Currently, the probability of extreme situations in the world is increasing, and people are increasingly exposed to them. There is a tendency for some people to consciously seek to live through such experiences by taking risks and creating extreme situations. The modern pace and rhythm of our lives can cause mental tension in people, the extreme form of which is stress. Situations and factors that lead to its occurrence are referred to as extreme. Working in extreme conditions implies high risk, the need to make an appropriate decision, great responsibility for the task and the presence of unforeseen obstacles. Under extreme working conditions, the usual work and rest schedule is often disrupted [1]. All this places increased demands on the monitoring and diagnosis of a person's emotional state.

Severe emotional and physical stress creates the conditions for mental and somatic disorders and, in some cases, suicide. Under such extreme working conditions, it is important that a person's emotional state is stable without stress, as there is a risk of emotional exhaustion (or emotional burnout) [2, 3]. Emotional burnout syndrome has been included in the International Classification of Diseases [4], which only increases its importance for personal and professional development. Emotional exhaustion is characterized by constant physical, psychic, and moral fatigue, insomnia, headaches, eating disorders, loss of interest in favorite activities, irritability and stress [5].

People in an emergency situation must be able to constantly monitor their condition, make quick decisions, evaluate the situation appropriately, and sometimes even be able to sacrifice their lives in an emergency [6]. All this requires considerable intellectual effort and emotional stability.

Many professions work under extreme conditions: pilots, astronauts, miners, sailors, firefighters, military personnel, police officers, etc. These professions are definitely extreme. Moreover, the number of such professions and people engaged in them is constantly increasing.

Under extreme conditions, a person's usual work and rest schedule is often disrupted. In severe extreme situations, mental and other overloads reach the limits beyond which fatigue, nervous exhaustion, impaired performance, affective reactions and psychogenics (pathological states) occur. Extreme situations are dangerous for people's life, health and well-being. They sometimes occur in the course of normal production activities and lead to so-called occupational stress [1, 7].

Extreme situations can be regulated and unregulated, planned and situational, “regular” and “emergency”. In their most general form, they are divided into four groups [7, 8]:

1) caused by extraordinary conditions (natural disaster, natural or man-made catastrophe, war, mass terrorist attacks, etc.);

2) of daily life (fire, criminal attack, acute lack of time, the need to solve several equally important tasks at the same time), i.e. those that occur in everyone’s life;

3) related to potentially dangerous hobbies (mountaineering, scuba diving, high-speed driving, etc.);

4) work-related, professional – caused by the performance of professional duties. Many types of work that contain elements of industrial and occupational risk (pilots, astronauts, miners, sailors, etc.), as well as the official activities of the military, policemen, firefighters and rescuers, are associated with risks to life and health.

The following types of extreme situations can be distinguished in people's professional activities [8, 9]:

1) short-term – associated with the need to act under severe time pressure, at the fastest possible pace, with a high level of organization, and with a great psychological burden (participation in a disaster relief, rescue operations, detention of a criminal or a military operation);

2) long-term – psychologically stressful activities for a long time (tension in the work of operators of chemical production facilities, nuclear power plants, the process of detecting and investigating a crime);

3) caused by “uncertainty” – requires a decision in the presence of alternative, subjectively equally significant options for behavior (performance or non-performance of official duties under difficult conditions, reporting official negligence or illegal behavior of a person or maintaining on good terms with him/her, family conflict, etc.);

4) a situation that requires constant readiness for action – staying in monotonous, little-changing conditions in anticipation of extreme changes (duty, staying at a military checkpoint);

5) due to the receipt of probably unreliable information – requires emergency action if there is no confidence in the reliability of the information received (reports of a possible accident, disappearance of a person, taking precautionary measures, etc.);

6) caused by subjective circumstances, i.e. by the employee himself or herself (distraction or inattention, unprofessional behavior, etc.).

The analysis of workplace situations with tragic consequences shows that numbness (stupor) in the face of a real danger to life usually leads to the death of a person. But its occurrence is not accidental, it is caused by a lack of readiness to act appropriately, fear of danger due to the lack of experience (“inexperience”), cowardice and cowardice as stable character traits, and generally by, a low level of professional and psychological training or professional unsuitability.

In case of insufficient level of volitional regulation of behavior when performing professional actions with a high degree of responsibility, which require the search for unusual ways out of a tense situation, the following phenomena can be observed: reduced coordination and accuracy of movements, slowed reaction, confusion, violation of the logic of thinking, reduced critical thinking, perceptual and attentional disorders up to the loss of orientation in time and space (“tunnel vision”). In particular, approximate 40% of law enforcement officers in extreme situations were guided by their moral principles, 32% were guided by the requirements of the law, and 8% defined their behavior as determined by self-preservation. Insufficient psychological preparedness to act in difficult conditions was reported by 20% of respondents whose behavior seemed to be orderly [8]. According to the surveys, only 10-25% of people in an extreme situation can take quick and effective action. About 65-80% of people hesitate and act in a shocked and confused manner. The remaining 10-15% exhibit severe, distressing behaviors, including distraction, crying, paralyzing fear and tantrums [10].

Special working conditions place increased demands on a working person, lead to errors and interruptions at work due to emotional distress, and adversely affect a person's performance and health.

Unfortunately, disorders of emotional state are not easy to be recognized by visible symptoms [6, 9], so prompt remote diagnosis and monitoring of a person's emotional state is important, especially in difficult geographical conditions, lack of transport and mobility for patients, reduced financial resources or lack of medical staff.

In many cases, to make an operational decision, it is necessary to have an effective support from various participants in a complex situation that may develop into a dangerous one. The global concept of Air Traffic Management [11] provides for collaborative decision-making (CDM) amongst all participants involved in aviation operation based on the exchange of information about the aircraft flight and its handling at the airport [12]. The implementation of CDM requires the use of an up-to-date informational environment based on the concepts of System Wide Information Management (SWIM) and Flight and Flow Information for a Collaborative Environment (FF-ICE) [12, 13].

CDM models were first considered by the authors in aviation systems to find an optimal solution in emergencies involving many different aviation actors (pilots, drone operators, flight dispatchers, air traffic controllers, etc.) on whom the overall outcome of the decision depends. However, specialists from other areas, such as engineers, emergency and rescue personnel as well as medical staff can also be involved in the CDM. For example, in an emergency that a pilot or passenger becomes incapacitated during the flight, digital medicine and telemedicine are used to seek qualified medical advice (Figure 1) [14, 15].

Figure 1. СDМ between aviation specialists in the extreme situation

Human failure as a medical failure is compared to the acceptable failure rate of other systems critical to flight safety, such as aircraft engines. In the process of modeling the “pilot failure” emergency, the recommendations of the “Two-Link Rule” Flight Crew Training Manual (FCTM) and the Quick Reference Handbooks (QRH) were used [15-17]. Thus, most aircraft are multi-crewed ones, with two pilots participating in the flight. If the risk of an unsafe flight ending increases (“pilot incapacitation”), the second pilot receives support from autopilot/auto assistance systems and may also receive some support from other flight participants. When modeling CDM in an emergency “pilot incapacitation”, the main participants are pilots, controllers, and telemedics/doctors [18].

The problem of effective real-time monitoring of a person's emotional state can be solved with the help of a modern Intelligent Remote Monitoring System (IRMS), which enables the monitoring and diagnosis of the emotional state based on the analysis of the person’s phase portrait.

The objectives of this work are:

- to analyze the methods for measuring a person’s emotional state;

- to design a medical IRMS for monitoring and diagnosing a person’s emotional state;

- to work out the non-stochastic CDM models in the delivery of urgent medical cargo using UAV;

- to find a route with minimum cost for the transportation of urgent medical cargo using UAV.

Today, there are quite a few diagnostic tools for examining the emotional sphere of a person. This is because emotion itself does not have its product, and can therefore only be studied indirectly. It can be said that each specific method for diagnosing the emotional sphere of a personality has one main component at its core, through the prism of which the emotional state is assessed. That is, each specific technique registers a particular emotion or the general emotional state of a person based on a particular criterion (change in behavior, facial expressions, choice of color, drawing details, choice of a specific picture, etc.) In general, therefore, according to the criterion of the parameter based on the emotion registered, all diagnostic methods can be divided into six main types:

- diagnostics based on the answers to questions (test methods);

- diagnostics based on the color selection;

- diagnostics based on the auditory criteria (speech rate, spectral and intonation indicators);

- diagnostics based on the behavioral changes (movements, facial expressions, etc.);

- diagnostics based on a picture, etc.

The most common methods of diagnosing the emotional state of a person are based on the answers to questions and color selection.

The most well-known tests for diagnosing emotions are the Differential Emotions Scale by C.E. Izard [19, 20] and the Self-Esteem Scale by A. Wessman and D. Ricks [21]. Both tests are based on the same principle. The methodology consists of a list of known emotional states and statements about them, which the test subject must evaluate. As a result, the sum of points is calculated according to the corresponding scheme and the dominant emotion or emotional state is determined.

The most famous method for determining a person’s emotional state through the prism of color is the M. Luscher test [22]. In this method, the test person arranges 8 colored cards in a sequential row. After that, the current emotional state is determined according to the author's interpretation of the particular position of each color and the combination of colors in the entire row.

Remote monitoring and diagnosis of a person’s emotional state is part of remote eHealth [23-25]. This has become possible thanks to the development of sensors, Wireless Sensor Networks (WSN), and other emerging technologies such as Wireless Body Area Network (WBAN) and the Internet of Things (IoT) [26-31]. For remote monitoring and diagnosis of emotional state, the most acceptable indicators are tremor, kinematics (reproduction of a specific range of motion), reflexometry (measurement of sensorimotor reaction times), voice, facial expressions, iris changes, perspiration, finger skin temperature, blood pressure, heart rate and skin conductance.

The assessment of the emotional and functional state based on the reviewed methods allowed the design of several diagnostic instruments that are recommended for use in professional, personal and group examinations. The most well-known among them are Kirlian bioelectrography, ROFES functional and emotional state assessment recorders, fitness trackers and smartwatches.

The Kirlian bioelectrography device [32] works on the principle of visualizing discharges. The nature of the radiation from fingerprints make it possible to determine the state of a person and draw a preliminary conclusion. The ROFES registrar [33] uses the MS7 biologically active point, which is stimulated by a microcurrent and analyzes the reactions to the stimulation. In addition to neuroses, stress levels, irritability and overstrain, the device's software evaluates 17 major systems and organs so that it can be used for regular monitoring of physical status. Fitness trackers [34] and smartwatches [35] can monitor physical activity on a daily basis with a pedometer and heart rate monitor. It is currently not possible for them to fully monitor the emotional state.

API/SDK uses AI algorithms to obtain information about the emotional state from the physiological sensors [36]. It uses common parameters such as heart rate and skin conductance to measure emotions. The technology can detect extreme triggers and levels of excitement in real time and offline. It can also timestamp the start and end of an emotional event for preliminary investigation. Long-term analysis of typical emotional responses throughout the day is also possible to note when they occur most frequently.

A system was developed for real-time monitoring of the emotional state, for diagnosing the intensity of emotional experiences in extreme situations and for determining the functional stability of the pilot to predict the development of the flight situation [37].

Thus, a recorder of a person's emotional state is a device that compares the body's reactions to standard actions with benchmark settings. Benchmark settings are determined through long-term studies of specific categories of people with a known emotional state. The device has a display that shows the measured values, which can be compared with typical settings to indicate the state or degree of abnormality. By targeting the software to a specific operating platform, its capabilities can be enhanced with comments and advice. The USE-CASE diagram (Figure 2) can represent the basic script of interaction between the device and the user's computer. The “Interrupt” operation is necessary to restore or change the state of a person within a certain time.

Figure 2. The main scenario for processing measurement results

IRMS is proposed for monitoring the emotional state of people in medicine, sports, treatment and automated monitoring of persons in hazardous environments, for example, in an aeroplane (passengers), in a smart home (people), in medicine (patients), etc. The core of the control system is to define and describe the relationships and dependencies between the key factors, options and features of the control device and the control object (person).

The monitoring and diagnosis of the person’s emotional state in real time is proposed to apply the concept of psychic activity, which is based on the property of the mind to slow down or speed up the flow of subjective time in relation to the real one. This is reflected in the deformity of emotional experience in the form of a transition from optimal (spontaneous) to hazardous (rational or emotional) types of human activity in extreme situations and a violation of a person's functional stability.

The phase plane method is used to timely detect a hazardous emotional state of a person in an extreme situation, the essence of which is to construct phase trajectories for differential equations in the coordinate system. Real-time identification of a person's emotional state is based on the variance analysis of the models of spontaneous (optimal), emotional and reasonable types of activity. The deformity of the emotional state is determined using a priori person’s models based on the actual material of a posteriori research on the accident investigations. Nyquist hodograph for the spontaneous (optimal) type of activity is built and it does not contain the critical point (-1; j0) that indicates the stability of the human-machine system.

For effective monitoring and diagnosis of the person's emotional state, IRMS is built based on the dynamic modeling principles. The subsystems of IRMS are formalized in the form of transmission functions, a person is considered as a control object, and the monitoring and diagnosis of the emotional state based on the analysis of the phase portrait of control device are obtained. An example of IRMS modeling by analyzing the influence of time constants and coefficients on the stability and reliability of system using Mikhailov and Nyquist criteria is presented. If the Mikhailov hodograph covers two quadrants in the positive direction (counterclockwise), the system is stable. As the control coefficients increase, the stability areas increase.

Based on the objective-subjective CDM method in the uncertainty, the problem of an urgent delivery of medical cargo using UAV from the departure points Mukachevo, Mizhhir’ya, Rakhiv to the destination point Khust is solved. The optimal decisions by the Wald, Laplace and Hurwitz criteria according to each participant are:

- for the remote pilot: by the Wald, Laplace and Hurwitz criteria – Mizhhir’ya; by the Laplace criterion – Mukachevo;

- for the air traffic controller: by the Wald and Hurwitz criteria – Rakhiv; by the Laplace criterion – Mukachevo;

- for medical personnel: by the Wald, Laplace and Hurwitz criteria – Mizhhir’ya;

- for logistics/transportation company: by the Wald criterion – Rakhiv; by the Laplace criterion – Mukachevo, Mizhhir’ya, and Rakhiv; by the Hurwitz criterion – Mukachevo and Mizhhir’ya.

The optimal decision with minimum risk and maximum safety by the Wald-Wald, Wald-Laplace and Wald-Hurwitz criteria according to all participants’ opinions on UAV transportation is found.

Based on the dynamic programming method, if it is necessary to urgently deliver medicines to a seriously ill patient, the task of finding a route of minimum cost from the starting point (Uzhhorod) to the destination point (Khust) using UAV is decided. The minimum cost of UAV route is 24 conventional units. In the case of big and complex data, the method can be implemented in traditional and hybrid systems of the next generation to make decisions by handling unsupervised situation data in deep landscape models.

Monitoring and diagnosis of emotional state is important for varied professional groups of persons, especially those involve in hazardous work, risks and high responsibility (pilots, astronauts, miners, sailors, firefighters, military personnel, law enforcement officers, etc.). These professions are definitely extreme. Moreover, the number of such professions and people engaged in them is constantly increasing. Unfortunately, disorders of the emotional state is not easily recognized by visible symptoms, so prompt remote diagnosis and monitoring of a person's emotional state is important, especially in conditions of complex geography, lack of transportation and mobility of patients, reduced financial resources, or lack of medical staff. In many cases, effective supports from various participants involved in a difficult situation that could become hazardous is required to make a timely decision.

For remote monitoring and diagnosis of the emotional state, the most acceptable indicators are tremor, kinematics (reproduction of a specific range of motion), reflexometry (measurement of sensorimotor reaction times), voice, facial expressions, iris changes, perspiration, finger skin temperature, blood pressure, heart rate and skin conductance. The most well-known diagnostic tools for the assessment of emotional state are Kirlian bioelectrography, ROFES functional and emotional state assessment recorder, fitness trackers and smartwatches.

The authors, who have aviation experience in operational detection of deviations in the pilot's emotional state and decision making under risk, propose to apply for the concept of psychic activity, which is based on the property of the mind to slow down or speed up the flow of subjective time in relation to the real one for monitoring and diagnosis of the person’s emotional state. The phase plane method is used for operational detection of a hazardous emotional state of a person in extreme situations. The real-time identification of a person's emotional state is based on the variance analysis of the models of spontaneous (optimal), emotional, and reasonable types of activity. The deformity of the emotional state is determined using a priori person’s models based on the actual material of a posteriori research on the accident investigations. For measuring the person’s functional stability, the Nyquist criterion is used. The method of real-time diagnosis of the person’s emotional state is presented. A software “Diagnostics of the emotional state of a human-operator” is developed.

The problem of effective monitoring and diagnosis of the person’s emotional state can be solved with the help of IRMS, which is built based on dynamic modeling principles. The conceptual model and the functional diagram of medical IRMS are worked out. The algorithm of the person’s emotional state monitoring and diagnosis is presented. Using Mikhailov and Nyquist criteria, the stability of IRMS is obtained and Mikhailov and Nyquist hodographs are built.

IRMS is proposed for monitoring the emotional state of the person in medicine, sports, treatment and automated monitoring of persons in hazardous environments, for example, in an aeroplane (passengers), in a smart home (people), in medicine (clients), etc. Prompt monitoring and diagnosis will allow timely adjustment and improvement of the person's emotional state and prevent the extreme situation developing towards worsening.

Based on the objective-subjective CDM method in the uncertainty, the problem of an urgent delivery of medical cargo using UAV from the departure points to the destination point is solved. The optimal decision with minimum risk and maximum safety by the Wald-Wald, Wald-Laplace and Wald-Hurwitz criteria according to all participants’ opinions in UAV transportation is found.

Based on the dynamic programming method, if it is necessary to urgently deliver medicines to a seriously ill patient, the task of finding a route of minimum cost using UAV is decided. In the case of large and complex data, the method can be implemented in traditional and hybrid next-generation decision-making systems by processing uncontrolled situation data in deep landscape models.

Further research should be aimed at determining the preconditions for the occurrence of extreme situations and preventing catastrophes. It is necessary to research the applied tasks of CDM in socio-technical systems (aviation, chemical production, nuclear energy, military industry, etc.) and to develop Intelligent Decision Support Systems for operating the highly complex control systems in emergencies based on detecting changes in the phase portraits and diagnosing the deformity of the emotional state. In particular, it will be able to timely identify the emotional exhaustion (or emotional burnout syndrome) that is characterized by constant physical, psychic and moral fatigue, insomnia, headaches, eating disorders, loss of interest in favorite activities, irritability and stress. When there is a data accumulation, it is planned to create the Intellectual Decision Support System modules with the Artificial Intelligence (AI) participation. AI participant will be a member of the CDM Participants Group.

A model for synchronizing the actions of all delivery participants – the sender and the recipient (medical personnel), and the delivery specialists (logistics/transportation company) in extreme situations can be developed using AI methods. Formalizing the actions of all CDM participants using AI will enable them to determine the optimal sequence and time of the procedure to resolve the non-standard situations. To prepare the participants for proper and efficient actions in extreme conditions, the educational procedures should simulate situations as close as possible to actual incidents.

List of abbreviations and symbols

AI – Artificial Intelligence

CDM – collaborative decision-making

CD – control device

CO – control object

DA – Dangerous Area

IRMS – Intelligent Remote Monitoring System

P – person

RA – Restricted Area

TA –Transit Area

UAV – Unmanned Aerial Vehicle

Authors' contributions

Each author participated and contributed sufficiently to take public ownership for the relevant parts of the content.

Funding

No outside financing was received for this research.

Competing interests

The authors claim no conflict of interest.

Ethical Statement and Data Provenance

The data utilized in this manuscript are strictly secondary, deriving from a posteriori study of aviation incident materials received by the Interstate Aviation Committee between 2004 and 2006, which were previously published in 2006 monographs by Professors S.D. Leichenko, A.V. Malyshevsky, and N.F. Mykhaylik. Consequently, the current study involved no direct human interaction, primary data collection, or handling of personal identifiers; instead, the analysis was conducted solely on aggregated, formalized theoretical models used to predict emergencies. Because no individual-level information regarding specific pilots was retained or accessed, and the foundational data and models have been publicly available since their initial publication (including subsequent works like Kharchenko et al., 2012), this research fully complies with Ukrainian data protection regulations and standard ethical requirements for secondary data analysis, with all sources appropriately referenced throughout the text.

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