Determining a degree of opening of vocal cords

Abstract

The invention relates to a measuring method for determining a degree of opening of vocal cords (2) of a living being (1), comprising: a) emitting electrical pulses distributed over a measurement period to a reference nerve (3) of the living being (1), b) for each of the electrical pulses output in step a), detecting a respective temporal profile of electromyographic measurement values which represent a measure for a response to the corresponding electrical pulse of a reference muscle (4) of the living being (1), said reference muscle being connected to the reference nerve (3), c) for each of the temporal profiles of the electromyographic measurement values detected in step b), by means of waveform analysis determining a set of parameters which characterise the corresponding temporal profile of the electromyographic measurement 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] Determination of the degree of vocal cord opening

[0002] The invention relates to a measuring method for determining the degree of opening of the vocal cords of a living being and to a corresponding measuring device.

[0003] In the fields of clinical anesthesiology, emergency and intensive care medicine, muscle relaxants are used for intubation (i.e., securing the airway using a breathing tube inserted into the trachea, medically known as a tube), to improve the patient's ability to operate in surgery, and to improve invasive ventilation of the patient.

[0004] Muscle relaxants cause the patient's muscles to relax. For intubation, for example, it is desirable that the muscles in the larynx are sufficiently relaxed so that the endotracheal tube can pass through them without causing injury. Therefore, an adequate dose of muscle relaxants is desirable for successful intubation. However, muscle relaxants do not act specifically on individual muscles. This is a key reason why excessive administration of muscle relaxants is harmful. In the worst case, an overdose can lead to impaired breathing or even complete respiratory arrest due to relaxation of the diaphragm. 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 individual patients.However, the relaxation of such muscles cannot be measured directly, or only with great difficulty, if they are not accessible or only with great difficulty to a measuring probe.

[0005] However, measurement methods are known from the prior art in which a nerve is used as a reference, for example, the easily accessible ulnar nerve in the arm. In this respect, however, only monitoring methods that describe the degree of muscular recovery are known from the prior art. 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. According to the prior art, therefore, only the extubation phase, i.e., the extubation itself, can be reliably monitored. Two different quantitative measurement methods are known from the prior art for this purpose:

[0006] 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 stimuli to the ulnar nerve at the innervated muscle. This method also records the number of muscle responses, which can vary between zero and four. After administration of a muscle relaxant, the train-of-four reveals a fading of responses with non-depolarizing muscle relaxants, thus describing the degree of relaxation (for example, 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 a muscle relaxant, the response decreases. This applies to both non-depolarizing and depolarizing muscle relaxants (examples: 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] The methods known from the prior art are not suitable for measuring static muscle tone. Therefore, readiness for intubation can only be assumed, 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 applies primarily to humans as patients, there is no inherent reason why it could not also be applied to animals. The object of the present invention is to provide a means of reliably determining the degree of opening of the vocal cords of a living being.

[0010] This problem is solved by the measuring method and measuring device according to the independent claims. Further advantageous embodiments are specified in the dependent claims. The features described in the claims and in the description can be combined with one another in any technologically meaningful way. According to the invention, a measuring method for determining the degree of opening of the vocal cords of a living being is presented. The measuring method comprises:

[0011] a) the delivery of electrical impulses to a reference nerve of the living being distributed over a measurement period,

[0012] b) for each of the electrical impulses delivered in step a), recording a respective time course of electromyographic measurements, which represent a measure of a reaction of a reference muscle of the organism connected to the reference nerve to the corresponding electrical impulse,

[0013] c) for each of the time courses of the electromyographic measurements recorded in step b), determine a set of parameters that characterize the corresponding time course of the electromyographic measurements by means of waveform analysis,

[0014] d) Determine the degree of opening of the vocal cords of the living being from the parameters determined in step c).

[0015] The described method can be used to determine the degree of opening of the vocal cords in a living being. The living being is preferably a human being. This is the primary focus here. However, there is nothing to prevent the described method from being applied to an animal. The fact that the measurement method is aimed at determining the degree of opening of vocal cords implies that it is limited to animals with vocal cords.

[0016] The vocal cords can also be called vocal folds. In humans, the vocal cords serve primarily to produce speech.

[0017] The described method can be used in various areas of medicine, particularly in anesthesia. However, the described method is merely a measurement procedure. Specifically, the described method lacks a step that could alter the health status of the organism or allow conclusions to be drawn about the organism's health status from the measurement results. This remains true even though the information obtained with the described method can be used in subsequent medical procedures. The sole purpose of the claimed measurement method is to obtain information. Specifically, the described measurement method can be used to determine whether the organism's vocal cords are sufficiently open for intubation.The described measuring method can thus help to avoid injuries to the living being during the insertion of the breathing tube. The described invention can therefore contribute to solving a significant problem in the induction of general anesthesia.

[0018] a) The reliable and precise prediction of the vocal cord opening as a prerequisite for atraumatic intubation of a patient, i.e., for the injury-free insertion of a breathing tube into the trachea.

[0019] b) The reliable prediction of vocal cord opening even with low doses of muscle relaxants, allowing mask ventilation in emergencies while largely preserving spontaneous breathing.

[0020] The information obtained with the described measurement method can, for example, allow clinicians to obtain a real-time estimate of vocal cord opening (updated, for instance, every 10 seconds) after administering a muscle relaxant to a patient. The algorithm used is a purely mathematical and non-stochastic calculation, fully interpretable, with very low computational requirements, allowing it to be executed almost in real time on inexpensive embedded processors in an electromyographic device. Although the electrical response after stimulation varies from patient to patient, the algorithmic estimate adapts to the interindividual differences in the electrical waveform responses. This means that the algorithm enables a personalized calculation tailored to the individual patient.In the described procedure, the degree of opening of the vocal cords of the organism is determined using measurement data obtained through electromyographic measurements.

[0021] In step a), electrical impulses distributed over a measurement period are delivered to a reference nerve of the organism. The electrical impulses stimulate the reference nerve. The electrical impulses can also be referred to as stimuli. These electrical impulses are harmless electric shocks for the organism. Instead of a direct measurement, the reference nerve is observed 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 organism. The ulnar nerve is particularly preferred as the reference 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 organism.To deliver electrical impulses to the ulnar nerve, for example, the electrode can be placed on the skin of the animal's arm. The electrical impulses then travel through the skin to the ulnar nerve.

[0022] The measurement period begins at a time zero. The electrical pulses are distributed over this period. They are therefore emitted at time intervals. Thus, the electrical pulses can also be described as discrete. It is particularly practical to emit the electrical pulses at fixed time intervals, i.e., periodically. However, this is not necessary for the basic functionality of the described measurement method.

[0023] For each electrical pulse, a measurement is performed in the following steps. The times at which the electrical pulses are emitted thus represent the points in time for which measured values ​​are obtained. For a time-resolved measurement, several electrical pulses are therefore emitted. The shorter the interval between successive electrical pulses, the greater the temporal resolution.

[0024] The delivery of the electrical impulses in step a) can be carried out in the manner known from the prior art, for example in the “train-of-four” method or single-stimulus method.

[0025] In step b), for each of the electrical impulses delivered in step a), a corresponding time course of electromyographic measurements is recorded, which represent a measure of the response of the reference muscle connected to the reference nerve to the respective electrical impulse. The electromyographic measurements can be, in particular, voltage values.

[0026] Electromyographic measurements can be acquired using a sensor, which can be attached to the skin of the organism. Electromyographic measurement is used to measure the electrical activity of muscles. In step b), the activity of the reference muscle is measured in response to stimulation of the reference nerve with the electrical impulses delivered in step a). Electromyographic measurements can be abbreviated as EMG values. The temporal profiles of the electromyographic measurements can also be referred to as EMG curves or EMG waveforms.

[0027] Each time series of electromyographic measurements contains a multitude of measurements distributed over the corresponding individual measurement period. 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 electrical impulse, a measurement is determined from the response of the reference muscle. These measurements can be plotted over the measurement period and thus represented as a time series. On the other hand, a separate time series of electromyographic measurements is considered for each electrical impulse.

[0028] The recording of the temporal profiles of the electromyographic measurements in step b) can be carried out in the way that is known from the state of the art, for example in the “train-of-four” method or the single stimulus method.

[0029] However, the described measurement method differs from prior art methods with regard to the processing of the measured values. This applies in particular to step c), according to which, for each of the time courses of the electromyographic measured values ​​recorded in step b), a set of parameters is determined by means of waveform analysis, which characterize the corresponding time course of the electromyographic measured values.

[0030] Each time series of electromyographic measurements contains a multitude of measurements, such as voltage values. These time series thus contain a wealth of information. While this is advantageous because the acquired data offers the potential to gain comprehensive insights, to fully utilize this potential, the desired findings must be extracted from this extensive information. In the described measurement procedure, this is achieved through waveform analysis in step c). Waveform analysis allows for the determination of a set of parameters for each time series of electromyographic measurements, characterizing that specific time series. From the complete information of a time series, a set of parameters is thus derived that characterize that time series.The individual time courses can thus be described more simply using the characterizing parameters. Furthermore, the parameters obtained in step c) can be used for further processing.

[0031] This is done in step d). The degree of opening of the vocal cords of the organism is determined from the parameters determined in step c). The degree of opening of the vocal cords is preferably expressed as a percentage relative to the maximum possible degree of opening.

[0032] The algorithm used in steps c) and d) is preferably based on complex multivariate waveform analysis. This waveform analysis can include Fourier and wavelet transformations to analyze the waveform characteristics of the time-dependent electromyographic measurements. In contrast, prior art methods only consider the area under the curve or the maximum amplitude (maximum minus minimum) from the electrical waveform response. Experiments have investigated a variety of parameters that can characterize the time-dependent electromyographic measurements. These experiments have shown that waveform analysis, in particular, yields parameters from which the opening of the vocal cords can be reliably determined.Other parameters, such as the amplitude of the temporal profiles of the electromyographic measurements or the area under the temporal profiles of the electromyographic measurements plotted as a curve, have proven to be less informative.

[0033] Cross-validation with clinical data showed that the described measurement method yields a significantly higher multivariate association with vocal cord opening than known methods.

[0034] By employing complex multivariate waveform analyses, including Fourier and wavelet transformations, 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 bivariately more informative for vocal cord opening than the state-of-the-art train-of-four method, area under the curve, or maximum amplitude. Furthermore, the algorithm of the described measurement method integrates all this extracted information into a multivariate calculation, which demonstrates a significantly lower deviation (squared mean error) between the estimated and the actually measured vocal cord opening during videolaryngoscopy compared to previous technologies.

[0035] Waveform analysis can be used to derive a multitude of parameters from a single time series of measurements. The following describes parameters that have proven particularly advantageous. However, the described invention is based on the understanding that waveform analysis can also yield numerous other parameters in addition to these, which can provide useful results for determining vocal cord opening. Therefore, the following explanations should be understood as merely an example.

[0036] In fact, it has been shown that the use of waveform analysis is the key feature for reliably determining the degree of vocal cord opening in a living being using the described measurement method. This is based on the understanding that waveform analysis can extract information from the measurement signals that would otherwise be unavailable.

[0037] In prior art solutions that 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 waveform analysis method allows for the acquisition and processing of detailed information. Prior art solutions analyze whether, and if so, how strong, the stimulus response of the reference muscle is. This can be done by considering the area under the curve or the maximum amplitude. The described measurement method, however, also takes into account the shape of the temporal profiles of the electromyographic measurements—that is, the measurement signals. This shape is obtained using waveform analysis.It has been shown that this form allows conclusions to be drawn about the state of the reference muscle and thus about the degree of opening of the vocal cords of the organism, which go beyond the measures known from the prior art. The following section explains, using a concrete mathematical example, how corresponding numerical values ​​can be calculated. However, the described invention lies generally in the recognition that the use of waveform analysis is advantageous.

[0038] Comparing traditional and modern signal analysis methods first requires a fundamental consideration of the mathematical foundations. Let x: HR -> HR be a piecewise continuous signal, where x(t) denotes the real-valued signal value at time te HR. With classical methods, the analysis is limited to determining the maximum signal amplitude, expressed by A. max= max{|x(t)|: te [ti,t2]} - m / n{|x(t)|: te [ti,t2]}, as well as the calculation of the area under the curve using the definite integral AUC = j [ti,t2] |x(t) |dt or the normalized AUCnorm =

[0039] ( 1 / T) j [ti,t2] |x(t) |dt; where [ti,t2] c HR denotes the interval under consideration with ti < t2, and T = t2- ti > 0 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.

[0040] In contrast, the Fourier transform for signals x(t) that satisfy the Dirichlet conditions allows a complete spectral analysis of the signal through the mathematical mapping X HR -> (C with X(f) = j [-00,00] x(t)e (-j2nft)dt, where f denotes the frequency in Hertz. This transformation provides access to essential signal information such as the complete frequency spectrum X(f) and the phase information. <p(f) = arg (X(f)) sowie der normierten spektralen Leistungsdichte 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.

[0041] The wavelet transform extends this analysis by providing a time-frequency-localized decomposition. It is defined by the mapping W: U x

[0042]

[0043] with W(S, T) = (1 / V|s|) \ [-00,00] x(t)i|j*((tT) / s)dt, where I|J* denotes the complex conjugate parent wavelet that must satisfy the admissibility conditions. The scaling parameter s > 0 determines the frequency resolution, while the translation parameter ie HR characterizes the time shift. This methodology allows for multi-resolution analysis, enabling 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. While traditional methods are limited to capturing the amplitude modulation A(t), modern transformation methods enable a more comprehensive signal analysis.They allow the determination of the instantaneous frequency com) = (1 / 2n)d <p(t) / dt in Hz, die Extraktion der Phasenmodulation <p(t) sowie die Analyse der zeitabhängigen Energieverteilung E(t,f) im Zeit-Frequenz-Raum. Für modulierte Signale der Form x(t) = A(t)cos(2nft + <p(t)) können damit sowohl die Amplituden- als auch die Frequenzmodulationscharakteristika quantifiziert werden. Im Kontext der elektro-myographischen Signalanalyse ermöglicht die synergistische Anwendung der verschiedenen Wellenform-Transformationsmethoden eine mehrdimensionale Charakterisierung in Zeit- und Frequenzdomäne.

[0044] In a preferred embodiment of the measurement method, each set of parameters comprises: one parameter from the discrete Fourier transform (DFT) and several parameters obtained using the discrete wavelet transform (DWT). Based on the electromyographic (EMG) measurements taken from the patient, the value is determined using DWT.

[0045]

[0046] Calculated. Based on the discrete approximation of the first EMG lead, five values ​​are calculated: M2...r6 using DWT and a value f using DFT. The first lead is used to analyze patient-specific changes. Additionally, the time t in minutes since the administration of a muscle relaxant is recorded.

[0047] Designation: Method, Filter Level

[0048] nung processing coefficient no DWT D2 3 1 D1 DWT D4 3 2 D1 DWT D4 4 1 D1 DWT BL18 3 2 D1 DWT C30 2 3 D1 DWT D6 4 1 fl D1 DFT 15 coefficients 4

[0049]

[0050] The DFT is a mathematical procedure for transforming a finite, time-discrete signal sequence x[n] of length N into its equidistant frequency representation X[k]: X[k] = £[n=0 to N-1] x[n]e A (-j2nnk / N), k = {0, 1,..., N -1}, and decomposes the signal into a sum of orthogonal complex exponential functions with frequencies fk = k / (NT), where T denotes the sampling period. This decomposition enables the analysis of the spectral signal properties in the frequency range from 0 to the Nyquist frequency fs / 2.

[0051] In a preferred embodiment of the measurement method, the value is derived from the discrete approximation of the first time derivative of the EMG signal.

[0052]

[0053] Calculated using DFT. The value is the fourth coefficient of the DFT analysis calculated with a frequency resolution of Af = fs / 15, where f s the sampling frequency.

[0054] The DWT enables hierarchical multi-resolution analysis of signals, similar to viewing an image at different magnification levels: The coarsest resolution reveals 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 magnifications. This multi-resolution capability allows for the precise characterization of both global and local signal properties.

[0055] The DWT implements this multi-resolution analysis using orthonormal basis functions. Wavelet families

[0056]

[0057] se U, T e IR} are transformed by scaling s and translation T of a parent wavelet e L. 2(W according to I|JS, T(t) = (1 / Vs)i|j((tT) / s) is generated. 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] = 2[k] h[k-2n] aj-i[k] (basic structure) & dj[n] = 2[k] g[k-2n] aj-i[k] (fine structure)

[0058] In the DWT, the decomposition levels je{1,..., J} define the scaling s = 2. j , analogous to discrete magnification levels. With increasing level, the frequency resolution doubles: Afj = fs / 2 i+1 The resulting wavelet coefficients characterize signal components in the corresponding frequency bands [fs / 2 i+1 , fs / 2 J], wherein the specific wavelet family determines the properties of the filters and thus the analysis. In a further preferred embodiment of the measurement method, a first wavelet parameter is determined directly from the corresponding time course of the electromyographic measurements (ro, and the remaining wavelet parameters (a)2...ro6) are determined from a discrete approximation of a first time derivative of the corresponding time course of the electromyographic measurements.

[0059] In another preferred embodiment of the measuring method,

[0060] ■ the first wavelet parameter (ro) obtained with a wavelet transformation using a D2 filter, with a level of 3 and with 1 as the nth coefficient,

[0061] ■ a second wavelet parameter (co2) obtained with a wavelet transformation with D4-FH- ter, with a level of 3 and with 2 as the nth coefficient,

[0062] ■ a third of the wavelet parameters (co3) obtained with a wavelet transformation with D4-FH- ter, with a level of 4 and with 1 as the nth coefficient,

[0063] ■ a fourth wavelet parameter (co4) obtained with a wavelet transformation using a BL18 filter, with a level of 3 and with 2 as the nth coefficient,

[0064] ■ a fifth of the wavelet parameters (co5) obtained with a wavelet transformation using a C30 filter, with a level of 2 and with 3 as the nth coefficient,

[0065] ■ a sixth wavelet parameter (co6) obtained with a wavelet transformation using a D6 filter, with a level of 4 and with 1 as the nth coefficient.

[0066] 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 with a compact support and a specific number of vanishing moments. D2 corresponds to the Haar wavelet, the simplest compact-support wavelet. D4 is the fourth member of the Daubechies wavelet family. It is frequently 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.

[0067] The term C30 filter is also an 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 function and the scaling function have 30 moments. They are particularly well-suited for the analysis of smooth signals. Coiflet wavelets have a compact support, meaning they are non-zero only over a limited interval, which makes them computationally efficient. Further information on Daubechies and coiflet wavelets can be found, for example, in the following scientific articles: AN Akansu and RA Haddad. Multiresolution 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.

[0068] The term BL18-Fi Iter is also an 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.

[0069] In another preferred embodiment of the measuring method, in step d) the following quantities are calculated for each of the electrical pulses output in step a):

[0070] / 75 4 \

[0071] X = tanh - - - — + Ü)4sinh(ü)6) + 1

[0072]

[0073] \2 tanf^ + Ü)4+ fJJ

[0074] Y = (5 — ÜJ3) t 2 — X COS(Ü)2— ro4)

[0075] Z = 0.072 arctan(asinh(T)),

[0076] where t represents the time elapsed between the start of the measurement period and the output of the respective electrical impulse, and where Z represents a measure of the degree of opening of the vocal cords of the organism at time t.

[0077] The intermediate variable X represents exclusively information extracted from the respective temporal progression 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 fold opening. In experiments, a coefficient of determination (R) was calculated. 2The correlation coefficient between measured and calculated vocal fold opening was determined to be 0.941.

[0078] This embodiment provides a concrete example of how the degree of vocal cord opening can be determined from the parameters described above. However, the mathematical equations given illustrate that numerous alternatives to this embodiment exist. For example, a usable result can still be obtained with a slight modification of the value 0.072 in the last of the three equations.

[0079] In another 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 organism.

[0080] 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.

[0081] Examples of muscle relaxants that can be considered are rocuronium and succinylcholine.

[0082] 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:

[0083] ■ a pulse generator and an associated electrode for outputting the electrical pulses in step a),

[0084] ■ an evaluation unit and an associated sensor for recording the temporal profiles of the electromyographic measurements in step b), wherein the evaluation unit is set up to perform steps c) and d).

[0085] The advantages and features of the measuring method are applicable and transferable to the measuring device, and vice versa.

[0086] The invention is explained in more detail below with reference to the figure. The figure shows a particularly preferred embodiment, to which, however, the invention is not limited. The figure and the size relationships shown therein are only schematic. It shows:

[0087] Fig. 1: A human being and a measuring device according to the invention, with which a measuring method according to the invention can be carried out. Fig. 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 an associated reference muscle 4.

[0088] Furthermore, a measuring device 5 is shown in Fig. 1. The measuring device 5 is designed to determine the degree of opening of the vocal cords 2 in humans. The measuring device 5 comprises a pulse generator 6 and an associated 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.

[0089] Furthermore, the measuring device 5 comprises an evaluation unit 7 and an associated sensor 10 for recording the temporal profiles of electromyographic measurements, which represent a measure of the response of the human reference muscle 4 to the electrical impulses. The sensor 10 is also in contact with the skin of the human arm. A display unit 8 is connected to the evaluation unit 7, and a result determined by the evaluation unit 7 can be output via this unit. The pulse generator 6, the evaluation unit 7, and the display unit 8 are arranged together in a housing 11.

[0090] Evaluation unit 7 is set up to carry out steps c) and d) of the following procedure:

[0091] a) Delivery of electrical impulses to a human reference nerve 3 via electrode 9 over a measurement period,

[0092] b) via sensor 10, for each of the electrical impulses output in step a), capture a respective temporal profile of electromyographic measurements; c) for each of the temporal profiles of the electromyographic measurements captured in step b), determine a set of parameters that characterize the corresponding temporal profile of the electromyographic measurements by means of waveform analysis.

[0093] d) Determine the degree of opening of human vocal cords 2 from the parameters determined in step c). Reference list

[0094] 1 living being

[0095] 2 vocal cords

[0096] 3 Reference nerve

[0097] 4 Reference muscle

[0098] 5 Measuring device

[0099] 6 Pulse generator

[0100] 7 Evaluation unit

[0101] 8 Display element

[0102] 9 electrode

[0103] 10 Sensor

[0104] 11 cases

[0105] Z is a measure of the degree of opening of the vocal cords.

Claims

Claims 1. Measurement method for determining the degree of opening of vocal cords (2) of a living being (1), comprising: a) Delivery of electrical impulses to a reference nerve (3) of the living being (1) distributed over a measurement period, b) for each of the electrical impulses issued in step a), recording a respective time course of electromyographic measurements, which represent a measure of a response of a reference muscle (4) of the organism (1) connected to the reference nerve (3) to the corresponding electrical impulse, c) for each of the time courses of the electromyographic measurements recorded in step b), determine a set of parameters that characterize the corresponding time course of the electromyographic measurements by means of waveform analysis, d) from the parameters determined in step c) determine the degree of opening of the vocal cords (2) of the living being (1).

2. Measurement method according to claim 1, wherein each of the sets of parameters comprises one Fourier parameter ( ) determined by discrete Fourier transformation from the corresponding time course of the electromyographic measurements and several wavelet parameters ( ) determined by discrete wavelet transformation from the corresponding time course of the electromyographic measurements. <x)-,<x)2,r 3,<x)4,<x)g,<x)g) umfasst.

3. Measurement method according to claim 2, wherein the Fourier parameter (fa) is determined from a discrete approximation of a first temporal derivative of the corresponding temporal course of the electromyographic measurements by means of a discrete Fourier transformation.

4. Measurement method according to claim 2 or 3, wherein a first wavelet parameter (ro) is determined directly from the corresponding temporal course of the electromyographic measurements and the remaining wavelet parameters (Ü)2, O)3, Ü)4, Ü)5, Ü)6) are determined from a discrete approximation of a first temporal The derivation of the corresponding temporal course of the electromyographic measurements can be determined.

5. Measuring method according to claim 4, wherein ■ the first wavelet parameter (ro) is obtained with a wavelet transformation using a D2-FH filter, with a level of 3 and with 1 as the nth coefficient, ■ a second wavelet parameter (co2) is obtained with a wavelet transformation using a D4 filter, with a level of 3 and with 2 as the nth coefficient, ■ a third wavelet parameter (co3) is obtained with a wavelet transformation using a D4 filter, with a level of 4 and with 1 as the nth coefficient, ■ a fourth wavelet parameter (co4) is obtained with a wavelet transformation using a BL18 filter, with a level of 3 and with 2 as the nth coefficient, ■ a fifth of the wavelet parameters (ÜJ5) is obtained with a wavelet transformation using a C30 filter, with a level of 2 and with 3 as the nth coefficient, ■ a sixth wavelet parameter (ÜJ6) is obtained using a wavelet transformation with a D6 filter, with a level of 4 and with 1 as the nth coefficient.

6. Measurement method according to claim 5, wherein in step d) the following quantities are calculated for each of the electrical impulses output in step a): / 75 4 \ X = tanh - - - — + Ü)4sinh(n>6) + 1 \2 tanlni-L + n>4+ f J Y = (5 — n>3) t 2 — X cos(n>2— ro4) Z = 0.072 arctan(asinh(T)), where t represents the time elapsed between the start of the measurement period and the output of the respective electrical impulse, and where Z represents a measure of the degree of opening of the vocal cords (2) of the organism (1) at time t.

7. Measurement method according to one of the preceding claims, wherein the start of the measurement period is the time at which a muscle relaxant was administered to the living being (1).

8. Measuring device (5) for determining the 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 emitting the electrical pulses in step a), ■ an evaluation unit (7) and an associated sensor (10) for recording the temporal profiles of the electromyographic measurements in step b), wherein the evaluation unit (7) is set up to perform steps c) and d).

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