PT117127B - DEVICE FOR DETECTING AND PREDICTING EXHAUSTION SYMPTOMS - Google Patents

Abstract

THE PRESENT INVENTION REFERS TO A DEVICE WITH THE PURPOSE OF DETECTING AND PREDICTING SYMPTOMS OF EXHAUST. MORE CONCRETELY, THE PRESENT INVENTION IS RELATED TO THE FIELD OF SIGNAL MEASUREMENT FOR LABOR AND PATHOLOGICAL MONITORING PURPOSES AND REFERS TO A COMPUTATIONAL UNIT AND A SENSORY UNIT INTENDED FOR THE MEASUREMENT AND RECORDING OF ELECTROCARDIOGRAPHIC SIGNALS (ECG), OF ELECTRODERMAL ACTIVITY (EDA) AND POSTURAL CONTROL OF A USER OVER TIME, MORE SPECIFICALLY TO A DEVICE THAT IS INCORPORATED INTO A SEAT, NAMELY AN OFFICE CHAIR. THE SENSOR UNIT INTEGRATES MEASUREMENT TERMINALS FOR USER INTERFACE, SIGNAL TRANSDUCTION AND CONDITIONING, ANALOGUE-DIGITAL CONVERSION AND SIGNAL TRANSMISSION. THE MEASUREMENT TERMINALS ARE CONSISTED OF PRESSURE SENSORS (104), AN ECG SENSOR (102) AND AN EDA SENSOR (103) WHICH ARE COVERED BY AN ELECTRICALLY CONDUCTIVE MEDIUM.

Description

DESCRIPTION

DEVICE FOR DETECTING AND PREDICTING SYMPTOMS OF

EXHAUST

Field of invention

The present invention is related to the field of signal measurement for labor and pathological monitoring purposes and refers to a computational unit and a sensory unit that integrates a set of sensors intended for measuring and recording electrocardiographic signals (ECG). ), electrodermal activity (EDA) and postural control of a user over time, more specifically to a device that is incorporated into a seat.

This allows the signaling of occurrences during the development of work activity, such as stress, fatigue, indicators for musculoskeletal injuries and/or discomfort related to the cervical spine, among other conditions that influence the worker's well-being.

Background of the invention

With the increasing pace and work demands of modern professions (also known as white collar), there is growing concern about the well-being and mental health of employees. Professional burnout in an occupational context was recently included by the World Health Organization (WHO) in the 11th ^Revision of the International Classification of Diseases [1].

The WHO further estimates that work-related health problems result in an economic loss of between 4 and 6% of Gross Domestic Product (GDP) for most countries and, good working conditions can provide social protection, opportunities for personal development and protection against physical and psychosocial risks, improving social relationships and workers' self-esteem, leading to positive health effects [2] .

For the reasons previously mentioned, specialized organizations and regulatory entities, such as the WHO and the Centers for Disease Control and Prevention (CDC), in published articles [3], encourage the development of new engineering and technological projects, which allow early detection and awareness among employees of indicators such as stress, exhaustion, fatigue and posture in the workplace. These aim to promote the active monitoring of workers, helping to prevent the aforementioned indicators and improve their well-being.

The ways of acquiring physiological signals have evolved from paradigms based on devices for clinical use and associated with the hospital environment (e.g. holter, oximeter, among others), to paradigms for daily use, in which the user maintains frequent contact with a monitoring device. monitoring physiological signals (e.g. watch, bracelet, car steering wheel, etc.).

The latter normally establish the acquisition of data periodically or in real time, which in the current state of the art includes different types of devices, commonly known as wearables and invisibles, distinguished by the way of use and characteristics of the device. Wearable devices presuppose that the device is placed on the user, generally in the form of an accessory (e.g. watch, t-shirt, etc.). Invisible devices allow active monitoring of the user's activity through objects present in their daily lives (e.g. car steering wheel, chair, etc.).

The signals collected by the aforementioned devices are subsequently processed using computer algorithms. Through this last process, it is possible for the user to obtain information, such as their average heart rate, consumption of energy levels, spinal inclination, sleep assessment, among others. This information is delivered to the user through notifications and/or means that can be considered as graphical interfaces (e.g. mobile applications, internet pages) present on the device, or on an accessory to which it is connected.

ECG is one of the oldest and simplest tests, used to analyze an individual's cardiovascular system. An ECG shows the evolution, over time, of the electrical activity of the heart muscles in response to the electrical depolarization triggered periodically by the sinusoidal node. For the heart to function properly, the atria and ventricles are activated sequentially and quickly. This activation causes the atrium to fill the ventricle with adequate volumes of blood before ventricular contraction. The system responsible for coordinating this function is the electrical conduction system composed of myocardial cells, which propagate the activation impulse through the atria and ventricles. A typical ECG signal consists of three main waves: a P wave, a QRS complex, and a T wave. The P wave illustrates depolarization, which refers to the electrical signature that causes atrial contraction. The QRS complex is associated with ventricular depolarization, that is, it is responsible for the contractions of the left and right ventricles. Finally, ventricular repolarization is represented by the T wave.

ECG sensor makes it possible to measure the electrical activity of the heart through electronic systems, from which it can be processed and analyzed according to the specificities of the application. In the context of use, the negative terminal, the reference and the positive terminal are applied to the body, with electrical changes detected through potential differences over time. These electrical changes are detected using different physical principles, the most common being based on the difference in electrical potential between several leads, using several metal-based electrical terminals placed in different parts of the body. Other measurement principles include capacitive and mechanical methods that may not require direct contact with the body.

In a typical ECG recording in a clinical setting, differences in electrical potential are measured in twelve different leads, placed in different parts of the body. Recent work has demonstrated that for biomedical applications a single derivation is sufficient [4]. However, conventional collection methods rely on chest-mounted terminals, gel-based metal electrodes, and bulky measuring devices. The acceptance of the ECG as a biometric measurement [5] therefore led to research into obtaining less intrusive montages, using the hands/wrists as signal acquisition points.

EDA sensor measures changes in skin conductance resulting from sympathetic nervous system activity.

One of the most sensitive and extremely important measures for evaluating arousal is the EDA. The areas where it can be applied are well documented, with research into epilepsy, autism, stress and anxiety being some of the most important examples. This measures the activity of sweat glands. In general, the existence of physical components in this activity suggests the existence of emotional stimulation.

Electrodermal activity makes it possible to measure the non-cognitive response, that is, it measures the organism's response mediated by sympathetic activity in subconscious processes. This is a difficult measure to control voluntarily and, therefore, is a very important marker to evaluate the variation in emotional arousal, as it allows inferring information about psychological and physiological processes. In response to emotional stimuli, the heart beats faster, the pulse increases and the hands sweat. To measure electrodermal activity it is necessary to monitor skin conductance. As such, one of the measurement methods consists of applying a small voltage to the surface of the skin through electrodes that can be positioned on either the palms of the hands or the soles of the feet, due to the greater amount of sweat that is released in these locations.

Postural control is a fundamental function, of great complexity, involved in almost all motor tasks. Several theories have been developed with the aim of explaining the process at the neural level for sitting, standing, breathing and movement [6,7]. Posture is defined by the state of balance between muscles and bones capable of protecting other body structures from injuries, whether standing, sitting or lying down [8]. The sitting position is, in turn, defined as the situation in which body weight is transferred to the seat through the ischial tuberosity, the soft tissues of the gluteal region and thigh;

part of the weight is also transferred to the floor through the feet. However, sitting is a dynamic action and should therefore not be analyzed as a static condition [8], observed only occasionally.

burnout is a concept that still does not gather consensus within the scientific community, which has promoted research by experts from various fields such as cognitive psychology, human factors, engineering and medical practice [9].

There is no consensus, as burnout is an experimental concept, a symptom, a risk, a cause (e.g. performance) and a consequence (e.g. sleep deprivation), however, one of the consequences is fatigue. According to Mosso's classic concept, fatigue is defined as a disabling symptom, in which physical and cognitive function is limited by interactions between performance fatigability and perceived fatigability. As a symptom, fatigue can only be measured by self-report, quantified as a trait characteristic or a state variable [10].

The fatigability attribute of performance depends on the contractile functions of muscles and the capacity for muscle activation. On the other hand, the attribute of perceived fatigability depends on the individual's homeostasis and psychological state, which may also include phases of excitement (also called arousal), highlighting the importance of using the electrodermal activity (EDA) sensor [10].

All individuals are susceptible to stress, which can alter both the physical and psychological health of each person. Stress can be defined as the condition that results when person/environment exchanges lead the individual to perceive or feel a discrepancy, which may or may not be real, between the demands of a given situation and the individual's resources, at the level biological, psychological or social systems [11].

Associated with stress, human beings have several types of response. The cognitive response is considered a subjective response, as it depends on the individual's perception, the way they filter and process information, and the meaning they attribute to situations or stimuli.

The behavioral response is defined as the organism's ability to give adequate responses to each stimulus. This depends on prior learning, based on each individual’s personal experience [12].

Finally, the physiological response associated with stress is due to the mind's perception of the environment and which then communicates with the rest of the body through the hypothalamopituitary-adrenal axis (HPA), with the subsequent activation of the Sympathetic Nervous System (SNS). ). SNS activity can be observed through EDA signals. The hypothalamus interprets the perception and sends a signal through the release of corticotropin-releasing factor and vasopressin which, in turn, activates the secretion of adrenocorticotropic hormone by the pituitary [13]. If interpreted as a threat, the pituitary stimulates the production of noradrenaline and adrenaline and activates the secretion of glucocorticoids, the main one being cortisol, in the adrenal glands in which the common understanding of these is a fight or flight response [14].

Due to the secretion of glucocorticoids, several bodily reactions are triggered, namely, the movement of blood to the arms and legs that was, a priori, in the viscera.

The entire cascade of reactions between the detection of the stimulus, its recording in memory, the attribution of the meaning given to it (e.g. neutral, pleasant or threatening), takes place in milliseconds. This translates into an increase in heart and respiratory rate, in which the heart beats faster (tachycardia) and more vigorously (increased contractility), increased blood pressure, muscle tension, dryness of the mouth and mucous membranes, changes in clotting factors, slowing of digestion due to the displacement of blood to the peripheries, dilation of the bronchi and increased activation of sweat glands [15] .

Among these indicators, measurements of cardiovascular activity are the simplest to obtain using non-intrusive methods, such as electrocardiography (ECG), but the sweating dynamics evidenced by EDA signals also plays a relevant role.

There are many studies that characterize the relationship between stress and performance in the workplace. Stress is important as it substantially influences an individual's ability to carry out their tasks effectively.

It is thought that stress impairs attention, affects memory and decision-making, which in turn influences action, and that extreme forms of stress, such as burnout, clinical anxiety and depression, are often harmful performance [16].

Three of the determining factors for workplace performance center on willingness to perform, ability to perform, and opportunity to perform. Burnout, in particular, can affect the aspect of willingness and ability to perform at work, promoting resentment, loss of motivation and absenteeism, the influence it has on so-called professional performance being clear [16].

Burnout and related problems, such as fatigue, irritability and anxiety, are classified as health problems and are quite common in the workplace. The costs to the industry are considerable due to reduced productivity, working days lost due to illness, absenteeism and workers' compensation [16].

Several studies show that there is a negative relationship between burnout and productivity. A study published by the International Journal of Stress Management [17] shows that well-being is the strongest predictor of productivity and, as is known, the influence between burnout (which is recognized as an extreme form of stress and which their experience suggests an extreme decrease in energy) and well-being, it was possible to predict a potentially similar relationship with productivity.

study further suggests that as negative well-being is accepted as an antecedent to so-called burnout and that as this well-being detrimentally affects performance, then decrements in performance are likely to be evident earlier in the experience of burnout [ 17].

Postural control is a fundamental function, of great complexity, involved in almost all motor tasks.

Several theories have been developed with the aim of explaining the process at the neural level of sitting, standing, breathing and movement [18].

The sitting position can be classified based on several reference points. Harrison used the positioning of the center of mass and identified three different postures, called anterior, posterior and middle [18]. Pynt et al. [20] classified the sitting position according to the curvatures of the spine into flexed sitting posture and lordotic posture.

In the literature there are several studies carried out on the subject of postural monitoring, from the study of support materials for the monitoring process, to data analysis. A work carried out by Fu et al. sought to monitor the different types of posture adopted by individuals in a sitting position, in a non-intrusive way [21]. Regarding the hardware, 8 pressure sensors were used that reduce resistance when the pressure on its surface increases.

Regarding data analysis, the program was developed with the aim of analyzing posture ergonomics and, to this end, the main features are the recognition of a static posture through sensors applied to a rigid surface (which is not a representative scenario). of an office chair), the recognition of an activity based on postural inputs and, finally, the recognition of a postural pattern [21].

In order to monitor static postures, in an article published by Huang et al., a piezoresistive sensor was used that tested 8 different positions adopted by several study subjects, concluding that, both the tested hardware and the data analysis methods, allow the monitoring of static postures, although this type of sensors have a low load limit, and the application was in a chair with a rigid base and back [22].

A study carried out by Wong and Wong et al., with the aim of detecting postural changes while individuals are sitting, used three sensors with triaxial accelerometers. The use of these sensors made it possible, through accelerometers, to eliminate the effect that the sensor orientation has on the calculation of the inclination angle, concluding that the precision and reliability of this type of sensors proved to be adequate for the purpose. The sensors were positioned to enable the observation of changes in posture by detecting different inclinations between the sensors [23].

Background of the invention

Several prior art documents were found that present devices and techniques for detecting and predicting burnout symptoms.

Refer in particular to document US201715647321A which presents a method for detecting and predicting symptoms of exhaustion.

Or even document EP2685885 which refers to a method and equipment for analyzing stress and professional burnout.

Or document EP3076868 which presents a Processor for processing skin conductance data and device for detecting at least one phase of professional burnout and/or chronic fatigue syndrome in a living being.

Also refer to document EP3716151 which presents a stress monitor and stress monitoring method.

However, no document was found that refers to an invention as described in this document, or that encourages it in this sense.

Advantages of the invention

The present invention has several advantages over other equipment, namely:

- the fact that it is an invisible device that allows data acquisition through a non-invasive and non-intrusive device, as it is only in contact with the user;

- unlike a wearable, an invisible device does not interfere with what is the definition of comfort for the user (e.g. physical discomfort, not liking to wear the device, etc.);

- the device does not depend on a power source with limited usage time (batteries);

- all functionalities contribute to a specific objective;

- the fact that the measurement terminals are covered with an electrically conductive layer has the advantage of enabling signal acquisition without the need for intermediate elements such as conductive gels, local electrodes, etc.;

- the fact that the collected signal is transmitted in real time to a computing unit, allows the extraction of value from these same signals so that they can be made available to the user in the form of useful indicators, graphs, notifications, etc.;

- the fact that it is applied to a seat allows it to be used in contexts where people spend a large part of their time sitting. In this way, the objective is to improve productivity and efficiency in labor development, improve focus and motivation and reduce the number of sick leave by giving an alert when something is out of line with the parameters identified as normal;

- contributes to health awareness.

Brief description of the figures

These and other characteristics can be easily understood through the attached drawings, which should be considered as mere examples and in no way restrictive of the scope of the invention. In the drawings, and for illustrative purposes, the measurements of some of the elements may be exaggerated and not drawn to scale. The absolute dimensions and relative dimensions do not correspond to the real relationships for carrying out the invention.

Figure 1 shows a block diagram with the device modules for measuring signals for labor and pathological monitoring purposes.

Figure 2 shows a schematic view of an embodiment of the invention, in which the device is integrated into an office chair, with the armrests of the chair covered by an electrically conductive leather covering (101) being visible.

Figure 3 shows a schematic view of an embodiment of the invention, in which the device is integrated into an office chair, with the positive terminal (102.1), the negative terminal and the ground terminal (102.1) of the ECG sensor being visible ( 102), the positive terminal (103.1) and the negative terminal (103.1) of the EDA sensor (103) placed on the arms of the chair.

Figure 4 shows a schematic view of the electronic components that make up the measurement terminals. More specifically, the ECG sensor (102) and the EDA sensor (103) are placed on the armrests of the chair and the pressure sensors (104) are located below the base of the seat.

Figure 5 shows an exploded view of the application of pressure sensors (104) placed below the seat base.

The figures indicate the elements and components of the equipment of the present invention, as well as elements necessary for the operation of the invention:

101 - nappa coating

102 - ECG sensor

102.1 - positive terminal

102.2 - negative terminal and ground terminal

103 - EDA sensor

103.1 - positive terminal

103.2 - negative terminal

104 - pressure sensors

200 - sensory unit

201 - measuring terminals

202 - signal transduction and conditioning

203 - analog-to-digital conversion

204 - signal transmission

205 - computational unit

Detailed description of the invention

Computational unit means any type of electronic equipment suitable for the digital processing and presentation of signals, including a fixed computer, portable electronic devices such as portable computers, mobile phones, or similar devices, more specifically, equipment that implements a method, enabling the extraction and processing of representative information from signals coming from the ECG sensor, the EDA sensor and the pressure sensors, in real time.

A seat means a piece of furniture on which a user can sit.

By nappa we mean also called artificial leather, which is a material used to replace leather in upholstery, clothing, footwear and other uses in which a leather-like finish is desired, but the true price of the material is cost prohibitive. or not indicated.

The seat base means the part of the seat where the buttocks are placed.

The present invention is related to the field of measuring cardiovascular signals, electrodermal activity and charge distribution and refers to equipment composed of a computational unit (205) and a sensory unit (200) which are intended:

- the measurement of electrocardiographic signals (ECG) and the measurement of electrodermal activity (EDA) using, respectively, an ECG sensor (102) and a sensor

EDA (103) which are coated with an electrically conductive medium without the need for a means of adhesion to the body,

- recording the distribution of the user's load over time through the positioning of pressure sensors (104), carried out through the seat base plate, through the support's contact with the seat base, or similar means.

In a preferred embodiment, the electrically conductive means is an electrically conductive leatherette coating (101).

In one embodiment, the device was developed with the aim of carrying out two types of monitoring, continuous (through pressure sensors (104)) and punctual (through the ECG sensor (102) and the EDA sensor (103) ). This real-time monitoring comes from the analysis of signals collected by the ECG sensor (102), the EDA sensor (103) and the pressure sensors (104) adapted to an office chair with armrests.

Sensory Unit (200)

The sensory unit (200) is based on different operating principles, namely, on the difference in electrical potential, measured through potential differences between terminals, through the contact of the user's skin with the device, and on mechanical action through direct contact between the user and the device. Measurement through mechanical action is made by pressure sensors, namely load cells, and sensors functionalized in a similar way can be used.

The sensory unit (200) comprises the following electronic components: measurement terminals (201) for user interface, signal transduction and conditioning (202), analog-to-digital conversion (203) and signal transmission (204).

The user interface is made through one or more measuring terminal electronic components (201), through which the ECG and EDA signals are acquired. In the present embodiment there are eight measuring terminals. Of the eight, five measuring terminals (201) are covered by the electrically conductive medium, which in turn is in direct contact with the user, namely with the wrists, wrists, fingers or, preferably, with the palms of the hands, in particular with the thenar eminence.

More specifically, of the measuring terminals (201) covered by the nappa coating (101), three terminals are for the ECG sensor (102) and two terminals are for the EDA sensor (103). The remaining three terminals are for the pressure sensors (104).

The electronic signal transduction and conditioning component (202) performs the conversion of physical signals detected through the measurement terminals (201), filtering the acquired signal through an electromagnetic noise filter compatible with data transmission via wireless connection. wires and amplification of the signal for subsequent processing as an electrical signal, producing a more adequate representation of the captured quantity. The filtering is of the band-pass type, with the invention being particularly advantageous in using a pass band between 0.5 and 40 Hz, which eliminates the use of the traditional notch filter, thus allowing the isolation of the ECG from parasitic signals, caused by the movement of the body, baseline fluctuation, muscle signals, electrical network noise, etc. Amplification, with a gain between 10 and 10000, allows the definition of the collected signal to be increased (in the order of pV, mV or V), making weak ECG signals more immune to external noise.

The analog-digital conversion electronic component (203) transforms the electrical signal obtained from the signal transduction and conditioning electronic component (202) into a digital signal that can be managed in the computational unit (205), integrates a quantization element and an analog-to-digital converter. The quantization element is a component that maps the voltage or electric current into a set of bits, which in the case of the present invention is between 8 and 64 bits. The analog-to-digital converter is a component that, at regular and pre-established moments of time, collects a sample that is then quantized. In the case of the present invention, the frequency with which samples from each sensor are collected (sampling frequency) is up to 1000 Hz, which in samples collected per unit of time, corresponds to 1000 samples per second.

The signal transmission electronic component (204) has the function of sending the data filtered by the signal transduction and conditioning electronic component (202) to the computational unit (205). This process can be carried out using:

- a wired connection, through connections, namely but not exclusively: COM/RS232 port, USB, printed circuit tracks, GPIO pins, direct connection to Rx/Tx pins of a microcontroller; or

- a wireless connection using protocols, namely, but not exclusively, such as Bluetooth, WiFi, ZigBee,

ANT, 3G, 4G or 5G.

Computational Unit (205)

The computing unit (205) is any type of electronic equipment suitable for digital signal processing and presentation, namely, but not exclusively, stationary computers, portable computers, tablets or mobile phones. The computational unit (205) can also be an electrocardiograph, in which case it requires any equipment to present the graphical representation of the acquired signals.

The computational unit (205) is an electronic device of any type, which changes its appearance, settings and properties, depending on the response of a method it implements for detecting and predicting exhaustion symptoms, and which uses ECG and EDA signals. , using electrodes that do not require a medium adherent to the body, such as conductive gel; and pressure sensors (104) from the sensory unit (200). These signals are processed in order to provide information related to the biological feedback obtained, such as heart rate and its variation, stress analysis, fatigue, analysis of movement in the seat, postural inertia and your position when sitting. All this information is subsequently transmitted to the user.

This computational unit (205) implements a process that makes it possible to extract characteristics relating to ECG, EDA and load distribution signals from the device, then providing them to the user through graphs, reports, animations or notifications. This process is preferably carried out continuously, that is, ensuring that the measurement of the load distribution carried out by the pressure sensors (104) occurs uninterruptedly during the time of use, while the acquisition of ECG signals and EDA signals carried out by the EGC sensor (102) and EDA sensor (103) is carried out punctually.

The computing unit (205) also integrates a database, in order to allocate the user to a registry of a known population. The database communicates with a central server that stores this information remotely and allows the user to associate with the device described in the present invention, as well as saving the collected information.

The electronic component of measuring terminals (201) of the device may be integrated into the computing unit (205), although, alternatively, they may be independent elements, connected to the remaining modules of the sensory unit (200) via wires or cables of length variable, in order to allow greater flexibility in the construction of its embodiment.

Pressure sensors (104)

The electronic signal transduction and conditioning component (202) also makes use of pressure sensors (104).

In one embodiment the pressure sensors (104) are disc-shaped load cells.

Each load cell is made of a steel alloy and has a reading capacity of up to 200 kg. Each load cell uses a four-terminal Wheatstone bridge configuration to connect to the cell amplifier component. These terminals are represented by red, black, white, green and yellow. Each color corresponds to the conventional color coding of load cells: red (VCC), black (GND), white (output), green (A+, S+, or 0+), yellow (mesh). The yellow terminal acts as an optional input that is not connected to the voltage meter, but is used to ground and protect against external EMI (electromagnetic interference).

The load cells offer an IP66 protection rating.

These load cells are somewhat easier to assemble than bar-shaped load cells, making them simpler and more advantageous to implement in the equipment of the invention.

Each load cell is connected to the sensor unit (200) via a load cell amplifier component. The cell amplifier component features a separation of analog and digital supplies, a 3.3 μΗ inductor, and a 0.1 μΕ filter capacitor for the digital supply.

The load cell amplifier component uses a two-terminal interface for communication.

Signal transmission (204)

The signal transmission electronics (204) sends the acquired ECG, EDA and charge distribution signals to the computing unit (205) using various alternatives. In this domain, the equipment of the invention allows the use of a wireless channel, using existing protocols, namely, but not exclusively, such as Bluetooth, WiFi, ZigBee or ANT.

Alternatively, transmission can also be done in a wired way, allowing more conventional cable interfaces to be used, such as connection to COM/RS232 port, USB, printed circuit tracks, GPIO pins, direct connection to Rx/Tx pins of a microcontroller, or similar methods.

The sensory unit (200) and the computational unit (205) are interconnected with each other. For example, a preferred embodiment of the invention is considered to be an office-type chair that integrates the sensory unit (200) and implements the process that transmits the analyzed parameters to the computational unit (205), thus enabling the extraction of information representative of the ECG, EDA and seat weight distribution signals.

For reasons associated with the convenience of application and use of the device, applications are also possible in which the sensory unit (200) and the computational unit (205) are separated from each other, but in which the signal transmission electronic component (204) of the sensory unit (200) guarantees communication between them. For example, a form of the present invention is considered to be the combination of an office chair that integrates the sensory unit (200) and that transmits the acquired signals of a certain format (wired or wirelessly) to the computing unit (205 ) composed of a circuit functionalized by a microcontroller. This information is subsequently stored in a database and can be analyzed locally or remotely, allowing different types of feedback to be obtained.

Preferred embodiment of the invention

The described embodiments should not limit the scope of the invention, in particular with regard to the computational unit (205), as this may take different formats, which include dedicated hardware built specifically for the implementation of the described method, but which can also take advantage of existing hardware such as portable electronic devices, cell phones, tablet computers, laptops, desktop computers, watches, or any other similar device designed for Human-Machine or Machine-Machine interaction.

Signal collection presupposes that the user is in contact with the device described in the present invention, more specifically with the electrically conductive medium. To measure ECG and EDA signals, this contact is made through a skin with electrically conductive properties, and through the base of the seat to analyze the user's position and inertia. The computational unit (205) integrates a software resource for the acquisition, analysis and processing of signals from the sensory unit (200).

The information collected by the device is based on the signals acquired by the ECG sensor (102), the EDA sensor (103) and the pressure sensors (104). The ECG shows the evolution over time of the electrical activity of the heart muscles in response to the electrical depolarization triggered periodically by the sinusoidal node. EDA makes it possible to measure the non-cognitive response, that is, it measures the organism's response mediated by sympathetic activity in subconscious processes. This is a difficult measure to control voluntarily and, therefore, is a very important marker to evaluate the variation in emotional arousal as it allows inferring information about psychological and physiological processes.

The three pressure sensors (104) are sufficient to estimate the user's position (whether they are leaning forward, backward, left, right and/or in a static position), after being placed at the bottom of the seat base. , once the specific place where the user should sit is defined. The place where the user should sit is the geometric center of the isosceles triangle, with dimensions 0.2 x 0.2 m, defined by the pressure sensors (104), arranged one at each of the vertices (one in the center front position). , one in left rear position and one in right rear position).

The information collected by the sensors is transmitted by the sensory unit (200) to the computational unit (205) through communication between the COM port of the sensory module (200) and the COM port of the computational unit (205). This transmitted information is subjected to analysis and processing by software in the computing unit (205). It is in this software that digital filtering is carried out, complementary to the filtering of the sensors, and the signals acquired by the sensors are converted into characteristics. In the signal feature extraction phase, with regard to the ECG, namely but not exclusively, heart rate, heart rate variability, wave complexes corresponding to the heart beat (PQRS-T) and R peaks are extracted. representative of the heart's activity and particularly advantageous, as it allows us to obtain indicators about cardiovascular dynamics. These may be pathological evidence, or evidence of increased stress and fatigue, contributing to the detection and prediction of burnout symptoms.

In the case of information collected by EDA, the software allows the extraction of sweating dynamics. Sweating is an indicator that allows the user to analyze stress and fatigue. Consequently, it allows a more detailed analysis of increased stress and fatigue, which is why it once again presents itself as an advantageous method, significantly increasing the effectiveness in detecting and predicting burnout symptoms.

The pressure sensors (104), through software, allow the acquisition and analysis of the user's load and load distribution throughout the use of the device described in the present invention. It is possible to analyze the user's position in relation to the location indicated as the geometric center (reference place where the user sits), through the load that affects the pressure sensors (104). Assuming that the user flexes the trunk forward, the front cell measures a greater load than the rear cells and the same for the remaining actions that the user performs. The software takes into account, notably but not exclusively, the user's front, back or side bending, subsequently timing the duration of the last action. User inertia can be identified if the load on the cells remains the same between consecutive time windows, the duration of which is an application configuration parameter.

ECG sensor (102) and EDA sensor (103) are connected directly to the electrically conductive medium through the measurement terminals (201). To acquire the respective signals, the user must maintain direct physical contact with the electrically conductive medium, located on the seat, namely, but not exclusively, on the seat arms, the back of the seat or the base of the seat. This application is also particularly advantageous and innovative, as it is possible to acquire ECG and EDA signals without the use of intermediate means (e.g., such as conductive gels), which could interfere with the process and the user's day-to-day life. and allowing the evaluation of their physiological signs, in a work context and in real time.

It should be noted that the electrically conductive medium covering the ECG sensor (102) is separate from the electrically conductive medium covering the EDA sensor (103).

The information is provided to the user in the form of notifications in the computing unit (205) and through a graphical interface, in which it is possible to observe animations and graphs, corresponding to the ECG, EDA and load distribution signals.

The software notifies the user if a set of criteria are met, namely:

- remain seated for more than 40 consecutive minutes, or 1 hour and 30 minutes accumulated without getting up;

- remain in a static position for more than 5 consecutive minutes, or 40 accumulated minutes;

- show trunk flexion for a period equal to or greater than 7 consecutive minutes, or 45 accumulated minutes.

In the graphical interface it is possible to observe the visual information of the signals acquired by the sensory module (200).

The result produced by the computational unit (205) can have multiple technical effects, which include, but are not limited to, analysis of ECG, EDA and load distribution signals, feature extraction, notification and visual feedback to the user. The result produced makes it possible to make the user aware of their state of increased stress, fatigue and the effects of complications generated by their posture, in a work context and in real time.

To extract features, the computational unit (205) implements a method for automatic learning (e.g. using artificial neural networks), and can also perform the same function based on the segmentation of one or more collected signals. Characteristics can be extracted individually for each user, but also for groups of users, and include latencies, amplitudes, power spectral density and others. The waveforms of each signal can also be obtained (e.g. the morphology of the P-QRS-T sequence on the ECG), with the amplitudes of the points obtained for these waves considered as representative information.

The detection and prediction of exhaustion symptoms can be done through an automatic classification step of the characteristics and representative information extracted from the signals. For this purpose, Artificial Neural Networks are primarily used, but alternatively other methods can be used, namely, but not exclusively, nearest neighbor (k-NN) with the Euclidean or cosine distance as a measure of similarity between features, or support vector machines (SVM).

The device is designed for work context, but can be used in other types of contexts, namely: at home, or any type of context, in which it is convenient for the user, to observe and evaluate their state of increased stress, fatigue and complications generated by your posture, without this present invention interfering with your daily life.

Forms of embodiment

In a preferred embodiment of the present invention, the seat is a standard office chair, that is, a chair with a padded seat base, riser for height adjustment and armrests.

sensory module (200) is integrated directly into the chair with the following arrangement: ECG sensor (102) and EDA sensor (103) arranged in the distal part of the armrests and pressure sensors (104), arranged in an isosceles triangle ( one in a central front position, one in a left rear position and one in a right rear position), with dimensions of 0.2 x 0.2 m.

In the case of the ECG sensor (102), the negative terminal and the ground terminal (102.2) are connected together to the leather covering (101) that covers the distal portion of one of the armrests of the chair, while the positive terminal (102.1) is connected to the nappa covering (101) that covers the distal portion of the other armrest.

The EDA sensor terminals (103) are also connected to the electrically conductive leatherette covering (101) covering the distal portions of the armrest. The negative terminal (103.2) is connected to a different nappa covering portion (101) from the positive terminal (103.1), although on the same armrest.

It should be noted that the leatherette covering (101) of the sensor

ECG (102) is separated from the leatherette covering (101) of the EDA sensor (103).

The pressure sensors (104) are arranged in the form of a triangle, below the upper plate of the seat base and resting on the lower plate of the seat base.

In a second embodiment of the present invention, the seat is a chair without armrests. The sensory module (200) is integrated directly into the chair with the following arrangement: ECG sensor (102) and EDA sensor (103) arranged on the side of the seat base and the pressure sensors (104) arranged in the form of a an isosceles triangle (one in the front center position, one in the rear left position and one in the rear right position), below the base of the seat.

In the case of the ECG sensor (102), the negative terminal and the ground terminal (102.2) are connected together to the electrically conductive nappa covering (101) that covers a side portion of the seat base, while the positive terminal (102.1 ) is connected to the electrically conductive nappa leather covering (101) that covers the other lateral portion of the seat base.

The EDA sensor terminals (103) are also connected to the electrically conductive leatherette covering (101) covering the side portions of the seat base. The negative terminal (103.2) is connected to a portion of the leather covering (101) distinct from the positive terminal (103.1), although in the same lateral area as the other.

It should be noted that the leatherette covering (101) covering the ECG sensor (102) is separate from the leatherette covering (101) covering the EDA sensor (103).

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Claims (7)

1. Device for detecting and predicting exhaustion symptoms, consisting of a computational unit (205) and a sensory unit (200) comprising measurement terminals (201), signal transduction and conditioning (202), analog-to-digital conversion (203) and signal transmission (204), electrocardiographic (ECG) signal measurement sensors, electrodermal activity (EDA) measurement sensors and charge distribution measurement sensors, characterized in that the equipment is located on a chair and that the detection and prediction of burnout symptoms can be carried out by carrying out two types of monitoring: - continuous, by measuring the user's load distribution using pressure sensors (104) placed in the lower part of the seat base of the chair; - punctual, by acquiring electrocardiographic (ECG) and electrodermal activity (EDA) signals, carried out respectively, using an ECG sensor (102) and an EDA sensor (103), located on the arms of the chair or on the base of the chair and coated with an electrically conductive medium, through direct user contact. 2. Device according to claim 1, characterized in that the sensors for measuring electrocardiographic (ECG) signals and the sensors for measuring electrodermal activity (EDA) are covered by an electrically conductive nappa coating (101), and for the acquisition of ECG signals and EDA signals are carried out by the user's direct contact with the electrically conductive leatherette covering (101) to detect and predict exhaustion symptoms, with the diagnosis supported by sensor data. 3. Device according to claim 1, characterized in that the pressure sensors (104) are load cells. 4. Device according to claim 1, characterized in that the pressure sensors (104) are functionalized sensors. 5. Device according to any one of the preceding claims, characterized in that the electrically conductive means covering the ECG sensor (102) is separate from the electrically conductive means covering the EDA sensor (103). 6. Device according to any one of the preceding claims, characterized in that the data acquired by the measurement terminals (201) are converted, filtered and amplified by the signal transduction and conditioning electronic component (202). 7. Device according to any one of the preceding claims, characterized in that the electrical signal obtained from the signal transduction and conditioning electronic component (202) is converted into a digital signal by the analog-to-digital conversion electronic component (203).