathing parameters do not use the original calculation methods during the course of the process. Such calculation methods during the course of the process consist in comparing previous sequences of respiratory cycles (data of respiratory cycles previously stored in memory from past sessions of procedures or stored in memory during the current session) with the current respiratory cycle and comparing deviations or changes as the assigned criterion of awakening or the occurrence of sleep fragmentation. Excessively rapid or excessively large changes in pressure often occur when the CPAP apparatus tries to correct the normal course of events unrelated to

OVDSH, or cannot detect the presence of weak manifestations of surface breathing, hypopnea or OVDSH, respectively. It is believed that the main cause of sleep fragmentation is rapid pressure changes in the patient's airways, which are caused by known ARAP devices.

In addition to the above, studies have also shown that some ARAP devices have limited ability to accurately detect the onset or decrease of shallow breathing, moderate hypopnea, or events

OVDSH This limitation may also relate to the limitations of these devices in terms of the interpretation of process curves.

Misdiagnosis of such events as mild hypopnea leads to an increase in LVDS, which in turn causes awakening and further fragmentation of sleep.

Currently known therapeutic equipment is not optimally adapted to minimize awakenings during therapy. The threshold of awakening for each patient depends on variable parameters, and the currently known equipment does not have adaptive control algorithms that could adapt the level of procedure parameters taking into account many of these variable parameters. These variables include (but are not limited to) sleep history events such as sleep deprivation or sleep propensity, physiological factors, psychological factors including (but not limited to) stress or anxiety, environmental factors including itself temperature, noise, lighting, vibrations, as well as factors such as a variable threshold of awakenings, which changes depending on changes in age, the influence of drugs and alcohol on thresholds of awakenings, etc.

As a result, in view of the disadvantages inherent in known methods of performing therapeutic procedures on patients who are asleep or trying to fall asleep, there is a need for a device and method for monitoring patient awakenings and adapting therapeutic procedures to minimize the occurrence of awakenings.

Disclosure of the essence of the invention

For clarity of explanation only, the invention is described primarily in the context of controlled gas delivery to a patient. One skilled in the art will appreciate that the invention is readily adaptable to other therapeutic procedures. Such therapeutic procedures may include ventilators, oxygen therapy machines, or pacemakers. Thus, the invention should not be limited to gas supply control.

This invention is made with the ability to maintain the quality of sleep of patients receiving therapeutic procedures by ensuring the sensitivity of the therapeutic equipment to various physiological indicators that predict the occurrence of awakening and applying an adaptive algorithm to change the parameters of the therapeutic procedure that the patient receives. Said algorithm for controlling the procedure of the present invention is made with the possibility of adaptation during operation in real time based on any combination of a) empirical clinical data, B) individually collected for the patient or alternatively (in the laboratory) collected data (from diagnostic studies in the sleep study laboratory or other alternative location) or c) real-time control and analysis data.

In one embodiment, this invention is made with the possibility of using empirical clinical data to establish standard threshold configurations, which in turn determine the response characteristics of the therapeutic equipment given by the current state of the patient. In the case of gas delivery devices, parameters such as rate of pressure change, absolute value of pressure change, minimum pressure injection values and maximum pressure injection values can be applied. In order to minimize awakenings while maintaining continuity of procedure, these rates and absolute magnitudes of pressure changes are adjusted based on various patient conditions, including (by way of example only) detection of the patient's current sleep state, or relative blood pressure, or arrhythmia. The present invention may be configured based on a fixed array of control data intended to predict the occurrence or detection of wake-up events.

In one of the variants of implementation, this invention is made with the possibility of functioning with or without any previous patient data. In the event that the object does not have any previous data or threshold readings, the present invention is made with the possibility of starting operation with standardized empirical data of threshold settings. During the creation by the device of pressure changes or in any case of respiratory disorders or the prediction of the occurrence of respiratory disorders, this invention is made with the possibility of adapting the control characteristics in order to minimize respiratory disorders and awakenings. Control characteristics are based on the speed and absolute values of changes in the pressure injected into the subject, together with the sensitivity of the equipment to detect weak manifestations of hypopnea, shallow breathing or OVDSH. Respiratory distress, wakefulness, or upper airway resistance may be detected by airflow monitoring equipment or more complex combinations of monitored physiological data channels. In its simplest configuration, the present invention can record and record the probability of awakening or upper airway flow restriction using the characteristics of the air intake signal graph (coming from the breathing mask circuit). This detection of desired graph characteristics can be achieved by detecting changes in the course of (1 or more) respiratory graph shapes and then comparing these changes to the likelihood of occurrence or actual reduction of hypopnea, shallow breathing, or ARDS.

According to one of the variants of implementation, the present invention includes an algorithm for detecting deviations in the course of air intake, which may be signs of a decrease or possible occurrence of resistance of the upper respiratory tract (UPR) or deviations of the UPR, awakenings associated with respiratory events (gezrigayugu emepi geiyayed agoizaye - VEVA, hereinafter PPRP) or awakenings associated with medical events (igeaitepi emepi geiiiai(ea agoiza!5 - TEVA, hereinafter PPLP). Such deviations in the course of air intake (and others) can be detected in the breathing mask of the patient receiving CPAP, oxygen procedures, lung ventilation, or other gas delivery or ventilatory support procedures.The ability to detect abnormalities in the flow of air allows the application of analysis techniques such as neural networks or other techniques capable of self-learning and algorithmic adaptation.

According to one of the implementation options, the methods of self-learning and algorithmic adaptation have special capabilities for detecting PPRP and PPLP. PPRP and PPLP can be detected by controlling cortical or subcortical! activity or by identifying the elements of the flow of air intake that correspond to the formation of such PPRP. In another option, only the methods of analyzing the amount and schedule of air intake can be used.

According to one of the implementation options, this invention is made with the possibility of detecting OVDSH, PPRP and PPLP in patients using such physiological parameters as the pulse wave propagation time (Ryive Tgapvii

Tite - RTT, hereinafter CHPPH) (ryize apegia! Yupoteyu - RAT, hereinafter ATP), plethysmographic wave amplitude, electroencephalogram (EES, hereinafter EEG), electromyogram (EMO, hereinafter EMG) and electrooculogram (ESS, hereinafter)

EOG) and others.

With the use of these methods and equipment for supplying gas under pressure (oxygen concentrator, artificial ventilation device, MRAP, CPAP, ARAP and others), it is possible to predict the events of OVDSH, PPRP and PPLP or the occurrence of such events and adjust the parameters of the procedure to avoid such events.

In one embodiment, the process of detecting and controlling awakenings can occur concurrently or in virtual real time with automated gas therapy algorithms that can be adapted to reduce or eliminate both sleep-disordered breathing and sleep fragmentation. The present invention is made with the ability to distinguish when the pressure adjustment of this gas supply device has too low sensitivity and leads to either the development of PPRP or PPLP, or to the inability to compensate for less noticeable (without detailed analysis of the graphs and possibly patient-specific calibration) or weaker manifestations of breathing disorders during sleep (5ieer Bgeaiinipd aizogaeg - 580, hereinafter RDS), for example, OVDSH, hypopnea events, as well as shallow breathing.

In order to simplify the understanding of the essence of the object for which protection is claimed, one of the variants of its implementation is shown in the accompanying drawings. From a consideration of these drawings, together with the following description, the nature of the claimed subject matter, its construction and operation, and most of its advantages should become apparent.

Fig. 1 is a schematic representation of one of the variants of implementation of the invention.

Figure 2 is a block diagram of wake-up control functions of the present invention.

Fig. 3 is a functional diagram of the air intake diagnosis process according to the present invention.

Fig. 4 is an example of a graph of the inhalation cycle with snoring.

Fig. 5 is an example of a graph of the inhalation cycle with OVDSH.

Fig. b6 is a functional diagram of one of the variants of the invention. ,

Fig. 7 is a schematic representation of one of the variants of implementation of the invention.

A. General overview

The invention covers a device and a method for maintaining the quality of sleep of patients receiving therapeutic procedures. The invention provides control and processing of signals of physiological parameters and spontaneous respiratory events in order to detect the occurrence of awakening. If the occurrence of awakening is detected, the invention provides for adjustments that are necessary in the functioning of the therapeutic equipment to avoid or minimize awakenings.

As shown in Fig. 1, according to one of the variants of the implementation of the present invention includes one or more sensors 10 that record the physiological parameters of the patient, a controller 12 that monitors and detects awakening based on the values of physiological variables received from the sensor, and the gas supply device 14, which is controlled by the controller 12. The sensor 10 can be a combination of one or more devices, which are made with the possibility of controlling physiological parameters, which are used according to the invention to determine the occurrence of awakening or the occurrence of a sleep disorder. These sensors can be combined into one device or can function independently of each other.

According to one of the implementation options, this invention is made with the possibility of detecting awakening using such physiological parameters as pulse wave propagation time (PWPT), arterial pulse tonometry (ATP), plethysmographic wave amplitude, electroencephalogram (EEG), electromyogram (EMG) and electrooculogram ( EOG) and others.

According to one of the implementation options, this invention is also made with the possibility of control, analysis and calculation of the course of the graphs and the sound of air intake. Patterns of breathing or waveforms or sounds from the patient are compared to various matrices associated with individual awakening events or breathing disorders during sleep.

According to one of the implementation options, the presence of RDS, OVDSH, surface breathing or their occurrence can be analyzed and calculated.

In one embodiment, the present invention provides for receiving a plurality of input signals from sensors and comparing these input signals with values entered in several tables. These tables identify different forms of respiratory and physiological parameters graphs or graphs and physiological data and serve to compare this information with specific events of awakenings or breathing disorders during sleep. In addition, various coefficients and equations may be applied to the values stored in this table to accommodate patient-specific variations.

According to one of the variants of implementation, this invention is made with the possibility of functioning in three different modes. One mode is the default mode, in which empirical data sets the thresholds and reference data that are used for optimal procedure control calculations. The invention also includes a calibration mode in which the patient's response to various settings is checked to determine the patient's tolerance. The invention also includes an adaptation mode in which optimal control of the Procedure is applied to minimize or eliminate wake-up or RDS events.

B. System configuration

According to one of the implementation options, the present invention includes three main blocks: a sensor for monitoring a physiological parameter, a therapeutic device for carrying out therapeutic procedures, and a controller for controlling the carrying out of these therapeutic procedures. The invention is described as having three main blocks, solely for the purpose of clarity of explanation. It is clear to a person skilled in the art that these three main blocks of the present invention can be seamlessly combined into one or more blocks.

In one embodiment, the present invention includes several sensors, some of which are used to detect upper airway resistance and air intake, and some of which are used to detect physiological parameters that are used to determine the state of wakefulness. This sensor can be any known device that has the ability to detect, measure or calculate a physiological parameter that is used to determine the state of awakening. This sensor can consist of a single combined device or several independent ones. These sensors can communicate with the controller using any known protocol.

According to one of the variants of the implementation, pressure sensors and a pneumotachograph are used, which are combined or are in interaction with the air hose or the patient's mask to determine the air flow and pressure in the patient's airways. Sensors such as EEG, EOG, EMG, ECG, pulse oximetry, blood pressure, carbon dioxide monitoring, sensors installed in the bed for monitoring the patient's position, processing systems are used to determine the physiological parameters according to the present invention, but are not limited to them. video images and microphones for monitoring breathing and breathing sounds.

In a preferred embodiment, all of these sensors are located in a single patient mask. A suitable mask is described in International Publication M/O 01/43804 entitled "Biomask with Built-in Sensors", the contents of which are incorporated into this application by reference in their entirety. This mask has built-in sensors that are designed to detect EMG, EEG, EOG, ECG, surface blood pressure, temperature, pulse oximetry, patient sounds, and gas pressure in this mask. This mask is designed with the possibility of sampling from the branch or from the main gas stream for real-time monitoring of the concentration of oxygen, CO", nitrogen oxide and other gases or any combination of the above gases. In addition, this mask controls the circuit for supplying gas to the patient.

In one embodiment, a mattress-based device is used to detect awakening.

At this time, there are two mattress models available on the market that can perform the aforementioned functions. One of them is known as a static charge-sensitive bed (bias Spagde-zepziyuye Wei - 5C58, hereinafter ChSZL), and the other is a polyvinylidene fluoride (made of piezoelectric RUOE plastic) bed.

In one embodiment, eye activity is used to control wakefulness.

The infrared video monitoring system is used as a sensor to determine the activity of the eyes using the position of the eyelid. The image signal from the video control is processed using a graphic processing program to determine the state of the eyes.

In one embodiment, the present invention includes an individual multi-standard wireless interface system. Typically, two separate wireless bands are used to separate physiological wireless signals from control data. In addition, a built-in encryption and security system can be applied to prevent unauthorized access to data.

An example of a typical implementation can be the use of the 2.4 GHz band of IZM (the range intended for industrial, scientific and medical applications) in the communication interface of wireless sensors with the controller.

Less critical data that does not affect the patient's condition during therapy, such as user viewing and reporting data, can pass through the M/-GAM interface or even wireless Wi-Fi devices. This multi-standard radio communication is an especially important consideration where operation is carried out with existing wireless systems. A further feature of the present invention is the detection of interference from radio systems of the same band and the transfer of critical signals and other control channels either to another channel or to the control of the adaptive analysis system without the use of wireless signals. This invention can be applied with various wireless electrode devices to provide easy expansion and access to additional physiological signals.

According to one of the implementation options, these sensors are powered by battery power, sufficient for a period of 1 or 2 days of transmitting signals to the controller. The possibility of wireless monitoring of this invention provides control of PPRP, PPLP and signals associated with RDS (breathing disorders during sleep) during the patient's sleep. In addition, the ability to monitor these electrodes during the patient's sleep may provide some additional information (in addition to the respiratory airflow, pressure signals, and sound normally obtained from the subject's mask), as well as the ability of the 5PAP system to provide optimal management of therapeutic pressure or gas inflow in order to minimize PPRP or PPLP, also minimizing obstructive sleep apnea/hypopnea (orvigisiime zIieer arpea-purorpea - O5AN, hereinafter OAGOS), as well as OVDSH.

Such a comparison of sleep quality during a traditional CPAP procedure or an improved (eg, with the use of additional wireless signals) CPAP can provide valuable information to the medical staff and the patient in understanding parameters of the patient's sleep quality. Similarly, the patient can select the position of the wireless position sensor, which can be located on the therapeutic breathing mask or other parts of the therapeutic equipment on the patient or on his clothing.

Said wireless electrode has several main functions that enable the application of this wireless technology with relatively convenient use inside the patient's residence or similarly also in the clinical environment. The electrodes of the present invention can be packaged in such a way that removal of the disposable outer packaging of the electrode activates the power batteries. This feature of automatic activation of the wireless electrode ensures automatic saving of battery life, especially during storage. The indication of the expiration date on the packaging of such a disposable electrode ensures the use of both the electrode of the right quality and the batteries with the right service life at the right time, protecting the user from the aging of the batteries and the reduction of the quality of the electrode. The wireless interface electrodes of the present invention may have self-adhesive properties to facilitate electrode installation. Disposable (or reusable) self-adhesive electrode devices can be attached by the patient with simple visual instructions.

These sensors feed their physiological data to a controller (including the pre-processing necessary to control the procedure), which receives the data and determines the state of wakefulness or the occurrence of wakefulness. In one embodiment, the controller includes an analog processing circuit that converts analog signals from sensors into a digital signal. This analog processing circuit uses known preamplification, amplification, matching, and filtering schemes to provide the ability to convert the sensor's analog signal to a digital signal. In some cases, such a sensor can directly provide a digital signal.

In one embodiment, such a controller also includes a processor that receives the digital signal and determines the patient's condition, as well as suitable settings for the gas delivery device or other therapeutic equipment. Such a processor contains a set of tables stored in a database. These tables contain a set of information elements that establish the relationship between the input signal from the sensor and the wake-up. Usually, several different physiological parameters are entered simultaneously, and all these parameters are factored into the definition of wakefulness. The processor can apply a system of weighting coefficients for each parameter, and appropriate actions are determined based on the obtained value of the indicator. In another embodiment, this processor can link a chain of physiological values together and compare with a table that establishes the relationship of this linked array of values with wakefulness.

According to one of the implementation options, the present invention includes memory blocks containing tables where recorded profiles containing normal or acceptable values for such physiological parameters as: sleep fragmentation, apnea/hypopnea index (ANI, hereinafter IAG) are stored . in sleep, occurrence of mixed apnea in sleep, occurrence of hypopnea, occurrence of peaks

EEG, occurrence of EEG spindles, occurrence of EEG K-complexes, occurrence of epileptic activity on EEG, values of the bicoherence index or bispectral index, potential index caused by auditory irritation, values of optimal pressure depending on the patient's posture, the patient's tendency to sleep, the patient's sleep state.

The controller communicates with the therapeutic equipment in order to control the level of parameters of providing the procedure to the patient. The controller determines the appropriate array of instructions using the levels of procedure provision parameters, which are in the information elements of the table and correspond to the patient's physiological condition. The processor then sends this array of instructions to the gas delivery apparatus, which then executes the array of instructions.

B. Wake-up control

As shown in Fig. 2, in this invention, various physiological parameters are used to determine the patient's awakening, as well as to adapt the air supply parameters to the patient's body in order to reduce the occurrence of awakenings to a minimum. Because of the complexity and variable nature of sleep states, and the large number of diagnosable sleep disorders, many different physiological parameters can be monitored and analyzed to determine wakefulness.

Minimizing awakenings includes the ability to automatically adjust the course of therapeutic procedures by monitoring at least one physiological parameter or signal, which may include (but are not limited to) the following monitored physiological parameter(s), signal(s), or quantity: blood pressure, patient movements, patient tremors, patient tremors, patient twitches, pulse oximetry, pulse wave, EEG, EOG, EMG, patient position, breath sounds, air flow signals, respiratory effort signal(s), pharyngeal pressure signals, PSO signals "expiratory, diaphragmatic EMG, total transthoracic impedance, electrocardiogram (ECG), reflex oximetry, pulse oximetry, oxygen saturation, nasal pressure, air supply pressure, air supply to breathing mask, breathing mask pressure, breathing mask sounds, sounds breathing, pressure during breathing, respiratory inductive plethysmography, plethysmographic wave, pharyngeal pressure, sensor signals into nasal cannulas, nasal and oral cannula sensor signals, oral cannula sensor signals, thermocouple sensor signals, thermistor sensor signals, RUO temperature sensor signals, RMO sound and vibration sensor signals, РМУБ0 breathing or air intake signals, pneumotachometer regulatory flow, or other clinical or experimental applications of polysomnograph (PSG) electrodes or control sensor signals.

According to one of the implementation options, the control of awakenings is carried out with the help of EEG. Typically, the forebrain is monitored to determine cortical arousals, and the brainstem is monitored to measure subcortical arousals. The occurrence of awakening is characterized by bursts of EEG signals of higher frequencies or a transition to alpha or theta activity from slower background frequencies, as well as, in some cases, a transient increase in skeletal muscle tone. Standard electrode placement schemes and EEG protocols can be used to measure awakenings.

According to one of the implementation options, this invention includes the ability to distinguish the awakening associated with periodic leg movements (regiodis Ied tometepi - RI M, hereinafter PRN), from the awakening associated with respiratory factors. Differentiating awakenings associated with PRN from awakenings associated with respiratory events may be important, particularly in cases where optimal management of the procedure may not depend on awakenings associated with PRN, but may need to respond to the awakenings , associated with respiratory events.

The present invention detects and distinguishes PRN and/or PRN awakenings by comparing subcortical awakenings detected by blood pressure deviations with cortical awakenings (EEG). Cortical awakenings are used to distinguish awakenings associated with sleep fragmentation and neurological events from subcortical awakenings, which generally include both awakenings associated with sleep fragmentation and neurological events and awakenings associated with PRN.

According to one of the implementation options, the occurrence of the wake is determined using the pulse wave propagation time (PWPT). Studies have shown that sleep disorders such as apnea, hypopnea, or upper airway resistance lead to a corresponding awakening, which is accompanied by changes in heart rate, a transient burst of sympathetic activity, and a spike in blood pressure.

Obstructive sleep apnea may be associated with a marked and measurable increase in intrathoracic pressure associated with obstructive efforts and effects on the ballistocardiogram. This effect on the ballistocardiogram occurs when the lungs exert pressure on the heart. This constricts the heart and reduces the volume of blood pumped by the heart. These changes in cardiovascular activity may be manifested by a transient but significant drop in the patient's baseline BP.

The LVEF is the time interval required for a pulse wave to pass between two arterial sections. Blood pressure is directly proportional to the speed with which this wave of blood pressure passes. An increase in blood pressure is associated with an acceleration of the pulse wave, i.e. a reduction in the systolic blood pressure. 1, on the contrary, a drop in blood pressure leads to a "slowing down of the pulse wave and an increase in CPPC.

According to one of the variants of the implementation, the CHPP is obtained with the help of sensors located on the above-mentioned biomask. The sensor receives input from the mask and generates a plethysmographic curve. The second sensor receives input from the mask and generates an ECG signal. These curves and the signal are fed to the input of the controller, where the calculations of the CHPPH readings are carried out.

The CIPPC is obtained using a plethysmographic curve obtained using pulse oximetry techniques in combination with an ECG signal. According to one embodiment, A or O, the ECG waves can be used as a starting point for the measurements of the CHPP, and the end point of the CHPP measurements can be a point located at 2595 or 5095 from the maximum value of the pulse wave height.

In one embodiment, EMG measurements are used to detect the patient's sleep depth level. The EMG control carried out according to this invention makes it possible to detect sleep-related changes in the patient's muscle tone. Sleep states are usually accompanied by changes in the tone of individual muscles.

Awakening usually leads to an increase in muscle tone.

In one embodiment, ECG and EMG signals from the diaphragm are monitored in combination to detect respiratory effort associated with central apnea versus obstructive apnea. Electrodes

ECGs are placed on the patient in order to distinguish diaphragmatic respiratory efforts from thoracic respiratory efforts. During central sleep apnea, breathing stops without respiratory effort. This is distinctly different from obstructive apneas, during which muscle activity increases as a result of increased respiratory effort to overcome airway obstruction.

According to one of the variants of the implementation, the patient's eye movements are monitored in order to assist in the determination of awakening. One technique involves the use of digital video recording and known graphic processing techniques to detect eyelid activity (ie, whether the eyelids are closed, open, or to what degree of opening).

In one embodiment, the detection of wakes is performed by monitoring the presence of signal deviations present in the analysis of the upper band (from direct current to 200 Hz or higher) of the airflow rate curve and the pressure curve obtained inside the breathing mask. Apnea, shallow breathing, upper airway resistance, and hypopnea events can also be detected and prevented by analyzing changes in the shape of the airflow and pressure curves while monitoring this upper band.

In addition to monitoring awakenings, one embodiment may monitor other physiological parameters to determine the patient's physical condition. In this invention, sensors in the biomask can be used to determine heart rate, ECG, respiratory rate, snoring sounds, air intake, air pressure, and oxygen saturation. Conventional methods can also be involved in the present invention to control blood pressure and CO." The position of the patient during sleep can also be monitored using pressure sensors or a special mattress.

In one embodiment, in which the patient receives a CPAP procedure, the monitoring of awakenings also includes monitoring the pressure and air flow corresponding to the patient's breathing in order to determine LVDS (which may cause PPRP). To prevent PPRP, it is necessary to identify several patterns that are indicators of sleep apnea symptoms, namely, airflow limitation during inhalation (smoothing), snoring, and a decrease in the amplitude of airflow (hypopnea and apnea). As shown in Fig. 3, in this invention, an analysis of the flow of air coming to and from the patient is carried out in order to determine the presence of OVDSH.

The "Breath detection" unit detects and registers the parameters of individual breathing cycles in real time. Inspiratory and expiratory peak detection includes "local" smoothing (to distinguish real respiratory cycles from noise interference) and "global" respiratory peak detection based on a relatively long history, which can include up to six consecutive inspiratory and expiratory cycles .

Analysis of inspiratory and expiratory cycles includes the precise determination of inspiratory intervals and the measurement of inspiratory flow parameters such as smoothing, snoring, and inspiratory amplitude, among others.

The "Processing by time interval" unit analyzes the received pressure and air flow signals based on the expiration of defined time intervals, not respiratory cycles. This is necessary in cases where breathing cycles are difficult to determine, such as during temporary pauses in breathing or when the mask moves away from the face.

The controller generates a pressure control signal based on the respiratory cycle information and time interval information provided by the two aforementioned units. The controller is a set of rules that take into account various combinations of indicators of flow restrictions, snoring, breathing amplitude, pressure loss and other parameters.

In one embodiment, the main strategy in detecting inspiratory and expiratory cycles is to use the maximum and minimum points (flow rate signal levels) as indicators of inspiratory and expiratory intervals. Inspiration corresponds to a positive change in the flow rate signal, and expiration corresponds to a negative change.

However, the flow rate signal can be distorted by a large amount of noise interference, ie, it is necessary to smooth the flow data before determining the real pattern of breathing (block 10050). Accurate detection of inspiratory and expiratory peaks also requires the use of a relatively long history to avoid confounding them with local maxima and minima of the flow rate signal.

In local smoothing, there are two main tasks. First, all local maxima and minima points of the flow rate signal are detected, after which each maximum point is determined as a preliminary candidate for setting the inhalation peak, and each minimum point as a preliminary candidate for the possible setting of the exhalation peak. The second task is to smooth out some points of maxima and minima with "relatively small amplitude", which should presumably be noise signals. As a result of local smoothing, only the points of maxima and minima with "relatively large amplitude" are preserved, and the flow rate signal is considered sufficiently smoothed. The sequence of local smoothing is described as follows: 1. Detection of all points of local maxima from the flow data array. 2. Formation for each maximum point of the picture, called max-peak where this maximum point is located in the center, the data on the left side monotonically increase, and on the left side monotonically decrease.

Forming an array of max-peak pictures for the current array of stream data.

C. For the same array of data, detection of all points of local minima and formation of a series of min-peak pictures using a similar method. 4. Calculation of several parameters such as signal change and duration for each max-peak and min-peak; these parameters are used as quantities to check whether some of the detected max-peak and min-peak patterns are actually noise interference. 5. Analysis of sequences of adjacent max-peaks and min-peaks (in each sequence the number of max-peaks must exceed the number of min-peaks by one, or alternatively the number of min-peaks must exceed the number of max-peaks by (one) and checking whether the sequence can be approximated by a single max-peak or min-peak in such a way that the approximation error will be much smaller than the parameters of change and duration of the final max-peak or min-peak 6. Application of piecewise linear approximation methods for the signal to noise interference signal smoothing flow rate 7. Storage of max-peaks with relatively large amplitudes, where for each "stored" max-peak both the "rise period" (left side) and the "decrease period" (right side) are at least a predefined threshold (0.75s) 8. The same method is used for the smoothing processing of min-peaks.

Local smoothing is mainly intended to eliminate noise interference signals that have a relatively small amplitude and duration. As a result, a large number of points of maxima and minima can be excluded from the array of "candidates" for designation as inhalation and exhalation peaks. Local smoothing processing can produce individual "rise periods" or "decrease periods", and the signal within the "rise period" or "decrease period" corresponds to the "probability" of a half-period of inspiration or expiration. This "half-period" smoothing process is one approach to removing small-signal noise interference. On the other hand, this "half-period" approach lacks the ability to smooth stream data, which contains some relatively large noise interference and artifacts.

Another serious problem in determining the respiratory cycle is related to changes in respiratory patterns. The flow rate signal is often influenced by patients who change their "pattern" of breathing, in other words, some periods of increase or decrease in the signal level are related to changes in the patient's respiratory "behavior" rather than to the inspiratory or expiratory cycle. Local smoothing cannot eliminate these kinds of max-peaks or min-peaks. However, it is possible to apply some measurements of a global nature in order to effectively detect these "incredible" max-peaks or min-peaks, and this represents the principle of global detection of respiratory peaks (global smoothing) (block 10080). In the process of global smoothing, multiple consecutive respiratory cycles are tested to further disqualify some max-peaks or min-peaks from the array of candidates for designation as inspiratory and expiratory peaks.

During a relatively long period of time (up to 3.5 min.), the parameters for pairs of consecutive max-peaks (also min-peaks) are checked, and an array of so-called max-pairs (or min-pairs) is formed. After that, several parameters for series of maxo-pairs are produced to obtain an array of max-pairs with similar "pictures", called a max-series. The same processing is carried out in order to form min-rows from min-pairs. Thus, there are two main parts to global smoothing, namely the formation of max-pairs (min-pairs) (block 10100) and max-series (min-series) (block 10110). The list below briefly describes the processing of max-pairs and max-rows in general terms (the formation of min-pairs and min-rows is carried out, respectively, using the same methods).

From the starting point of such an array of max-peaks, a pair of pictures of max-peaks is determined, which must meet the following conditions: (1). The duration of the interval between two max-peaks should be greater than the minimum duration of the respiratory cycle (0.756). (2). The duration of the interval between two max-peaks should be shorter than the maximum duration of the respiratory cycle (10s). (3). There are no intermediate max peaks within a max pair. An intermediate max-peak pattern is determined by the fact that the signal level at the maximum point of the intermediate max-peak pattern is greater than 80905 from the signal level at the maximum point of the max-pair itself.

This processing of the search data is carried out over the entire array of max-peaks in order to obtain a sequence of max-pairs. (4). For each max-pair, several statistical calculations are performed based on the difference between the output flow rate signal and the approximating lines in each max-pair.

The results of this processing are two, one of which is an array of max-pairs that are one step closer to the final array of inspiratory peaks, and the other is several statistical quantities that are used to describe the "shape" of this max-pair. In the further processing of the max-series, these statistical values are the basis for performing the "similarity" check.

The main method used to process a max-series is called a "similarity" check, that is, the "similarity" within a sequence of max-pairs is measured to form a sequence of max-pairs with a "similar" pattern, which is called a max-series. Only those maxo-pairs that have passed the "similarity" check can be included in the max-series. The principle behind the max series is that and. The sequence of normal respiratory cycles for a further period of time (3-6 respiratory cycles) should have similar forms, and this pattern should not undergo significant changes even during a fairly short period of time. and. If the max-parameter is not similar to this normal pattern of the respiratory cycle, it may be likely a respiratory event (apnea or hypopnea) or noise interference/artifact in the flow rate signal. Thus, the abbreviated statement of the max-row processing algorithm is as follows: 1. Each candidate max-pair must first meet the minimum duration requirement, which is defined as the distance between the candidate and the reference max-pair. 2. Starting from each individual candidate, several parameters are calculated, such as duration, signal level changes, max-peak (or min-peak) shape. Then, some statistics are calculated for this set of candidates, such as the mean, deviation, mean and maximum error for all elements to be tested for similarity among these candidates. 3. If they meet the condition of similarity, then such a group of max-pairs is formed into a max-row (block 10120). Otherwise, processing proceeds to the next max-pair until all max-pairs have been tested. 4. The same method is used to process mine rows. 5. Using the max-series and min-series arrays, it is now possible to detect the location of the global maximum points of the flow rate signal levels, which are associated with the inspiratory periods, as well as the minimum points, which are associated with the expiratory periods.

Global arrays of max-peaks and min-peaks provide the predicted locations for each respiratory cycle, i.e. inspiratory and expiratory peaks. In order to detect respiratory events, the following respiratory cycles should be considered in more detail, including: 1. Detection of the initial and final points of the inhalation interval (block 10130). 2. Performing flow smoothing (block 10150) and snoring analysis (block 10160), as well as calculating other breathing parameters.

During smoothing processing, a linear approximation method is used to smooth the stream data except for the maxima and minima points in the max-row and min-row data arrays. However, in order to analyze the respiratory cycle, it is necessary to "restore" the raw flow data using the points of maxima and minima as reference points before performing the respiratory cycle analysis.

In determining the inspiratory cycle, two steps are distinguished, namely estimation and fine-tuning. The inspiratory cycle interval is estimated on the assumption that the amount of air coming in during the inspiratory period should be the same as the "exhaled" air during the expiratory period. Using the maximum and minimum points of the flow rate signal as reference points, the inhalation interval is evaluated, that is, the initial and final points of inhalation based on the calculation of data areas on the flow rate curves.

However, this method as such has two problems that may affect the accuracy of inhalation determination. First, when measuring flow in a mask, the amount of air during an inspiratory period and the following expiratory period may not be the same, especially when patients use their mouth for breathing; we refer to this problem as "cost imbalance". Second, there may be a "dead zone" problem. As patients begin to inhale, the level of the flow rate signal increases rapidly, but measuring the area of the flow rate curve is an integration process that is much slower than changing flow rate signals per se. In other words, changing the area of the flow rate curve is not sensitive enough to accurately measure the inspiratory start point if the flow rate signal changes rapidly.

The area of the flow rate curve is first calculated to estimate the inspiratory interval, which includes the inspiratory start point and inspiratory end point. The start point of the expiratory period is defined simply as the end point of the previous inspiratory period, and the end point of the current inspiratory period is the start point of the next inspiratory period, or can be ignored if this point is not relevant in the control algorithms. Starting from the estimated starting point of the expiratory period, a "break point" within the rise period of the flow signal is determined by linear approximation methods, and this break point is then assigned as the starting point of this inspiratory interval. The endpoint of this inspiratory period is defined simply as the point at which the signal level is the same as at the initial inspiratory point, but after passing the maximum point.

As indicated above, this invention requires the detection of three types of respiratory events, namely apnea and hypopnea, snoring, and airflow limitation during inspiration. The first type of events (apnea and hypopnea) is associated with a decrease in air flow during inhalation and this can be determined directly from the detection of breathing. Both snoring and airflow limitation during inhalation are more likely to occur during periods of "abnormal" breathing. For "normal" breathing, the "shape" of the signal in the peak area of the airflow rate curve during inhalation is "rounded" and relatively smooth. In the presence of snoring, a high-frequency airflow rate signal is noticeable during inhalation, as shown in Fig.4. Inspiratory airflow limitation is defined as an event in which the patient is unable to produce a continuous increase in airflow during the first half of the inspiratory period. As a result, this flow rate signal in the peak flow rate area during inhalation becomes "flat", as shown in Fig.5. In the smoothing analysis, we define a reference "flat" line that can best match the flow signal at the peak of inspiration for the smallest root mean square error (Ieazi zdiage eitog - І5E, hereafter NSP), and the difference between the flow signal and the baseline "flat" line over this period is calculated as the smoothing error. There are several smoothing errors for the various selected baseline points. The smallest smoothing error is defined as the smoothing index. This smoothing index is used for airflow limitation measurements, and the lower the smoothing index, the more significant the airflow limitation during inspiration. The snoring index is also used to show the degree of snoring. This snoring index is defined as the result of measuring the magnitude of the high frequency airflow rate signal at the peak of the airflow rate curve during inspiration.

S. The principle of action

The functional diagram of one of the embodiments of the invention is shown in Fig. Exclusively for the purpose of clarity of explanations, the invention will be described according to one of the variants of implementation, made with the possibility of use with the CPAP apparatus. It will be understood by one skilled in the art that the invention is easily adapted for use with or incorporated into other therapeutic equipment.

In this invention, the validity of signals from sensors is checked (block 2). After checking these signals, they are analyzed to determine the occurrence of a wake (blocks 5, 6, 7 and 8). The data used in the analysis is defined by the user.

According to one of the implementation options, this invention provides the ability to apply various procedures with forced oscillations (egsei ozsiPasyop igeaytepi - ROT, hereinafter PZK) to determine patient-specific threshold values for awakenings and RDS. The results of the PPK are used to create matrices that are used to determine the appropriate response to a therapeutic procedure to prevent or eliminate cases of CAS, obstructive sleep apnea (orbzigisiime zierer arpea

О5А, hereinafter OAS), SOAGS (orzygysiime zieyer arpea/purorpea zupagote - OBAN5), PPRP and PPLP (block 3). These matrices or profiles are determined based on patient-specific diagnostic studies or appropriate CPD procedures in each individual patient's sleep phase or breathing state.

The present invention provides for obtaining patient-specific PFK matrices and profiles by applying forced pressure fluctuations, or changes in airflow pressure, in order to determine whether changes in the airflow pattern as a result of these weak manifestations of changes during the course of the procedure differ from the shape or characteristics of the profile that are indicators of the case or occurrence of awakenings (PPLP or PPRP), or

OAS and OVDIP. The technical solution according to this invention provides the possibility of changing the magnitude of pressure changes and the speed of changes in order to counteract such cases.

This device provides a means of downloading from sleep laboratory studies or other preliminary studies of sleep, respiratory and/or cardiac activity. This individual data is linked to the subject's breathing and arousal parameters and is used to adjust gas delivery equipment as needed to increase sensitivity and accuracy to minimize accidents

SOVDSH, SOAGS, PPLP or PPR, as well as to simultaneously minimize sleep fragmentation and optimize sleep quality (block 23). Each patient has an individual respiratory circuit and corresponding airways. Accordingly, the shapes of breathing schedules during all phases of sleep change from patient to patient. The ability of the present invention to accumulate personal empirical data of the patient provides the means to create a more sensitive and efficient algorithm of the procedure.

In one embodiment, if a wake is detected (block 11), then this invention determines whether the CPAP caused pressure changes (block 13), or whether this event was caused by the presence of the LVDS (block 14). If no pressure changes have been applied to the CPAP apparatus, then this invention will most likely determine that this wake occurrence is caused by PPRP or some other form of wake. If there were changes in pressure associated with

CPAP, the present invention would determine whether this wake occurrence is due to this pressure change or some other event (block 15). Appropriate remedies are then selected based on the patient's physiological signals and flow rate (block 18).

According to one of the implementation options, this invention is made with the possibility of applying the determination of the degree of adaptation of empirical data (unit 20). This provides for the invention the possibility of significantly increasing the sensitivity to the patient's physiological reaction.

Minimizing awakenings includes the ability to automatically adjust the parameters of therapeutic procedures based on at least one array of derived data or indices, which may include: upper airway resistance (UAR), respiratory event-related awakenings (RPE), awakenings related to associated with medical events (PPLP), respiratory disorder index (gezrigaigu aizishtrapve ipaeeh -

AOI, hereinafter IRD), index of respiratory awakening (hevrigaigu agoiza! ipdeh - VAI, hereinafter IRP), apnea/hypopnea index (AG), awakening (micro-awakening), awakening (cortical), awakening (subcortical), awakening (general), general awakening time, sleep phase, rapid or paradoxical sleep phase ("tary eaue tometepi" - VEM-sleep, hereinafter FSHS), sleep onset, body movements, percentage of sleep fragmentation by awakening (for all fragmented phases), sleep quality index, sleep fragmentation index (new -5РЙ, hereafter IFS - the total number of awakenings that cause sleep fragmentation, per hour), air intake curve shape trend, air intake curve shape matrix type, smoothing index, forced oscillation events, pressure change events, pressure change rate, curve graph of pressure change events, maximums and minimums of pressure change events, mixed sleep apnea events, central sleep apnea events, upper airway resistance syndrome (UARS5) events, events syndrome of obstructive apnea and hypopnea in sleep (OBAN5, hereinafter SOAGS), awakenings associated with respiratory events (PPRP) with filtering, qualification and display of relevant awakenings associated with respiratory efforts, awakenings associated with medical events ( PPLP) with filtering, qualification and display of pressure changes and awakenings, sleep quality index (new - correction coefficient of the sleep index per hour), awakenings related to quality, reduction of saturation (blood| oxygen, pulse wave propagation time (PWTP), arterial pulse tone (ATP), pulse wave amplitude (RU/A, hereinafter APH), desaturation events and artifacts of arterial blood oxygen saturation (saturation) (5rpm) - accurate detection of cascade desaturations, desaturations with artifacts 5brO" inside, places of beginning and end of artifacts 5ro", detection sequence of respiratory events with partial or reduced recovery, classification of respiratory events with noisy or poor quality effort signals, detection episodes of Chain breathing -

Stokes, concordance stability to enable quantitative comparisons between any two defined data sets, pneumotachometer flow, flow through a thermal sensor, total respiratory effort signal, EEG wake-up, CPP, plethysmographic waveform, total transthoracic impedance, detection and acceptance in calculation of the (most) bright areas of the shielding grid image for the expanded array of automatic events to include other events, events or syndromes of obstructive sleep apnea/hypopnea (OSA, OGS (О5Н - orvigisiime, ziiier purorpea - obstructive hypopnea in sleep), SOAGS) , awakenings related to respiratory efforts, central sleep apnea (SAS), central sleep hypopnea (SOS, hereafter CSH), Cheyne-Stokes breathing, hypoventilation, yawning, respiratory instability associated with changes in sleep state or occurrence deeper phases of sleep, swallowing, coughing, spontaneous or irregular but normal breathing signals, respiratory derivative volume (from nasal pressure or regulatory flow), derived flow restriction index (from nasal pressure or regulatory flow), derived snoring (from nasal pressure or regulatory flow), derived diaphragmatic EMG amplitude, derived upper airway resistance (from pressure mask, pharyngeal pressure and regulatory flow), derived subcortical arousals (from CPPC or braid-wave amplitude), respiratory mask sound and/or airflow analysis with segmentation for various respiratory disorders such as cough, wheezing, interruptions, apnea and hypopnea .

For each of the selected events (a combination of the array of the extended group of events from the aforementioned and the current array of events), the user has the opportunity to select an array of measurement signals and set the detection parameters of these events. This enables the invention to use more than one signal simultaneously to detect events and more than one scenario to detect events. The following are examples of defined events:

PPRP

1. A break in the flat profile of the inspiratory cycle after several breathing cycles with limited air flow 2. Changes in frequencies on the EEG, increasing amplitudes on the EMG 3. Further activity of leg movements

4. Absence of additional pressure (CONTROL signal)

Awakening associated with leg movements 1. Increasing activity of leg movements 2. Changes in frequencies on the EEG, increasing amplitudes on the EMG 3. Disruption of the inspiratory cycle profile is not necessarily during the inhalation itself 4. Absence of additional pressure (CONTROL signal)

Spontaneous awakening 1. Changes in frequencies on EEG, increase in amplitudes on EMG 2. Absence of growth (or after changes in EEG/EMG) activity of leg movements 3. Disruption of the profile of the inspiratory cycle not necessarily during inhalation itself 4. 4. Absence of additional pressure (CONTROL signal)

Awakening associated with additional pressure 1. Increase in pressure according to the titration algorithm 2. Further changes in frequencies on EEG, increase in amplitudes on EMG 3. Absence of increase (or after changes in EEG/EMG) activity of leg movements 4. Disruption of the profile of the inspiratory cycle not necessarily during the inhalation itself. The present invention significantly reduces awakenings by introducing limitations in the course of procedures carried out under pressure, as long as the patient is in such a phase of sleep that the pressure is not felt or does not cause any harmful effects and discomfort to the patient. The air pressure supplied to the patient's body increases or decreases depending on the patient's sleep state. The pressure rises slowly with the simultaneous control of physiological parameters. As soon as these physiological parameters indicate the occurrence of awakening (microawakening), the pressure is maintained at the same level or reduced until the patient is in a deeper sleep, when it is possible to continue to raise the pressure. Pressure reduction is performed accordingly.

The controller 12 is made as a combination of rules for changing the pressure. Any pressure change rule specifies the magnitude and sign of the pressure change and the allowable range of pressure values within which pressure changes can occur, as well as several additional parameters, including time constants, pauses, and forced oscillation logic.

Any pressure change rule is activated if the corresponding logical combination of its conditions takes the value of true. According to one of the implementation options, the pressure change rules are combined using a logical operation

OR - the pressure changes if any individual rule in this rule array is satisfied. If multiple rules are satisfied, the rule with the highest priority is preferred.

The conditions for different pressure change rules represent several physiological scenarios:

Limitation of the flow (smoothing) during several consecutive breathing cycles - pressure increase

Flow restriction (smoothing) and snoring during several consecutive respiratory cycles - pressure increase

Snoring during one or two breathing cycles is an increase in pressure

Hypopnea - increased pressure (it is recommended to use additional information such as CPAP, cuff or mattress signals to distinguish obstructive hypopnea from central hypopnea)

Detection of the beginning of apnea - the beginning of forced oscillations

Low level of conduction of the upper respiratory tract with forced oscillations - increased pressure (obstructive apnea detected)

There are no flow restrictions (rounded shape of the breathing curve) - a gradual decrease in pressure

A large loss - a decrease in pressure to 4 cm of water.

There is no air flow during Zhv. - pressure reduction up to 4 cm. water station

This invention is made with the possibility of overcoming the variable factors that depend on the awakening, by applying the methods of adaptive algorithms. These adaptive algorithm techniques are able to use empirical clinical data to establish standard threshold configurations, which in turn determine the response characteristics of the apparatus and its functional characteristics in terms of gas supply parameters. The mentioned methods of adaptive algorithms are also able to use arrays of threshold characteristics.

In one embodiment, these threshold characteristics may vary parameters such as rate of pressure change, absolute magnitude of pressure change, minimum pressure input values, and maximum pressure input values. These rates and absolute magnitudes of pressure changes may vary depending on the condition of said patient, including (by way of example only) detection of the patient's current sleep state, or relative blood pressure, or arrhythmia. The present invention can be configured in a preset mode of operation, when the algorithm adaptation function can be disabled and replaced by an algorithm based on a fixed array of reference data designed to predict the occurrence or detect the presence of PPLP and PPRP while minimizing breathing disorders during sleep.

In one embodiment, the present invention is designed to allow medical professionals to set different threshold parameters that may prevent adverse medical conditions for each specific patient. For example, if central sleep apnea is detected in combination with an increase or unwanted change in ECG parameters, pulse waves, or arrhythmias, the intensity of the gas delivery devices is increased to stabilize the patient's condition. In some cases, this stabilization may include immediate shutdown of pressurized gas supply. During events such as central sleep apnea (stopping of breathing caused by brain commands in response to an obstructed airway), for example, forced pressure injection without an obstructed airway can otherwise impair the subject's blood pressure or cardiac function.

The present invention is designed to function with or without prior patient data (eg, specific characteristics of the airflow curve or various threshold characteristics). In the event that the object does not have any previous data or threshold readings, this invention is made with the possibility of starting operation with standard empirical data of threshold settings. During device-induced pressure changes or the presence of any respiratory disturbances, the present invention can adapt its control characteristics to minimize these respiratory and wake disturbances.

According to one of the variants of implementation of the control of awakenings, the invention is able to increase the possibilities of detecting sleep disorders associated with CPAP. False-negative results often occur during moderate hypopnea events. These are usually such minimal limitations of air flow that CPAP devices are unable to detect breathing disorders. However, such moderate events often create an ASD sufficient to induce awakening in the patient. Detection of the occurrence of such awakenings according to the present invention ensures the initiation of a corrective response by the CPAP apparatus even when the CPAP cannot detect this event.

According to one of the implementation options, the mode of carrying out the procedure includes the use of matrices of the breathing pattern, which are stored in the table, in order to increase the intensity of the current CPAP settings. These dynamic matrices of breathing patterns complement the CPAP algorithm by changing the control characteristics of the CPAP equipment. Such matrices meet a patient's specific pressure requirements while optimizing that patient's sleep state and minimizing patient awakenings.

According to one embodiment, the present invention is made with the possibility of providing the procedure with a predetermined sleep state, level of awakening activity and/or a predetermined level of breathing activity for a sleep disorder. One of the problems that patients face when using known gas supply equipment for the procedure, there is discomfort due to positive air pressure being applied to the patient while he is trying to fall asleep.

Known devices have the ability to delay the start of the procedure. Such a delay function provides a time delay before starting to slowly increase the pressure or bringing it to a specified initial pressure value. However, patients cannot always predict the onset of their sleep state, as the patient's tendency to sleep changes each evening. The principle of a predetermined time delay can also lead to psychological anxiety, as the patient is constantly worried about whether a sufficient state of sleep will be achieved in the appropriate period of time; he expects unpleasant sensations of excessive air pressure while preparing for sleep.

This invention is made with the possibility of detecting the state of sleep and/or awakenings as a means of determining the time of pressure increase. Procedures are performed only when that patient is in a predetermined or deep sleep state and the ability to begin the procedure is apparent. Determining the state of sleep can be accomplished by known methods, including methods described in US Patent No. 397,845, the contents of which are incorporated herein in their entirety.

According to one of the implementation options, the present invention has a built-in diagnostic and procedure mode, in which the regulation of the air supply is carried out in real time (that is, changes are made immediately depending on the values of the monitored parameters).

The control algorithm of the present invention is designed to be adaptable during operation in real time based on any combination of a) empirical clinical data, B) individually collected for the patient or alternatively (in the laboratory) collected data (from diagnostic studies in a sleep study laboratory or other location) or c) real-time control and analysis data.

Yur. Alternative implementation options

In one of the alternative embodiments, as shown in Fig. 7, the present invention is used to administer medication to a patient. Previous methods of determining the appropriate dosage of sedatives or tranquilizers for a patient were often based on evaluation of a generalized patient population or a specific patient population.

A patient's tendency to sleep or wakefulness is a very complex issue, it depends on many parameters. For example, it has been established that a person's tendency to sleep may be related to sleep deprivation, alcohol exposure, anxiety, stress, environmental factors, body mass index, gender, hereditary and other factors.

Consequences of sedative drug overdose include increased wake time, risks of attention deficit disorder associated with excessive sleepiness, increased drug costs, and decreased quality of life due to the patient's prolonged sleepiness.

Administration of drugs can be by many methods, such as (but not limited to) oral, transdermal, dropper delivery, vapor and gas inhalation. By combining a drug delivery system with the present invention, drug dosage can be optimized to a predetermined level or a corresponding level of sleepiness, wakefulness, or alertness.

The user or health care professional can adjust the dosage of drug administration in consultation with the patient and using patient monitoring data.

A further possibility of the present invention is the use of sensors, such as motion-sensitive devices, which, together with signal analysis (such as, but not limited to, spectral, phase, and amplitude), can detect twitches, tremors, and other indications of drug administration. . In case of illness

Parkinson's and other diseases, this system can be programmed to administer, for example, appropriate medications to reduce tremors and twitches, while providing the patient with a defined state of wakefulness during the day and quality of sleep during the night that best meets the level of individual quality of life needs or wishes of each person .

This invention can be adapted to numerous configurations of equipment with various combinations of channels for recording physiological parameters, sensors, means of analysis, storage and display of information. These tools may vary depending on the specifics of the diseases and disorders to be treated, as well as the specific individual information requirements of healthcare professionals.

In another alternative embodiment, as shown in Fig. 7, the device of the present invention includes a pacemaker control algorithm that minimizes PPRP and PPLP, optimizing the patient's heart rhythm. This invention is made with the possibility of detecting PPRP and PPLP using an electrocardiogram or, for example; pulse wave signals. Alternatively, more complex signals can be used. This invention is made with the possibility of normal optimization of rhythms

ECG with simultaneous reduction of awakenings and sleep fragmentation to a minimum. Pacemaker management may also be used to help with some sleep-disordered breathing conditions. The present invention may provide important feedback for identifying causes of sleep fragmentation, such as inappropriate pacemaker control that causes awakenings that contribute to sleep fragmentation.

The present invention is also capable of monitoring heart rhythm, blood pressure changes, and awakenings that cause sleep fragmentation, and determining whether said changes relate to normal sleep physiology or whether these changes require changes in pacemaker control parameters to optimize cardiac function , while minimizing sleep fragmentation.

According to another embodiment, the present invention provides optimal sleep during procedures with increased oxygen concentration by using cortical, subcortical parameters, as well as characteristics of air flow or curves of these parameters as indicators for optimizing the procedure. The present invention provides control of the titration algorithm to minimize PPRP and PPLP with optimization of the respiratory procedure received by the patient. The present invention provides detection of PPRP and PPLIP by monitoring using any combination of sounds in a breathing mask or hose, signals of air or pressure. In another variant, more complex signals can be used. The control system ensures the usual optimization of the state of gas in the subject's blood, with the minimization of awakenings. For example, a mismatch in the mixture of oxygen and air or the rate of gas supply to the patient's body can contribute to the occurrence of awakenings.

Inadequacy of gas supply can, in turn, cause through mechanical or chemical receptors of the anatomical structure of the patient's airways to initiate awakenings that cause sleep fragmentation (SSL). Control of the shape of the air supply curve can be used to predict the occurrence of cases of PPLP or PPRP, providing the possibility of controlling the gas delivery procedure in such a way as to minimize such awakenings (while maintaining the function of optimizing the delivery of the breathing procedure).

In one embodiment, the present invention is used purely as a diagnostic tool for detecting breathing disorders that cause sleep disorders and determining sleep quality. The present invention is adapted to record, measure, index, or display in real-time, or playback or review, numerous physiological: or statistical sleep or wake data. Statistics and indices such as IPR, IAH, PPRP, IRD, awakenings, sleep fragmentation index or sleep patterns are obtained from monitored parameters and this information is stored for analysis.

According to one of the options, control of physiological parameters is carried out, which are used to obtain statistical data and indices, which can also be stored for use in the analysis. The present invention may also include known graphical and statistical tools to enable the user to manipulate and display raw data or derived values in an understandable format. In one embodiment, the present invention is made with the ability to display raw data and then apply visual cues to indicate events such as wake-ups among the raw data. The present invention is also made with the possibility of associating an event or events with specific index values or derivative values that indicate the presence of this event.

The subject matter set forth in the preceding description and in the accompanying figures is provided for illustrative purposes only and does not constitute a limitation of the scope of the invention. Although specific embodiments have been shown and described, it will be apparent to one skilled in the art that changes and improvements may be made without departing from the spirit of the invention. The existing scope of the claimed protection is defined in the following claims, considered in due perspective based on the existing state of the art.

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Claims (57)

1. The method of supplying gas under pressure to a sleeping patient, which includes: determining the sequence of supplying gas under pressure; control of a physiological parameter, which is an indicator of awakening; determining whether this controlled physiological parameter indicates the occurrence of awakening; as well as adjusting the level of the parameters of the procedure in order to avoid awakening. 2. The method according to item I, which also includes the operation of determining whether the awakening is caused by the resistance of the upper respiratory tract (URP), or the level of the parameters of the procedure. 3. The method according to item I, which is characterized by the fact that the adjustment operation includes changing the level of procedure provision parameters until such a level of procedure provision parameters is determined that does not cause awakening. 4. The method according to claim 3, which also includes the operation of storing in the memory the parameters of providing the procedure, which do not cause awakening. 5. The method according to item I, which differs in that the control operation includes control of cortical or subcortical activity. 6. The method according to claim 5, which differs in that the determination operation includes detecting changes in the activity of alpha or theta EEG rhythms with a lower background frequency. 7. The method according to item I, which is characterized by the fact that the determination operation includes the detection of the pulse wave propagation time drop (PWTP). 8. The method according to item I, which also includes calculating the value of the index based on several controlled parameters and using this value of the index to predict the occurrence of awakening. 9. The method according to claim 1, characterized in that the determination operation includes comparing the patient's airflow graph with a plurality of matrices that show the occurrence of awakening. 10. The method according to claim 1, which includes the additional operation of creating correlation tables of the combination of parameters of physiological events in order to optimally adjust the parameters of the procedure that minimize awakening. 11. The method according to claim 10, which is characterized in that the operation of determining includes detecting whether the event is associated with central apnea or obstructive apnea. 12. The method according to claim 1, which is characterized in that the operation of determination includes the use of specific individual data of the patient to determine the threshold parameters for awakening. 13. The method according to item I, which differs in that the determination operation includes a comparison of cortical and subcortical activity to determine awakenings associated with periodic leg movements. 14. The method according to item I, which includes an additional operation of determining the parameters of the patient's sleep state and adjusting the parameters of the procedure based on the parameters of the patient's sleep state. 15. The method according to claim 1, which is characterized in that the determination operation includes detecting changes in the measurement results of residual carbon dioxide levels, residual nitrogen oxide levels, or residual oxygen levels. 16. The method according to item I, which includes an additional operation of transmitting data to the therapeutic equipment to enable this therapeutic equipment to determine a procedure parameter that minimizes awakenings or breathing disorders during sleep. 17. The method of controlling the supply of gas to the patient's body, which includes: controlling the physiological parameter; gas supply with the set level of parameters; determining the occurrence of awakening, based on the physiological parameter; determination of whether the occurrence of awakening is caused by resistance of the upper respiratory tract or gas supply; and adjusting gas delivery parameter levels based on whether the awakening is related to upper airway resistance or gas delivery. 18. The method according to claim 17, which also includes applying a forced oscillation procedure to determine threshold levels of parameters for awakening. 19. The method according to claim 17, which includes an additional operation of determining the occurrence of awakening associated with respiratory efforts. 20. The method according to claim 17, which also includes the operation of determining the occurrence of obstructive apnea/apnoea in sleep. 21. The method according to claim 17, which also includes creating a table containing a plurality of elements that determine the occurrence of an event based on an array of values for a plurality of different controlled physiological parameters. 22. The method according to claim 17, which includes an additional operation of regulating the pressure level of the supplied gas, based on the value of the index obtained on the basis of at least one of the set of controlled physiological parameters. 23. The method according to claim 17, which also includes the operation of determining the quality of sleep. 24. The method according to claim 17, which also includes the operation of determining Cheyne-Stokes respiration. 25. The method according to claim 17, which also includes creating a table that relates a plurality of values from monitored parameters and events, and updating this table to accumulate patient sensitivity data. 26. The method according to claim 17, characterized in that the detection operation includes monitoring the upper band of the airflow rate curves or pressure curves to detect awakenings or breathing disorders during sleep. 27. The method according to claim 17, which is characterized by the fact that the determination operation includes the analysis of pulse wave propagation time, blood pressure, as well as EKI signals to determine the occurrence of awakening. 28. The method according to claim 17, which is characterized in that the determination operation includes an analysis of the patient's respiratory cycle to determine periodic respiratory events. 29. The method according to claim 17, which also includes the operation of determining the presence of mouth breathing and in which the adjustment operation includes compensation for mouth breathing. 30. A device for monitoring and controlling the flow of gas supplied to a sleeping patient, which includes: a sensor for detecting a physiological signal; therapeutic equipment for monitoring and regulating the flow, which ensures an adjustable level of gas flow; as well as the controller interacting with the sensor and equipment, made with the ability to detect the occurrence of awakening, based on the detected physiological signal, and with the ability to adjust the flow level in order to avoid awakening. 31. The device according to claim 30, which is characterized by the fact that the therapeutic apparatus is a gas supply apparatus. 32. The device according to claim 30, which is characterized by the fact that the therapeutic equipment is an infusion device. 33. The device according to claim 30, which is characterized by the fact that the therapeutic equipment is a pacemaker of the heart. 34. The device according to claim 30, which also includes a storage device containing a table of correlation values of a set of physiological parameters with the occurrence of awakening. 35. The device according to claim 30, which also includes a storage device that contains a table of correlation of the parameters of the occurrence of the awakening with the corresponding levels of the parameters of the provision of the procedure. 36. The device according to claim 30, which is characterized by the fact that the controller is also made with the possibility of predicting the occurrence of obstructive apnea/apnoea in sleep. 37. The device according to claim 30, which is characterized by the fact that the controller is also made with the possibility of performing a trial change of the level of parameters of providing the procedure in order to determine the sensitivity of the patient to the awakenings associated with the procedure. 38. The device according to claim 30, which is characterized by the fact that the controller is also made with the possibility of controlling the quality of sleep. 39. The device according to claim 30, which is characterized by the fact that the controller is also made with the ability to determine the value of the index, based on a set of different physiological signals, and with the ability to adjust the parameters of the procedure based on this value of the index. 40. A device for monitoring the physiological state of a sleeping patient, which includes: a plurality of sensors for monitoring a plurality of physiological signals; a processor made with the ability to detect the occurrence of awakening based on a set of physiological signals. 41. The device according to claim 40, characterized in that the sensors include EEG sensors. 42. The device according to claim 40, characterized in that the sensors include EMG sensors. 43. The device according to claim 40, which is characterized by the fact that the sensors include an air flow sensor. 44. The device according to claim 40, which is characterized by the fact that the sensors include an ECG sensor and a 5roO sensor, in which the processor is made with the possibility of calculating the PNPC. 45. The device according to claim 40, characterized in that the sensors include a body position sensor. 46. The device according to claim 40, which is characterized by the fact that the processor is made with the possibility of testing the patient's sensitivity to awakenings. 47. The device according to claim 40, which also includes a memory device, made with the ability to store values of physiological parameters that indicate awakening for a specific patient. 48. The device according to claim 40, which also includes a storage device, in which the processor is configured to store physiological signals in the storage device. 49. The device according to claim 40, which is characterized by the fact that the processor is made with the ability to display raw data and indexes obtained on the basis of physiological parameters according to the formats selected by users. 50. A device for supplying gas, which includes: a set of sensors for monitoring a set of physiological parameters; gas supply equipment that provides an adjustable pressure level; as well as the controller interacting with the sensor and the gas supply equipment and made with the possibility of detecting the occurrence of a wake-up due to PPRP or PPLP reasons, as well as with the ability to adjust the pressure level provided by the gas supply equipment accordingly. 51. The gas supply device according to claim 50, which is characterized in that the gas supply apparatus is a CPAP apparatus. 52. The gas supply device according to claim 50, which is characterized in that the gas supply device is a ventilation device. 53. The gas supply device according to claim 50, which is characterized in that the gas supply apparatus is an oxygen concentrator. 54. The device for supplying gas according to claim 50, which is characterized by the fact that the controller is also made with the possibility of receiving and storing individual physiological parameters of a specific patient, which indicate the occurrence of awakening. 55. The device for supplying gas according to claim 50, characterized in that the plurality of sensors are in communication with the controller using wireless communication. 56. Device for administering drugs, which includes: a set of sensors; medication administration equipment that provides an adjustable level of medication administration; as well as a controller that interacts with sensors and medication administration equipment and is made with the ability to adjust the level of medication administration based on the parameters of the patient's sleep state. 57. Heart rate control device, which includes: a set of sensors; heart rhythm driver made with the possibility of adjustable control of output parameters; as well as a controller that interacts with sensors and a pacemaker and is made with the ability to adjust the output parameters of the pacemaker in order to minimize awakenings.