Determination of the degree of opening of vocal cords

Abstract

Measuring method for determining a degree of opening of vocal cords (2) of a living being (1), comprising: a) delivering electrical impulses to a reference nerve (3) of the living being (1) distributed over a measuring period, b) for each of the electrical impulses emitted in step a), recording a respective time course of electromyographic measured values ​​which represent a measure of a reaction of a reference muscle (4) of the living being (1) connected to the reference nerve (3) to the corresponding electrical impulse, c) for each of the time courses of the electromyographic measured values ​​recorded in step b), by means of waveform analysis, determining a set of parameters which characterise the corresponding time course of the electromyographic measured values, d) determining the degree of opening of the vocal cords (2) of the living being (1) from the parameters determined in step c).

Description

[0001] The invention relates to a measuring method for determining the degree of opening of vocal cords of a living being and to a corresponding measuring device.

[0002] In the field of clinical anesthesiology, emergency and intensive care medicine, muscle relaxants are used for intubation (i.e. to secure the airway using a ventilation tube that is inserted into the trachea and is medically known as a tube), to improve the patient's ability to undergo surgery and to improve the patient's invasive ventilation.

[0003] Muscle relaxants cause the patient's muscles to relax. For intubation, for example, it is desirable for the muscles in the larynx to relax sufficiently so that the tube can pass through them without causing injury. Therefore, a sufficient dose of muscle relaxants is desirable for intubation. However, muscle relaxants do not specifically target individual muscles. This is why excessive administration of muscle relaxants is harmful. In the worst case, an overdose can lead to difficulty in breathing or even to breathing becoming impossible due to the relaxation of the diaphragm.

[0004] The effect of muscle relaxants is patient-dependent and therefore difficult to predict. It is therefore desirable to be able to measure the effect of muscle relaxants in patients. However, relaxation cannot be directly measured in muscles that are inaccessible or difficult to access with a measuring probe.

[0005] However, current measurement methods are known in which a nerve is used as a reference, for example, the easily accessible ulnar nerve in the arm. In this respect, however, the current state of the art only provides monitoring methods that describe the degree of muscular recovery. Conversely, information about muscular blockade is also obtained. Complete muscular recovery describes a state in which the patient is no longer affected by the effects of the muscle relaxants. These adverse effects include, for example, impaired vital functions or reduced coughing and swallowing functions, which in extreme cases can lead to the patient's death.

[0006] According to the current state of the art, only the extubation phase, i.e., extubation, can be reliably monitored. Two different quantitative measurement methods are known for this purpose: A) The "train-of-four" method, which measures the ratio of the fourth to the first muscular response amplitude in a series of four consecutive stimulations of the ulnar nerve in the innervated muscle. This method also records the number of muscle responses, which can vary between zero and four. After administration of muscle relaxants, the train-of-four method shows a fading of the responses to non-depolarizing muscle relaxants, which describes the degree of relaxation (e.g., the drug rocuronium). B) The single twitch method, in which the electromyographic response is recorded after a single stimulation of the ulnar nerve. After administration of muscle relaxants, the response diminishes. This applies to both non-depolarizing and depolarizing muscle relaxants (e.g., rocuronium, succinylcholine).

[0007] In both measurement methods, either the area under the curve or the maximum amplitude (maximum minus minimum) is calculated from the electrical waveform response.

[0008] State-of-the-art methods are not suitable for measuring static muscle tone. Therefore, readiness for intubation can only be estimated, possibly based on pharmacokinetic considerations, and the dosage of muscle relaxants can only be monitored imprecisely, for example, using the train-of-four method.

[0009] While the above description primarily applies to human patients, this is no reason why it couldn't also be applied to animals.

[0010] The object of the present invention is to provide a way to reliably determine the degree of opening of the vocal cords of a living being.

[0011] This object is achieved by the measuring method and a measuring device according to the independent claims. Further advantageous embodiments are specified in the dependent claims. The features presented in the claims and in the description can be combined with one another in any technologically expedient manner.

[0012] According to the invention, a measurement method for determining the degree of vocal cord opening of a living being is presented. The measurement method comprises: a) delivery of electrical impulses to a reference nerve of the living being over a measuring period, b) for each of the electrical impulses emitted in step a), recording a respective time course of electromyographic measured values ​​which represent a measure of a reaction of a reference muscle of the living being connected to the reference nerve to the corresponding electrical impulse, c) for each of the time courses of the electromyographic measured values ​​recorded in step b), by means of waveform analysis, determining a set of parameters which characterise the corresponding time course of the electromyographic measured values, d) Determining the degree of opening of the vocal cords of the living being from the parameters determined in step c).

[0013] The described method can be used to determine the degree of vocal cord opening of a living being. The living being is preferably a human. This case is primarily addressed here. However, there is nothing to prevent the described method from being applied to an animal other than the living being. The fact that the measurement method is aimed at determining the degree of vocal cord opening implies that this is limited to animals with vocal cords.

[0014] The vocal cords can also be referred to as vocal folds. In humans, the vocal cords serve primarily to produce speech.

[0015] The described method can be used in various fields of medicine, particularly in anesthesia. However, the described method is merely a measurement method. In particular, the described method lacks a step with which a change in the health status of the living being could be modified or with which conclusions about the health status of the living being could be drawn from the measurement results obtained. This does not change the fact that the information obtained with the described method can be used in medical procedures downstream of the described measurement method. The sole objective of the claimed measurement method is the acquisition of information.

[0016] The described measurement method can be used, in particular, to determine whether the subject's vocal cords are sufficiently open for intubation. This measurement method can thus help prevent injury to the subject during insertion of the ventilation tube. The described invention can thus contribute to solving a key problem in the induction of general anesthesia: a) The reliable and precise prediction of the vocal cord opening as a prerequisite for atraumatic intubation of a patient, ie for the injury-free introduction of a ventilation tube into the trachea. b) The reliable prediction of vocal cord opening even with low-dose muscle relaxants, which allow mask ventilation in an emergency while spontaneous breathing is largely preserved.

[0017] The information obtained with the described measurement method can, for example, enable the clinician to obtain a real-time estimate of vocal cord opening (updated every 10 seconds, for example) after administering a muscle relaxant to the patient. The algorithm used is a purely mathematical and non-stochastic calculation, fully interpretable, with very low computational requirements, allowing it to be executed in near real time on inexpensive embedded processors in an electromyography device. Although the electrical response after stimulation varies from patient to patient, the algorithmic estimate adapts to inter-individual differences in electrical waveform responses. This means that the algorithm enables a personalized calculation tailored to the individual patient.

[0018] In the described procedure, the degree of opening of the vocal cords of the living being is determined using measurement data obtained by means of electromyographic measurements.

[0019] In step a), electrical impulses distributed over a measurement period are delivered to a reference nerve of the living being. The electrical impulses stimulate the reference nerve. The electrical impulses can also be referred to as a stimulus. The electrical impulses are harmless electric shocks for the living being. The reference nerve is observed instead of directly at the difficult-to-access nerves and muscles in the larynx. The reference nerve is therefore preferably easily accessible. The reference nerve is preferably located on an extremity of the living being. The reference nerve is particularly preferably the ulnar nerve. The electrical impulses can be generated with a pulse generator and delivered to the reference nerve via an electrode. The electrode can be attached to the skin of the living being for this purpose.To deliver electrical impulses to the ulnar nerve, for example, the electrode on one of the creature's arms can be placed in contact with the creature's skin. The electrical impulses then travel through the skin to the ulnar nerve.

[0020] The measurement period begins at a temporal zero point. The electrical pulses are distributed over the measurement period. The electrical pulses are thus emitted at a certain time interval. The electrical pulses can therefore also be described as discrete. It is particularly practical to emit the electrical pulses at a fixed time interval, i.e., periodically. However, this is not necessary for the basic functionality of the described measurement method.

[0021] A measurement is performed for each of the electrical pulses in the subsequent steps. The times at which the electrical pulses are emitted thus represent the times for which measured values ​​are obtained. For a temporally resolved measurement, multiple electrical pulses are therefore emitted. The shorter the interval between consecutive electrical pulses, the greater the temporal resolution.

[0022] The delivery of the electrical impulses in step a) can be carried out in the manner known from the state of the art, for example in the “train-of-four” method or the single stimulus method.

[0023] In step b), for each of the electrical impulses delivered in step a), a respective temporal course of electromyographic measurements is recorded, which represent a measure of the response of the reference muscle connected to the reference nerve to the corresponding electrical impulse. The electromyographic measurements can, in particular, be voltage values.

[0024] Electromyographic measurements can be recorded using a sensor, which can be attached to the skin of the animal. Electromyographic measurements are used to measure the electrical activity of muscles. In step b), the activity of the reference muscle is measured in response to the stimulation of the reference nerve with the electrical impulses delivered in step a). The electromyographic measurements can be abbreviated as EMG measurements. The temporal progression of the electromyographic measurements can also be referred to as EMG curves or EMG waveforms.

[0025] Each of the temporal courses of the electromyographic measured values ​​contains a multitude of measured values ​​distributed over a period of the corresponding individual measurement. This period should not be confused with the measurement period. On the one hand, there is the measurement period, over which the electrical impulses are delivered. For each of the electrical impulses, a measured value is determined from the response of the reference muscle. These measured values ​​can be plotted over the measurement period and thus represented as a temporal course. On the other hand, a temporal course of the electromyographic measured values ​​is considered for each of the electrical impulses.

[0026] The recording of the temporal courses of the electromyographic measured values ​​in step b) can be carried out as is known from the state of the art, for example in the “train-of-four” method or the single stimulus method.

[0027] However, the described measurement method differs from the methods known from the prior art with regard to the processing of the measured values. This particularly applies to step c), according to which, for each of the temporal courses of the electromyographic measured values ​​acquired in step b), a set of parameters is determined using waveform analysis that characterize the corresponding temporal course of the electromyographic measured values.

[0028] Each of the temporal courses of the electromyographic measured values ​​contains a multitude of measured values, such as voltage values. The temporal courses of the electromyographic measured values ​​therefore contain a great deal of information. This is advantageous because the data obtained offers the potential to gain comprehensive knowledge. However, in order to utilize this potential, the desired insights must be extracted from the extensive information. This is achieved in the measurement method described with the waveform analysis in step c). Using waveform analysis, a set of parameters can be determined for each of the temporal courses of the electromyographic measured values, which characterize the corresponding temporal course of the electromyographic measured values. From the complete information of a temporal course, a set of parameters is thus obtained which characterize this temporal course.The individual temporal progressions can thus be described in a simplified manner using the characterizing parameters. Furthermore, the parameters obtained in step c) can be used for further processing.

[0029] This occurs in step d). The degree of opening of the organism's vocal cords is determined from the parameters determined in step c). The degree of opening of the vocal cords is preferably expressed as a relative percentage relative to the maximum possible degree of opening.

[0030] The algorithm used in steps c) and d) is preferably based on complex multivariate waveform analysis. The waveform analysis may include Fourier and wavelet transforms to analyze waveform characteristics of the temporal profiles of the electromyographic measured values. In contrast, the prior art only considers the area under the curve or the maximum amplitude (maximum minus minimum) of the electrical waveform response.

[0031] Experiments have investigated a variety of parameters that can characterize the temporal course of electromyographic measurements. It has been found that waveform analysis, in particular, yields parameters from which vocal cord opening can be reliably determined. Other parameters, such as the amplitude of the temporal course of electromyographic measurements or the area under the curve of the temporal course of electromyographic measurements, have proven less informative.

[0032] By cross-validation on clinical data, it was found that the described measurement method can achieve a significantly higher multivariate association with vocal cord opening than with known methods.

[0033] By employing complex multivariate waveform analyses, including Fourier and wavelet transforms, the algorithm of the described measurement method can extract patient-specific, subtle changes in the waveform morphology of the evoked muscle response. These changes are more predictive of vocal cord opening in a bivariate manner than the state-of-the-art train-of-four method, the area under the curve, or the maximum amplitude. Furthermore, the algorithm of the described measurement method integrates all this extracted information into a multivariate calculation, demonstrating a significantly lower deviation (root mean square error) between the estimated and the actually measured vocal cord opening during video laryngoscopy compared to previous technologies.

[0034] Using waveform analysis, a multitude of parameters can be obtained from a single temporal progression of measured values. The parameters that have proven particularly advantageous are described below. However, the described invention is based on the realization that, in addition to these parameters, numerous other parameters can be obtained through waveform analysis, which can yield useful results for determining the opening of the vocal cords. Therefore, the following explanations should be understood as merely an example.

[0035] In fact, it has been shown that the use of waveform analysis is the key feature for determining the degree of vocal cord opening of a living being with the described measurement method with particular reliability. This is based on the realization that waveform analysis can extract information from the measurement signals that would otherwise be unavailable.

[0036] In the prior art solutions, which consider the area under the curve or the maximum amplitude, the information content of the measurement signal is not fully extracted. In contrast, the claimed method of waveform analysis can obtain and process detailed information. In the prior art solutions, it is analyzed whether and, if so, how strong the stimulus response of the reference muscle is. This can be done by examining the area under the curve or the maximum amplitude. In the described measurement method, in contrast, the shape of the temporal progression of the electromyographic measured values ​​– i.e., the measurement signals – is also taken into account. This shape is obtained using waveform analysis.It has been found that this form allows conclusions to be drawn about the condition of the reference muscle and thus about the degree of opening of the vocal cords of the living being, which go beyond what is known from the state of the art. Below, a concrete mathematical example will be used to explain how corresponding numerical values ​​can be calculated. However, the invention described is generally based on the recognition that the use of waveform analysis is advantageous.

[0037] The comparison of traditional and modern signal analysis methods requires a fundamental consideration of the mathematical foundations. Let x: ℝ → ℝ be a piecewise continuous signal, where x(t) denotes the real-valued signal value at time t ∈ ℝ. In the classical methods, the analysis is limited to the detection of the maximum signal amplitude, expressed by A max = max{|x(t)|:t ∈ [t1,t 2]} - min{lx(t)| : t ∈ [t1,t 2]}, as well as the calculation of the area under the curve using the definite integral AUC = ∫[t1,t 2] |x(t)|dt or the normalized AUC norm = (1 / T) ∫[t1,t 2] |x(t)|dt; where [t1,t 2] ⊂ ℝ is the observation interval with t1 < t2, and T = t2 - t1 > 0 is the length of this interval. This reduction of a complex signal x(t) to individual scalar values ​​inevitably leads to a significant loss of information regarding the dynamic and spectral signal characteristics.

[0038] In contrast, the Fourier transformation for signals x(t) that satisfy the Dirichlet conditions allows, through the mathematical Fig.: ℝ → ℂ with X(f) = ∫[-∞,∞] x(t)e^(-j2πft)dt a complete spectral analysis of the signal, where f denotes the frequency in Hertz. This transformation provides access to essential signal information such as the complete frequency spectrum X(f), the phase information φ(f) = arg(X(f)) and the normalized spectral power density S xx (f) = (1 / T)|X(f)| 2 , with T as the observation period. The frequency moments and distributions obtained in this way allow for a significantly more differentiated signal characterization in the frequency domain.

[0039] The wavelet transform extends this analysis by a time-frequency localized decomposition. It is defined by the mapping W: ℝ +× ℝ → ℂ with W(s,τ) = (1 / √|s|)∫[-∞,∞]x(t)ψ*((t-τ) / s)dt, where ψ* denotes the complex conjugate mother wavelet, which must satisfy the admissibility conditions. The scaling parameter s > 0 determines the frequency resolution, while the translation parameter τ ∈ R characterizes the temporal shift. This methodology allows for multi-resolution analysis, which enables both the detection of local, transient signal properties and a scale-dependent analysis of the signal components. In contrast to the Fourier transform, it thus allows the analysis of non-stationary signal components with simultaneous time and frequency localization.

[0040] While traditional methods are limited to the measurement of the amplitude modulation A(t), modern transformation methods enable a more comprehensive signal analysis. They allow the determination of the instantaneous frequency ω i(t)= (1 / 2π)dφ(t) / dt in Hz, the extraction of the phase modulation φ(t), and the analysis of the time-dependent energy distribution E(t,f) in the time-frequency domain. For modulated signals of the form x(t) = A(t)cos(2πft + φ(t)), both the amplitude and frequency modulation characteristics can be quantified. In the context of electromyographic signal analysis, the synergistic application of the various waveform transformation methods enables multidimensional characterization in the time and frequency domains.

[0041] In a preferred embodiment of the measurement method, each of the sets of parameters comprises one parameter from the discrete Fourier transform (DFT) and several parameters using the discrete wavelet transform (DWT). Based on the electromyographic (EMG) measurements taken from the patient, the value ω1 is calculated using DWT. Based on the discrete approximation of the first derivative of the EMG, five values ​​are calculated: ω2 ... ω6 using DWT, and a value f1 using DFT. The first derivative is used to analyze patient-specific changes. In addition, the time t in minutes since the administration of a muscle relaxant is recorded. Designation Preprocessing method filter Level nth coefficient 1 no DWT D2 3 1 ω2 D1 DWT D4 3 2 ω3 D1 DWT D4 4 1 ω4 D1 DWT BL18 3 2 ω5 D1 DWT C30 2 3 ω6 D1 DWT D6 4 1 f1 D1 DFT 15 coefficients 4

[0042] The DFT is a mathematical method for transforming a finite, time-discrete signal sequence x[n] of length N into its equidistant frequency representation X[k] : X[k] = Σ[n=0 to N-1] x[n]e^(-j2πnk / N), k = {0,1,...,N-1}, and decomposes the signal into a sum of orthogonal complex exponential functions with frequencies f k = k / (NT), where T denotes the sampling period. This decomposition allows the analysis of the spectral signal properties in the frequency range from 0 to the Nyquist frequency f s / 2.

[0043] In a preferred embodiment of the measurement method, the value f1 is calculated from the discrete approximation of the first temporal derivative of the EMG signal using DFT. The f1 value is the fourth coefficient of the DTF analysis with a frequency resolution of Δf = f s / 15, where f s the sampling frequency.

[0044] DWT enables hierarchical multi-resolution analysis of signals, comparable to viewing an image at different magnification levels: The coarsest resolution level conveys the basic structure, while successively higher magnifications reveal increasingly finer details. The approximation coefficients correspond to the basic structure at low magnification (low-frequency signal components), while the detail coefficients quantify the fine structures (high-frequency signal components) that become visible at higher magnification. This multi-resolution enables precise characterization of both global and local signal properties.

[0045] The DWT implements this multi-resolution analysis using orthonormal basis functions. Wavelet families {ψ s ,τ:s ∈ ℝ + , τ ∈ ℝ} are obtained by scaling s and translating τ of a mother wavelet ψ ∈ L 2(ℝ) is generated according to ψS, τ(t) = (1 / √s)ψ((t- τ) / s). The implementation is carried out by a two-channel filter bank with complementary quadrature mirror filters: A low-pass filter h[n] generates approximation coefficients aj[n] and a high-pass filter g[n] generates detail coefficients dj[n]. The decomposition follows a dyadic scheme: aj[n] = Σ[k] h[k-2n] a j-1 [k] (basic structure) dj[n] = Σ[k] g[k-2n] a j-1 [k] (fine structure)

[0046] In the DWT, the decomposition levels j∈{1,...,J} define the scaling s = 2 j , analogous to discrete magnification levels. With increasing level j, the frequency resolution Δf doubles j = fs / 2 j+1 . The resulting wavelet coefficients characterize signal components in the corresponding frequency bands [fs / 2 j+1 , fs / 2 j ], where the specific wavelet family determines the properties of the filters and thus the analysis.

[0047] In a further preferred embodiment of the measuring method, a first wavelet parameter is determined directly from the corresponding temporal course of the electromyographic measured values ​​(ω1) and the remaining wavelet parameters (ω2 ... ω6) are determined from a discrete approximation of a first temporal derivative of the corresponding temporal course of the electromyographic measured values.

[0048] In a further preferred embodiment of the measuring method, ▪ the first wavelet parameter (ω1) is obtained with a wavelet transform with D2 filter, with a level of 3 and with 1 as the n-th coefficient, ▪ a second of the wavelet parameters (ω2) is obtained with a wavelet transform with D4 filter, with a level of 3 and with 2 as the n-th coefficient, ▪ a third of the wavelet parameters (ω3) is obtained with a wavelet transform with D4 filter, with a level of 4 and with 1 as the n-th coefficient, ▪ a fourth of the wavelet parameters (ω4) is obtained with a wavelet transform with BL18 filter, with a level of 3 and with 2 as the n-th coefficient, ▪ a fifth of the wavelet parameters (ω5) is obtained with a wavelet transform with C30 filter, with a level of 2 and with 3 as the n-th coefficient, ▪ a sixth of the wavelet parameters (ω6) is obtained with a wavelet transform with D6 filter, with a level of 4 and with 1 as the n-th coefficient.

[0049] The terms D2 filter, D4 filter, and D6 filter are established technical terms. They refer to so-called Daubechies wavelets. Daubechies wavelets are a family of orthogonal wavelets that have a compact support and a certain number of vanishing moments. D2 corresponds to the Haar wavelet, the simplest wavelet with a compact support. D4 is the fourth member of the Daubechies wavelet family. It is widely used because it offers a good balance between time and frequency localization. D6 is the sixth member of the Daubechies wavelet family and offers even finer resolution than D4, making it particularly suitable for applications with higher signal smoothing requirements.

[0050] The term C30 filter is also a well-established technical term. It refers to so-called Coiflet wavelets. The C30 wavelet of order 30 belongs to a family of orthogonal wavelets in which both the wavelet and the scaling function have 30 moments. They are particularly well suited for analyzing smooth signals. Coiflet wavelets have a compact support, meaning they are non-zero only over a limited interval, which makes them computationally efficient.

[0051] Further information on Daubechies and Coiflet wavelets can be found, for example, in the following scientific articles: AN Akansu and RA Haddad. Multi-resolution signal decomposition: transforms, subbands, and wavelets. Academic Press, San Diego, second edition, 2001, and I. Daubechies. Ten Lectures on Wavelets. Society for Industrial and Applied Mathematics, 1992.

[0052] The term BL 18 filter is also a well-established technical term. It refers to so-called Battle-Lemarie wavelets. These are closely related to multiscale approximation and prewavelet analysis. They are used for continuous functions due to their differentiability. Further information on Battle-Lemarie wavelets can be found, for example, in the following scientific article: G. Battle. Wavelets and renormalization, volume 10. World Scientific, 1999.

[0053] In a further preferred embodiment of the measuring method, in step d) the following quantities are calculated for each of the electrical pulses output in step a): X=tanh(7ω5−42 tan(ω1+ω4+f1))+ω4 sinh(ω6)+1 Y=(5−ω3)t2−X cos(ω2−ω4) Z=0.072 arctan(asinh(Y)), where t indicates a time elapsed between a start of the measurement period and an output of the respective electrical pulse, and where Z indicates a measure of the degree of opening of the vocal cords of the living being at time t.

[0054] The intermediate variable X represents exclusively information extracted from the respective temporal course of the electromyographic measurements (i.e., the EMG waveform), while the intermediate variable Y introduces the time dependence. The final result Z scales the intermediate variable Y both linearly and non-linearly and has a value range between 0 and 1, where 0 corresponds to a completely closed and 1 to a completely open vocal cord opening. In experiments, a coefficient of determination (R 2 ) of Z with respect to the vocal cord opening was determined to be 0.941. The correlation coefficient between measured and calculated vocal cord opening was thus 0.97.

[0055] This embodiment represents a concrete example of how the degree of vocal cord opening can be determined from the parameters described above. However, the mathematical equations provided illustrate that there are numerous alternatives to this embodiment. For example, even with a slight modification of the value 0.072 in the last of the three equations, a usable result can still be achieved.

[0056] In a further preferred embodiment of the measuring method, the start of the measuring period is chosen to be a time at which a muscle relaxant was administered to the living being.

[0057] In this embodiment, the time of administration of the muscle relaxant is chosen as the time zero point. Thus, the time parameter t expresses the time elapsed since the administration of the muscle relaxant.

[0058] Rocuronium and succinylcholine, for example, can be considered as muscle relaxants.

[0059] As a further aspect of the invention, a measuring device for determining the degree of opening of the vocal cords of a living being is described using a measuring method designed as described. The measuring device comprises: ▪ a pulse generator and an electrode connected thereto for outputting the electrical pulses in step a), ▪ an evaluation unit and a sensor connected thereto for recording the temporal progression of the electromyographic measured values ​​in step b), wherein the evaluation unit is set up to carry out steps c) and d).

[0060] The advantages and characteristics of the measuring method are applicable and transferable to the measuring device, and vice versa.

[0061] The invention is explained in more detail below with reference to the figure. The figure shows a particularly preferred embodiment, to which the invention is not limited, however. The figure and the proportions depicted therein are only schematic. It shows: Fig. 1: a person and a measuring device according to the invention, with which a measuring method according to the invention can be carried out.

[0062] Fig. Figure 1 shows a human being as a living being 1. The human being has vocal cords 2, the degree of opening of which is to be determined. The parameter Z is a measure of the degree of opening of the vocal cords 2. Furthermore, the human being has a reference nerve 3 and a reference muscle 4 connected to it.

[0063] In addition, Fig.1 shows a measuring device 5. The measuring device 5 is designed to determine the degree of opening of the human vocal cords 2. The measuring device 5 comprises a pulse generator 6 and a connected electrode 9 for outputting electrical impulses. The electrode 9 is in contact with the skin of the human arm in such a way that the electrical impulses can be output to the reference nerve 3 via the electrode 9.

[0064] The measuring device 5 further comprises an evaluation unit 7 and a sensor 10 connected thereto for recording temporal profiles of electromyographic measured values, which represent a measure of the reaction of the human's reference muscle 4 to the electrical impulses. For this purpose, the sensor 10 is also in contact with the skin of the human arm. A display device 8 is connected to the evaluation unit 7, via which a result determined by the evaluation unit 7 can be output. The pulse generator 6, the evaluation unit 7, and the display element 8 are arranged together in a housing 11.

[0065] The evaluation unit 7 is set up to carry out steps c) and d) of the following procedure: a) delivering electrical impulses to a human reference nerve 3 via electrode 9 over a measuring period, b) via the sensor 10, for each of the electrical impulses emitted in step a), recording a respective time course of electromyographic measured values, c) for each of the time courses of the electromyographic measured values ​​recorded in step b), by means of waveform analysis, determining a set of parameters which characterise the corresponding time course of the electromyographic measured values, d) determine the degree of opening of the human vocal cords 2 from the parameters determined in step c). List of reference symbols 1 living being 2 vocal cords 3 Reference nerve 4 Reference muscle 5 Measuring device 6 Pulse generator 7 Evaluation unit 8 Display element 9 Electrode 10 Sensor 11 housings Z Measure of the degree of opening of the vocal cords

Claims

[1] Measuring method for determining the degree of opening of vocal cords (2) of a living being (1), comprising: a) delivering electrical impulses to a reference nerve (3) of the living being (1) distributed over a measuring period, b) for each of the electrical impulses emitted in step a), recording a respective time course of electromyographic measured values ​​which represent a measure of a reaction of a reference muscle (4) of the living being (1) connected to the reference nerve (3) to the corresponding electrical impulse, c) for each of the time courses of the electromyographic measured values ​​recorded in step b), by means of waveform analysis, determining a set of parameters which characterise the corresponding time course of the electromyographic measured values, d) determining the degree of opening of the vocal cords (2) of the living being (1) from the parameters determined in step c). [2] Measuring method according to claim 1, wherein each of the sets of parameters comprises a Fourier parameter (f1) determined by means of discrete Fourier transformation from the corresponding time course of the electromyographic measured values ​​and a plurality of wavelet parameters (ω1,ω2,ω3,ω4,ωs,ω6) determined by means of discrete wavelet transformation from the corresponding time course of the electromyographic measured values. [3] Measuring method according to claim 2, wherein the Fourier parameter (f1) is determined from a discrete approximation of a first time derivative of the corresponding time course of the electromyographic measured values ​​by means of a discrete Fourier transformation. [4] Measuring method according to claim 2 or 3, wherein a first wavelet parameter (ω1) is determined directly from the corresponding time course of the electromyographic measured values ​​and the remaining wavelet parameters (ω2,ω3,ω4,ω5,ω6) are determined from a discrete approximation of a first time derivative of the corresponding time course of the electromyographic measured values. [5] Measuring method according to claim 4, wherein ▪ the first wavelet parameter (ω1) is obtained with a wavelet transform with D2 filter, with a level of 3 and with 1 as the n-th coefficient, ▪ a second of the wavelet parameters (ω2) is obtained with a wavelet transform with D4 filter, with a level of 3 and with 2 as the n-th coefficient, ▪ a third of the wavelet parameters (ω3) is obtained with a wavelet transform with D4 filter, with a level of 4 and with 1 as the n-th coefficient, ▪ a fourth of the wavelet parameters (ω4) is obtained with a wavelet transform with BL18 filter, with a level of 3 and with 2 as the n-th coefficient, ▪ a fifth of the wavelet parameters (ω5) is obtained with a wavelet transform with C30 filter, with a level of 2 and with 3 as the n-th coefficient, ▪ a sixth of the wavelet parameters (ω6) is obtained with a wavelet transform with D6 filter, with a level of 4 and with 1 as the n-th coefficient. [6] Measuring method according to claim 5, wherein in step d) the following quantities are calculated for each of the electrical pulses output in step a): X=tanh(7ω5−42 tan(ω1+ω4+f1))+ω4 sinh(ω6)+1 Y=(5−ω3)t2−X cos(ω2−ω4) Z=0.072 arctan(asinh(Y)), where t indicates a time elapsed between a start of the measuring period and an output of the respective electrical pulse, and where Z indicates a measure of the degree of opening of the vocal cords (2) of the living being (1) at time t. [7] Measuring method according to one of the preceding claims, wherein the start of the measuring period is chosen to be a time at which a muscle relaxant was administered to the living being (1). [8] Measuring device (5) for determining a degree of opening of vocal cords (2) of a living being (1) using a measuring method according to one of the preceding claims, wherein the measuring device (5) comprises: ▪ a pulse generator (6) and an electrode (9) connected thereto for delivering the electrical pulses in step a), ▪ an evaluation unit (7) and a sensor (10) connected thereto for recording the temporal courses of the electromyographic measured values ​​in step b), wherein the evaluation unit (7) is set up to carry out steps c) and d).

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