Artificial intelligence-based and computer-controlled sedation and general anesthesia application

Abstract

The invention relates to an application designed to be used in general anesthesia and sedation applications, which can use multiple parameters and adjust medication and anesthetic gas dosages and the amount of fluid according to these parameters.

Description

[0001] ARTIFICIAL INTELLIGENCE-BASED AND COMPUTER-CONTROLLED SEDATION AND GENERAL ANESTHESIA APPLICATION Technical Field of the Invention

[0002] The invention relates to an artificial intelligence-integrated system designed for use in general anesthesia and sedation processes.

[0003] State of the Art Regarding the Invention

[0004] The anesthesia and sedation applications are carried out in order to make the patients unconscious (general anesthesia) or to numb them loacally (local anesthesia) during any surgical procedure or applications that require immobility and thus to make them insensitive to pain. In these applications, it is not possible to establish a standard in the medications and dosages used depending on many factors such as the procedure to be performed on the patient, the patient’s health history, the medications used, age, height, weight, gender, harmful substance habits and physiological characteristics of the patient. Depending on the sedative / hypnotic medications, muscle relaxants, analgesics used in over or under doses during anesthesia, there may be differences in the desired level of anesthesia in general anesthesia and sedation applications, loss of sensation is not sufficient, patients’ state of alertness and / or awareness under general anesthesia and differences in postop pain levels can be seen.

[0005] As a result, all the above-mentioned problems have made it necessary to realize a novelty in the relevant field.

[0006] Objects and Summary of the Invention

[0007] The main object of the invention is to overcome the lack of standardization in general anesthesia and sedation processes and to create a system that can automate these processes.Accordingly, the invention is trained by an artificial intelligence model to predict the need for blood or liquid electrolytes that patients will require as a result of the tests performed on them. In addition, the artificial intelligence can also be used in anesthesia and sedation applications in real time by training it with data such as medications, etc. that need to be used in different conditions that may be encountered in general anesthesia and sedation processes.

[0008] Definitions of Drawings Describing the Invention

[0009] In order to better describe the device developed with this invention, the drawings used and the related descriptions are as follows.

[0010] Fig. 1 Representative view of the system of the invention

[0011] Definitions of the Elements / Sections / Parts of the Invention

[0012] In order to better describe the device developed with this invention, the parts and sections in the drawings are numbered and the equivalent of each number is given below.

[0013] 1. Patient bed

[0014] 2. Medication and anesthetic gas connection

[0015] 3. Medication unit

[0016] 4. Connection between processing unit and medication unit

[0017] 5. Processing unit

[0018] 6. Data transfer cable

[0019] 7. Examination unit

[0020] Detailed Description of the Invention

[0021] The subject of the invention relates to general anesthesia and sedation processes integrated with the artificial intelligence.

[0022] With reference to Fig. 1, the processing unit (5) is configured to analyze the data received from the patient’s tests and data such as the patient’s age, height, weight, gender and harmful habits and, based on these analyses, to determine the medications that should be used asoutput and the dosages of medications and anesthetic gases. The processing unit (5) generates a signal carrying this information and transmits this signal to the medication unit (3) and the connection (4) between the processing unit and the medication unit is provided in a wired or wireless way.

[0023] A preferred embodiment of the invention may comprise an examination unit (7) for real-time monitoring of vital signs and examination of a patient. Said examination unit (7) examines at least some of the patient’s ventilation parameters, preferably all ventilation information obtained from the patient, set on the ventilator, and all of alarm parameters, at least some of hemodynamic status, preferably all invasive and non-invasive data obtained from the patient, blood gas checks, preferably arterial and / or venous blood gas data, invasive monitoring parameters, levels of consciousness, pupil size, BIS (bispectral index), which determines the level of consciousness under general anesthesia and sedation in real time, and evaluates the results of the examinations and tests performed in the examination unit (7) and determines the patient’s fluid electrolyte needs and blood product needs. In addition, the level of muscle relaxation is also controlled in real time with neuromuscular (NMT) monitorization. From there, the examination unit transfers the data to the processing unit (5) via a wired or wireless connection using a data transfer cable (6).

[0024] The invention comprises a medication unit (3) for storing medications and anesthetic gases to be administered to the patient lying in the patient bed (1). Said medication unit can also receive the signals generated by the processing unit (5) and according to this signal, it can adjust the dosage of the medication and anesthetic gas given to the patient and transfer it to the patient or transmit it to the healthcare professional (such as a physician, nurse, anesthesia technician) with the help of a screen therein. The invention may further comprise a medication and anesthetic gas connection (2) to enable this.

[0025] General anesthesia application consists of three stages and the invention can carry out all three stages with the elements mentioned above and described in the drawings. The first stage of general anesthesia application is anesthesia induction, in which stage the medications necessary for anesthesia are delivered to the patient. This stage is achieved with sedative / hypnotic medications, opioid analgesics and muscle relaxants. The patient is secured with airway intubation or other airway devices (such as LMA) and the controlled ventilation is started by making the necessary ventilation settings on the anesthesia device.The second stage is the maintenance of anesthesia, in which stage the patient is anesthetized. This stage is achieved with intravenous hypnotics and / or inhalation anesthetics. If pain relief is required, opioid analgesics given intermittently or by infusion and the muscle relaxants may be used if deemed necessary.

[0026] The third stage is waking up from anesthesia, i.e., extubation. At this stage, towards the end of the surgical operation or procedure, the anesthetic medications and opioids are reduced, anesthesia is superficialized, and the patient is awakened from anesthesia and extubated with medications that reverse the muscle relaxant effect.

[0027] In anesthesia processes, the patients’ ventilation parameters, hemodynamic status, blood gas controls, invasive monitoring parameters, consciousness levels, pupil sizes, BIS (bispectral index), which determines the level of consciousness under general anesthesia or sedation, are controlled in real time. In addition, the level of muscle relaxation is also controlled in real time with neuromuscular (NMT) monitorization. In addition to these, the patient’s age, height, weight, gender and bad habits are also used in the anesthesia process.

[0028] The problems mentioned in the prior art are encountered, such as remaining awake or aware under general anesthesia, not knowing the exact level of anesthesia due to lack of objective data when adjusting the doses of general iv hypnotics or the doses of inhalation anesthetics, not being able to use appropriate doses due to lack of objective criteria for the use of muscle relaxants, and similarly, not being able to determine the exact doses of analgesics.

[0029] With the artificial intelligence, the invention will teach the machine how each parameter monitored during the general anesthesia or sedation applications is monitored and in which cases which interventions and changes are made, and will transfer these to the artificial intelligence. For example, if a value of 50 is to be targeted on the BIS monitor during the monitoring of the level of consciousness, how the amount of anesthetic gas, opioid analgesia doses or doses of sedative / hypnotic medications are adjusted to reach this target in our clinical applications will be transferred to the artificial intelligence with the machine learning. With this model, a standard model will be created that will teach what should be done in which situations according to the targeted values of each parameter monitored, so that fewer sideeffects and problems will be encountered during the general anesthesia and sedation applications, and less awareness and wakefulness will be seen under the general anesthesia.

[0030] The invention may preferably also include a screen that allows doctors to check the patient’s examination results and the medication, anesthetic gas and dosages thereof.

Claims

CLAIMS1. An anesthesia system, characterized in that it comprisesa processing unit (5) configured to generate a signal that determines the dosage of medication and anesthetic gas by analyzing the results of examinations with artificial intelligence and transmits this information,a medication unit (3) that stores medications and receives signals sent by the processing unit and delivers medication and anesthetic gas to the patient in prescribed dosages, at least one medication and anesthetic gas connection (2) to transfer the necessary medication and anesthetic gas to the patient.

2. An anesthesia system according to claim 1, characterized in thatit comprises an examination unit that can examine at least one of the ventilation parameters, hemodynamic status, blood gas controls, invasive monitoring parameters, consciousness levels, pupil sizes, BIS and muscle relaxation level data and transfer them to the processing unit.

3. An anesthesia system according to claim 1, characterized in thatit comprises a processing unit configured to analyze data such as the patient’s age, gender, height, weight and harmful habits with artificial intelligence.

4. An anesthesia system according to claim 1, characterized in thatit comprises at least one screen that allows the doctor to check the patient’s examination results, and the delivered medications and dosages.

5. An anesthesia system according to claim 1, characterized in thatit comprises at least one dosage control unit to adjust the medication and anesthetic gas dosage.

6. An intelligence-based anesthesia system according to claim 1, characterized in thatit comprises a processing unit that processes the medication and anesthetic gas dosage with artificial intelligence in real time according to the surgical process and the patient’s examination results.

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