ITMI20140312U1 - DEVICE FOR THE STUDY AND DIAGNOSIS OF NEURODEGENERATIVE DISORDERS - Google Patents

Description

"DEVICE FOR THE STUDY AND DIAGNOSIS OF DISORDERS

NEURODEGENERATIVE "

The present invention relates to a medical device for the study and diagnosis of sleep disorders in the REM phase and associated neurodegenerative disorders. The classification of sleep in the five stages was defined based on the analysis of three main polysomnographic signals: the electroencephalogram (conventionally abbreviated as "EEG") which records brain activity, the electrooculogram (conventionally abbreviated as "EOG") which records the eye movements and the electromyogram (conventionally abbreviated as "EMG") which records muscle activity (usually in polysomnography that of the mylohyoid muscle). Based on the analysis of electroencephalographic, electromyographic and electrooculographic parameters, it was possible to classify sleep in five stages: four non-REM stages (stage 1, stage 2, stage 3, stage 4) and a REM stage. Sleep has a regular alternation of non-REM and REM phases consisting of cycles of similar duration. In particular, the REM stage (which takes its name from rapid eye movements) is the phase in which dreams predominantly occur and is characterized by substantial paralysis of the muscles (detectable for example by a low tone of the mental muscles) and by a 'high brain activity (the brain consumes oxygen and glucose as if the subject were awake and engaged in an intellectual activity). Some people may suffer from certain sleep disorders such as bruxism, bedwetting, restless legs syndrome, sleepwalking, sleep talk, insomnia, hypersomnia, sleep apnea and narcolepsy. Depending on the severity of the disturbance manifested, a polysomnographic analysis may be required which involves a night's sleep in the clinic or at the patient's home and which is usually carried out using special devices called polygraphs. These devices allow to simultaneously acquire different neurophysiological and cardiorespiratory signals, therefore in addition to electrooculographic (EOG), electroencephalographic (EEG) and electromyographic (EMG) signals, further signals can be acquired relating to, for example, the movement of the chest and abdomen for respiratory dynamics, electrocardiogram (EKG), O2 saturation, oro-nasal airflow (thermistor / oro-nasal cannula), patient position, etc. Polygraphs are therefore complex instruments, which require dedicated processing systems to manage the acquisition and processing of recorded data. They can be divided into two categories, fixed polygraphs, consisting of recording and processing stations for outpatient use and portable polygraphs, which can be transported by the patient out of the outpatient setting, to be then brought back to the clinic and connected to a dedicated system. for reading, processing and displaying data.

In recent years, studies on neurodegenerative diseases have shown that a particular sleep disorder, called REM behavior disorder (RBD), could be a warning sign for the onset of a neurodegenerative disease such as dementia or Parkinson's disease.

Further studies and research on neurodegenerative diseases have focused their attention on the analysis of a particular parameter, heart rate variability, conventionally abbreviated as "HRV". The main clinical application of HRV analysis is the surveillance of post-heart attack and diabetic patients. For these patients, heart rate variability provides information on the function of the sympathetic-parasympathetic balance and therefore on the risks of sudden cardiac death. The HRV in fact allows to evaluate the activity of the Vegetative Nervous System (VNS) and in particular the balance of the activity between the Sympathetic and Parasympathetic nervous system (sympathetic / vagal balance), i.e. the body's ability to modify its own balancing towards one or the other system. This mechanism is fundamental to obtain a dynamic balance of the organism both from a physiological and psychological point of view. A healthy individual has natural heart rate variability in response to factors such as breathing rhythm, emotional states, anxiety, stress, anger, etc. In other words, heart rate responds quickly to all of these. factors, changing according to the situation, so that the body is able to adapt in the best possible way to the different situations that may arise.

In recent years, HRV analyzes have also been used to identify warning elements of diseases related to the accumulation of Lewy bodies such as in the case of Parkinson's disease. In fact, several studies show that people with Parkinson's disease show a decrease in HRV.

HRV can be calculated for example from electrocardiographic recordings from which beat-to-beat heart rate can be derived from R-R intervals (cardiac cycle period). The evaluation of HRV can be carried out in the time domain or in the frequency domain, that is to say by calculating an index through statistical operations on the R-R interval, or by means of spectral analysis of an array of R-R intervals. In both methods, the HRV is obtained by processing the acquired R-R intervals on the computer at a later stage after recording. The mechanism and causes of the onset of Parkinson's disease are still not clear today. Research is currently investigating some areas such as aging, viruses, genetic and environmental factors. However, it is not clear why Parkinson's disease develops in certain people and not others. A screening activity on certain population samples could be essential to identify which environmental factors can trigger the disease and on which categories of people. The diagnosis of a neurodegenerative disease at an early stage could allow timely intervention to reduce mortality and / or disorders related to the disease or the harmful effects of treatments administered in an advanced stage of the disease.

A screening activity with a polysomnographic examination using current polygraphs would involve high costs due to the cost of the polygraphs themselves, as well as the time required for processing and viewing the results obtained from the recordings. An investigation of this type could be too burdensome for the health service, with waiting lists that are too long.

The object of the present invention is to overcome the problems of the known art discussed above, and to provide a device that allows to facilitate and speed up the diagnosis of behavioral disorders of REM sleep and of the neurodegenerative disorders associated with it.

Another object of the present invention is to provide a portable device to perform a polysomnographic examination and simultaneously record the activity of the vegetative nervous system without having to resort to post-processing of data on a computer.

Yet another object of the present invention is to provide an instrument which allows the instrumental examination to be carried out also in the home environment, and which thus allows a wide diffusion of the diagnostic practice even outside highly specialized centers.

A further object of the present invention is to provide a portable device for the study and diagnosis of neurodegenerative disorders which can be produced at a lower cost than devices of the known art and which allows a diagnosis to be reached more quickly.

These and further objects are achieved by the present invention by means of a device according to claim 1. Further peculiar characteristics are reported in the related dependent claims.

In particular, according to the present invention, the portable device for the study and diagnosis of neurodegenerative disorders comprises means for acquiring at least one polysomnographic signal, means for determining an HRV signal and at least one internal and / or external memory unit for the memorization of the polysomnographic signal and the HRV signal.

The device according to the present invention allows to simultaneously acquire at least one polysomnographic signal selected from at least one electroencephalographic signal (EEG) or at least one electromyographic signal (EMG) or at least one electrooculographic signal (EOG) or any combination of the above. The means for the acquisition of these signals comprise, for each polysomnographic signal to be acquired, one or more electrodes, at least one differential amplifier, at least one analog filter and at least one A / D converter to send the polysomnographic signals to a microcontroller, by means of of which the acquired signals are further digitally filtered. Similarly, the device also allows to acquire at least one electrocardiographic (EKG) and / or photoplethysmographic (PPG) cardiac signal.

The means for determining the HRV signal comprise at least one electrode for detecting an EKG cardiac signal and / or at least one photoplethysmographic sensor for detecting a PPG cardiac signal from which it is possible to directly determine the heart rate variability (HRV signal).

In particular, the HRV signal is determined starting from a cardiac signal, preferably a PPG signal which is converted into a square wave signal by means of a comparator. The square wave signal is then processed by the microcontroller to determine the R-R intervals and the related HRV.

The polysomnographic signals acquired and processed by the microcontroller, together with the HRV signal are stored, preferably in ASCII and / or binary format, in a memory unit and are ready for viewing.

The device according to the present invention is portable, preferably wearable by a user, and is designed to perform a simplified polysomnographic examination, unlike the classic "general purpose" polygraphs, with a consequent lower manufacturing cost.

Since there is no need for post-processing on a computer of the acquired data (to filter the signals and / or to calculate the heart rate variability), the present invention allows to speed up and simplify the procedure for reaching the diagnosis of a neurodegenerative disorder such as Parkinson's disease. The analysis of the VNS activity and behavior in the REM phase, recorded by means of the device according to the present invention, can be conducted by directly viewing the acquired signals without the need for post-processing on a computer. The visualization can therefore take place on any PC without the need for dedicated software. Preferably, the values of the polysomnographic signals and of the HRV are stored in such a way as to be synchronized in time.

This solution allows you to obtain a fast and inexpensive diagnosis by means of a low-cost device thanks to which it is therefore possible to carry out a screening activity with targeted surveys on different population samples, resulting in a sustainable burden on the health service.

Brief description of the drawings

Further aspects and advantages of the present invention will become clearer from the following description, made for illustrative and non-limiting purposes with reference to the attached schematic drawings, in which:

Figure 1 is a perspective view of an embodiment of the device according to the present invention;

Figures 2-6 are block diagrams of the main acquisition units of the device according to the present invention;

Figure 7 is a block diagram of the device according to the present invention; Figure 8 shows an example of graphic display of the signals acquired by means of the device according to the present invention.

With reference to Figure 1, the portable device 1 for the study and diagnosis of neurodegenerative disorders comprising means 2 for the acquisition of at least one polysomnographic signal, means 3 for determining an HRV signal and at least one internal memory unit 4 and / or external for storing the polysomnographic signal and the HRV signal.

The means 2 for the acquisition of at least one polysomnographic signal comprise at least two electrodes for detecting at least one polysomnographic signal, preferably arranged on the patient's body according to the international criterion 10-20. Each electrode is connected to the device 1 by means of a pin 5 able to be inserted inside a corresponding socket 6.

For greater ease of visualization, Figure 1 shows the device 1 with the electrodes disconnected from the device 1, so as to easily view the corresponding sockets 6 for the connection of electrodes / sensors to the device 1 (for each socket 6 there is an associated electrode or a sensor).

Preferably, at least one polysomnographic signal is selected from at least one EEG signal or at least one EMG signal or at least one EOG signal or any combination of the above. In the embodiment shown in Figure 1, the device 1 provides for the acquisition of three types of polysomnographic signals, EEG, EMG and EOG. In particular, the device 1 comprises means 2 for the acquisition of an EEG signal, an EOG signal and one or more EMG signals. However, embodiments may be envisaged which provide any combination of these signals.

The means 3 for determining the HRV signal comprise at least one electrode 30, 31 for detecting an EKG cardiac signal and / or at least one photoplethysmographic sensor 35 for detecting a PPG cardiac signal. Preferably, the HRV signal is determined from the cardiac PPG signal, but embodiments in which the HRV signal can be determined from a cardiac EKG signal can also be envisaged.

In Figure 1, the reference 7 indicates a socket for connecting a photoplethysmographic sensor 35 (shown in Figure 6) to the device 1, in order to detect the PPG cardiac signal.

The device 1 further comprises at least one internal and / or external memory unit 4, such as for example a removable memory card, for storing one or more acquired polysomnographic signals and the determined HRV signal. In this way it is therefore possible to simultaneously obtain a diagnosis of a possible sleep behavioral disorder in REM phase (from the visualization of the acquired polysomnographic signals) associated with an evaluation of the activity of the vegetative nervous system (from the visualization of the HRV signal) to obtain a diagnosis. of a possible neurodegenerative disorder (such as Parkinson's disease).

In correspondence with each socket 6 (input / connection for the electrodes) there is a luminous indicator 72 which, during assembly, turns on RED to indicate the disconnection of the electrode / channel or a contact impedance greater than 5 kΩ, or GREEN to indicate the correct application of the electrode.

The means 2 for the acquisition of at least one polysomnographic signal comprise two electrodes 13, 14 for the detection of an EEG signal. In particular, Figure 2A shows a block diagram of the means 2 for the acquisition of polysomnographic signals relating to the acquisition of the EEG signal only. The EEG polysomnographic signal can be detected by means of two electrodes 13, 14 suitable for being positioned in correspondence with the frontal and central regions of the cerebral cortex, such as Fz and Cz, i.e. in correspondence with the median frontal region and in correspondence of the central median region of the cerebral cortex. The means 2 further comprise an active compensation circuit 60 (DRL) of the so-called "antenna effect" connected to a reference electrode 61 positioned in a region D far from the patient's head or in correspondence with the mastoid process (right or left). In the embodiment shown in the figures, the device 1 comprises a number of electrodes 13, 14 (two electrodes) for acquiring an EEG signal, such as to make the device 1 as compact and simple as possible. Further embodiments may provide means 2 comprising a greater number of electrodes for detecting at least one EEG signal, positioned in correspondence with different regions of the cerebral cortex, while remaining within the scope of protection of the present invention. The means 2 for the acquisition of at least one polysomnographic signal comprise at least one differential amplifier to amplify at least one polysomnographic signal. With reference to Figure 2A, the means 2 comprise a differential amplifier 8 connected to the two electrodes 13, 14 to amplify the difference (symbolically indicated Fz-Cz) of the signals detected by means of the electrodes 13, 14.

The means 2 further comprise at least one analog band-pass filter 9 with frequencies fL equal to 0.16 Hz and fH equal to 60 Hz, suitable for filtering the amplified signal and at least one A / D converter 10 by means of which the signal Fz-Cz amplified and filtered it is converted into a digital signal. The digitized EEG polysomnographic signal is then digitally filtered by means of a digital filter 41 which will be described in greater detail below.

Figure 2B shows the block diagram of an alternative embodiment of the means 2 for the acquisition of polysomnographic signals relating to the acquisition of the EEG signal only. In this embodiment, the means 2 comprise a further electrode 62 adapted to be positioned in correspondence with the occipital region of the cerebral cortex, such as for example the Oz region (median occipital region). The reference 8 'symbolically indicates a block for amplifying the differences in the signals detected by the electrodes 13, 14, 61 and 62. In particular, the differential signals amplified by the block 8' are selected preferably following the international criterion 10-20 . The amplified differential signals will then be filtered, converted into digital and digitally filtered by means of the respective blocks 9 ', 10' and 41 'in a similar way to the embodiment shown in Figure 2A.

The means 2 for the acquisition of at least one polysomnographic signal further comprise two electrodes 11, 12 for the detection of an electrooculographic signal (EOG). In particular, Figure 3 shows a block diagram of the means 2 for the acquisition of polysomnographic signals relating to the acquisition of the EOG signal only. Preferably, the EOG polysomnographic signal is detected by means of two electrodes 11 and 12, ie two surface electrodes positioned respectively in correspondence with the external canthus of the right eye and the left eye. The electrodes 11, 12 can be arranged respectively 1 cm above and 1 cm below an ideal horizontal line passing through the eye (or in any case according to the international criterion 10-20). Similarly to what has been said for the EEG signal, in the embodiment shown in the figures, the means 2 comprise a number of electrodes 11, 12, in this case two, for detecting at least one EOG signal such as to make the device 1 as compact as possible.

With reference to Figure 3, the means 2 further comprise a differential amplifier 15 connected to the two electrodes 11, 12 to amplify the difference in the signals (electrooculographic potentials) detected by means of the electrodes 11, 12. The means 2 further comprise at least one analog filter low pass 16, adapted to filter the amplified signal and at least one A / D converter 17 by means of which the amplified and filtered EOG signal is converted into a digital signal. The digitized EOG polysomnographic signal is then digitally filtered by means of a digital filter 42 which will be described in greater detail below.

The means 2 for the acquisition of at least one polysomnographic signal further comprise six electrodes 21-26 for the detection of three electromyographic (EMG) signals. In particular, Figure 4 shows a block diagram of the means 2 for the acquisition of polysomnographic signals relating to the acquisition of EMG signals only. Preferably, the three EMG electromyographic signals are detected by means of three pairs of electrodes 21-22, 23-24 and 25-26. The pair of electrodes 21, 22 is suitable for being positioned in correspondence with the mylohyoid muscle (under the patient's chin), the electrodes 23, 24 are suitable for being positioned on an upper limb (for example near the biceps and / or the triceps), the electrodes 25, 26 are adapted to be positioned on a lower limb (for example near the tibial muscle and / or the calf).

As previously mentioned, further embodiments of the device 1 can provide that the means 2 for the acquisition of at least one polysomnographic signal, and in particular for the acquisition of at least one EMG electromyographic signal, can comprise a single pair of electrodes 21- 22 or 23-24 or 25-26, suitable to be positioned in correspondence with one or more muscles of the patient.

Referring to Figure 4, the means 2 further comprise at least one differential amplifier 18 connected to the electrodes 21-26 to amplify the differences in the electrical potentials that are formed in the muscles during contraction. In Figure 4, reference 18 shows a differential amplification block with three differential inputs (ie six single inputs). This amplification block 18 comprises three differential amplifiers 18a, 18b, 18c (not shown) adapted to amplify each signal detected by each pair of electrodes 21-22, 23-14 and 25-26. Each pair of electrodes is connected to a differential input of each differential amplifier 18a, 18b, 18c. Therefore at the output of the amplification block 18 there are three amplified signals (the outputs of the three differential amplifiers 18a, 18b, 18c) relating to the pairs of electrodes 21-22, 23-14 and 25-26.

The means 2 further comprise at least one analog band-pass filter 19 with frequencies fL equal to 0.16 Hz and fH equal to 80 Hz, suitable for filtering the signals amplified by the amplification block 18. Similarly to what has been said previously, with the reference 19 it is possible to indicates a filtering block comprising three bandpass filters 18a, 18b, 18c (not shown), each of it adapted to filter the signals amplified by each differential amplifier 18a, 18b, 18c.

The amplified and filtered EMG signals are then converted into digital signals by means of at least one A / D converter 20. Also in this case, for a simpler representation of the block diagram, reference 20 indicates an analog conversion block -digital comprising three A / D converters 20a, 20b, 20c (not shown) for the digital conversion of each amplified and filtered signal relating to the pairs of electrodes 21-22, 23-24 and 25-26. The digitized EMG electromyographic signals are then filtered by means of a digital filter 43 which will be described in greater detail later in the description.

The means 3 for determining the HRV signal comprise at least one electrode 30 for detecting an EKG cardiac signal. Figure 5 shows a block diagram of the means 3 for the acquisition of cardiac signals relating to the acquisition of the EKG signal only. Preferably, the cardiac signal EKG is detected by means of an electrode 30 adapted to be positioned in correspondence with the patient's heart and a reference electrode 31 (the electrode 31 can in any case be omitted, for example if it is configured as a reference electrode. electrode 14, i.e. the one positioned in correspondence with the region Cz).

The EKG signal is then amplified by means of a differential amplifier 32, filtered by means of an anti-aliasing filter 33 and converted to digital by means of an A / D converter 34. The digitized EKG cardiac signal is then digitally filtered by means of a digital filter 44.

The means 3 for determining the HRV signal further comprise a photoplethysmographic sensor 35 for detecting a PPG cardiac signal. Figure 6 shows a block diagram of the means 3 for the acquisition of cardiac signals relating to the acquisition of the PPG signal only. Preferably, the PPG cardiac signal is detected by means of a sensor 35 applicable to a lobe of the patient's ear or possibly to the terminal part of a finger of the hand. The sensor 35 detects the cyclical variations of the pressure tone in the capillaries of the lobe or of the finger, which faithfully represent the heartbeat, through the emission (by means of a photodiode) and the uptake of infrared light absorbed by the blood (by means of a phototransistor). In particular, the means 3 for determining the HRV signal comprise at least one comparator 36 for converting the PPG signal into a square wave signal or, more particularly, the electrical signal produced by the sensor 35 is converted into a two-level square wave signal. ("Low" and "high") by means of comparator 36.

With reference also to Figure 7, in addition to Figures 5, 6, the means 3 for determining the HRV signal further comprise a microcontroller 38 for digital processing of the EKG cardiac signal and / or the PPG signal converted into square wave. In particular, from the square wave signal it is possible to derive the intervals R-R by means of an interrupt system 37 implemented by the microcontroller 38. The interrupt system 37 detects the transitions from the low level to the high level of the square wave signal, so as to determine the instant in time in which this transition took place. The microcontroller, by comparing two successive transitions, determines the R-R interval from which it is possible to obtain the beat-tobeat heart rate.

In other words, the microcontroller 38 can calculate the HRV signal directly from the PPG signal converted to square wave. Preferably, the microcontroller 38 determines the heart rate starting from the R-R intervals, therefore the HRV signal is calculated by means of algorithms per se known in the art.

Further embodiments may provide that the HRV signal is derived from the digitized EKG signal. In the latter case, the R-R intervals will be obtained, by means of the microcontroller 38, from the comparison between two successive maximums of the EKG signal. Thanks to the present invention it is therefore possible to calculate the HRV signal from a cardiac signal (PPG and / or EKG) without having to resort to post-processing of the data on a computer.

The microcontroller 38 is further adapted to the digital processing of at least one polysomnographic signal. The block diagram of Figure 7 describes the connection of the main functional blocks of the device 1 according to the present invention. In particular, the reference number 39 indicates an analog block comprising the differential amplifiers 8, 15, 18, 32, the analog filters 9, 16, 19, 33 and the A / D converters 10, 17, 20, 34 of the means 2 and of the means 3 described in Figures 2-5, for acquiring the polysomnographic signals EEG, EOG and EMG and the cardiac signal EKG. At the input of block 39 there are electrodes 11-14, 21-26, 30 and 31 for the detection of the aforementioned signals, while at the output of block 39 there are the amplified, filtered and digitized signals ready for digital processing for means of the microcontroller 38. As previously described, the digitized signals are processed by the microcontroller 38 with a digital filtering indicated schematically by a block 40 comprising the various digital filters 41-44, 41 'shown in Figures 2-5.

In particular, for the EEG signal, the digital filters 41, 41 'preferably include at least a Butterworth type bandpass filter with programmable frequencies fL equal to 3 Hz and fH between 30 Hz and 40 Hz.

For the EOG signal, the digital filter 42 preferably comprises a Butterworth type bandpass filter with programmable frequencies fL between 1 Hz and 3 Hz and fH between 12 Hz and 15 Hz.

For EMG signals, the digital filter 43 preferably comprises at least a first Butterworth type bandpass filter with programmable frequencies fL equal to 25 Hz and fH equal to 70 Hz and at least a second band-eliminating filter with programmable frequencies fL equal to 48 Hz and fH equal to 52 Hz.

For the EKG signal, the digital filter 44 preferably comprises a Butterworth type bandpass filter with programmable frequencies fL equal to 0.1 Hz and fH equal to 40 Hz.

The microcontroller 38 comprises a data storage management unit 50, by means of which at least one polysomnographic signal EEG, EOG, EMG (possibly also cardiac signal EKG) and the HRV signal are stored inside at least one memory 4. The device 1 can therefore comprise an internal memory unit 4 and / or an external memory unit 4 (such as an SD card or external USB memory). In particular, the device 1 may comprise a module 51 for receiving and transmitting data in order to transfer the acquired signals to an external memory unit or directly to a display device (tablet, smartphone, PC, etc.). Module 51 can further allow you to change the options relating to the acquisition of signals, or program the start and end of the acquisition based on a specific time slot.

Preferably both the polysomnographic signals and the HRV signal are stored in ASCII and / or binary format, so as to be able to directly view the acquired signals without the need for post-processing on a computer. The visualization can therefore take place on any PC with a generic software for visualization (for example MatLab, Octave, Excel, etc.) without the need for dedicated software.

The microcontroller 38 is further adapted to control the impedance detected by the electrodes during assembly on the patient. In this way the technician is provided with an immediate indication of the correctness of the assembly, allowing him to intervene quickly with the addition of gel or paste with saline content to lower the contact impedance of the channel indicated by the red light.

The device 1 is similar to a Holter type device, therefore it can be worn by the patient during sleep. Figure 7 further indicates the power management unit with reference 63. Device 1 can be powered directly from the mains or by batteries.

The values of the polysomnographic signals and of the HRV are stored in such a way as to be temporally synchronized with each other. Figure 8 shows an example of displaying the signals acquired by means of the device according to the present invention. In the example of Figure 8, four graphs are shown, in which time is represented along the abscissa axis, while the values of the various quantities of interest are represented along the ordinate axes; in particular, graph 52 shows the HRV signal, graphs 53, 54 and 55 show the polysomnographic signals EOG, EMG (of the myloid muscle) and EEG (Fz-Cz) respectively. This solution allows to distinguish the REM phase from the other sleep stages, to identify a possible RBD disorder (from the presence of muscle tone of the mylohyoid muscle) and at the same time to visualize the activity of the vegetative nervous system (from the HRV signal) thus obtaining a diagnosis of a possible neurodegenerative disorder in a short time with the possibility of carrying out a screening activity on different population samples with a reasonable cost for the health service.

Claims (13)

CLAIMS 1. Portable device (1) for the study and diagnosis of neurodegenerative disorders comprising means (2) for the acquisition of at least one polysomnographic signal, characterized in that it comprises means (3) for determining an HRV signal and at least one unit of internal and / or external memory (4) for storing said at least one polysomnographic signal and said HRV signal. Device (1) according to claim 1, wherein said at least one polysomnographic signal is selected from at least one EEG signal or at least one EMG signal or at least one EOG signal or any combination of the above. Device (1) according to claim 1 or 2, wherein said means (3) for determining an HRV signal comprise at least one electrode (30, 31) for detecting an EKG cardiac signal and / or at least one photoplethysmographic sensor (35) to detect a PPG heart signal. Device (1) according to claim 1, wherein said means (2) for acquiring at least one polysomnographic signal comprise at least two electrodes (13, 14, 61, 62, 11, 12, 21-26) for detection of said at least one polysomnographic signal. 5. Device (1) according to claim 1, wherein said means (2) for the acquisition of at least one polysomnographic signal comprise at least one differential amplifier (8, 8 ', 15, 18) to amplify said at least one polysomnographic signal. Device (1) according to claim 1, wherein said means (3) for determining said HRV signal comprise at least one differential amplifier (32) for amplifying said EKG cardiac signal and / or at least one comparator (36) for converting said signal PPG in a square wave signal. Device (1) according to claim 1, wherein said means (2) for acquiring at least one polysomnographic signal comprise at least one A / D converter (10, 10 ', 17, 20) for the digital conversion of said at least one polysomnographic signal. Device (1) according to claim 1, wherein said means (3) for determining said HRV signal comprises an A / D converter (34) for digital conversion of said EKG cardiac signal. Device (1) according to any one of claims 1 to 8, wherein said means (3) for determining said HRV signal comprise a microcontroller (38) for digital processing of said EKG cardiac signal and / or said signal PPG converted to square wave. 10. Device (1) according to claim 9, wherein said microcontroller (38) is suitable for digital processing of said at least one polysomnographic signal. Device according to claim 9 or 10, wherein said microcontroller (38) calculates said HRV signal directly from said PPG signal converted into square wave. Device (1) according to any one of the preceding claims, wherein said at least one polysomnographic signal and said HRV signal are stored in said at least one internal and / or external memory unit (4) so as to be temporally synchronized with each other. Device (1) according to any one of the preceding claims in which said at least one polysomnographic signal and said HRV signal are stored in ASCII and / or binary format.